last updated by Venus on February 25, 2021 02:00 PM on behalf of Ankur Sinha.
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in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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Spinal and bulbar muscular atrophy (SBMA) is a neuromuscular disease caused by expansions of a polyglutamine (polyQ) tract in the androgen receptor (AR) gene. SBMA is associated with the progressive loss of lower motor neurons, together with muscle weakness and atrophy. PolyQ-AR is converted to a toxic species upon binding to its natural ligands, testosterone, and dihydrotestosterone (DHT). Our previous patch-clamp studies on a motor neuron-derived cell model of SBMA showed alterations in voltage-gated ion currents. Here, we identified and characterized chloride currents most likely belonging to the chloride channel-2 (ClC-2) subfamily, which showed significantly increased amplitudes in the SBMA cells. The treatment with the pituitary adenylyl cyclase-activating polypeptide (PACAP), a neuropeptide with a proven protective effect in a mouse model of SBMA, recovered chloride channel current alterations in SBMA cells. These observations suggest that the CIC-2 currents are affected in SBMA, an alteration that may contribute and potentially determine the pathophysiology of the disease.
in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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Highly active antiretroviral therapy (HAART) works effectively in inhibiting HIV replication in patients. However, the use of nucleoside reverse transcriptase inhibitors (NRTIs) often causes side effects of neuropathic pain, and its mechanism remains to be elucidated. Therefore, we aim to explore the mechanism of NRTIs-induced neuropathic pain at the transcriptome level. C57BL/6 J mice were given intraperitoneal injection of zalcitabine (ddC) or saline (control) for 2 weeks, during which the mechanical pain threshold of the mice was detected by von Frey test. Then the L3~L5 spinal segments of the mice were isolated and subsequently used for RNA sequencing (RNA-seq) on the last day of treatment. The mechanical pain threshold of mice given ddC decreased significantly. Compared with the control group, ddC caused significant changes in the expression of 135 genes, of which 66 upregulated and 69 downregulated. Enrichment analysis showed that the functions of these genes are mainly enriched in regulation of transcription, multicellular organism development, and cell differentiation, and the pathway is mainly enriched in the cGMP-PKG signaling pathway and AMPK signaling pathway. Furthermore, key genes such as Gabrd, Kcnd3, Npcd, Insr, Lypd6, Scd2, and Mef2d were also identified. These may serve as drug targets for the prevention or treatment of NRTI-induced neuropathic pain.
in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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Cortical disinhibition is the underlying pathological alteration contributing to neuropathic pain associated with peripheral nerve injury. Nerve injury resulting in disinhibition of the anterior cingulate cortex has been reported. However, the effect of optogenetic inhibition of the anterior cingulate cortex (ACC) on the sensory component of nerve injury–induced neuropathic pain has not been well studied. To investigate the feasibility of optogenetic ACC modulation, we injected an optogenetic virus or a null virus into the ACC of a nerve injury–induced neuropathic pain model. The unilateral ACC was modulated, and the optogenetic effect was measured by mechanical and thermal sensitivity tests. The assessment was performed in “pre—light off,” “stimulation—yellow light on,” and “post—light off” states. Optogenetic inhibition of the ACC in injury models revealed improved mechanical and thermal latencies with profound pain-relieving effects against nerve injury–induced neuropathic pain. The sensory thalamic discharge in electrophysiological in vivo recordings was also altered during laser stimulation. This finding indicates that hyperactivity of the ACC in nerve injury increases output to the spinothalamic tract through direct or indirect pathways. The direct photoinhibition of ACC neurons could play a vital role in restoring equilibrium and provide novel insight into techniques that can assuage peripheral nerve injury–induced neuropathic pain.
in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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The choroid plexus (CP) constitutes a barrier between the blood and the cerebrospinal fluid (CSF) which regulates the exchange of substances between these two fluids through mechanisms that are not completely understood. Polyamines as spermine, spermidine and putrescine are produced by all cells and are present in the CSF. Interestingly, their levels are altered in some neuronal disorders as Alzheimer’s and Parkinson’s diseases, thus increasing the interest in their signalling in the central nervous system (CNS). Cadaverine, on the other hand, is synthetized by the intestinal microbiome, suggesting that the presence of this bacterial metabolite in the CSF requires that it is up taken to the CNS across brain barriers. We knew that polyamines are detected by the olfactory signalling cascade operating at the CP, but the receptor involved had not been identified. The zebrafish TAAR13c was the only receptor known to bind a polyamine-cadaverine. Thus, we searched for a human receptor with homology to TAAR13c and found that some human TAARs including TAAR1 showed great homology. Then, we confirmed the expression of TAAR1 mRNA and protein in a human cell line of the CP, and in human CP samples. Calcium imaging assays after TAAR1 knockdown in these cells with a specific siRNA against TAAR1 showed a consistent reduction in the responses of these cells to cadaverine and spermidine, but not to spermine, suggesting that TAAR1 is activated by cadaverine and spermidine, but not spermine.
in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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Anti-inflammatory cytokine interleukin-10 (IL-10) plays a crucial role in controlling the resolution of inflammation. In this study, we aimed to assess gene expression and the level of IL-10 in the hippocampus and prefrontal cortex of rats, after a single injection of neurotoxicant trimethyltin chloride (TMT). It was shown that 4 weeks after the treatment with TMT, the level of IL-10 in the prefrontal cortex, but not in the hippocampus of TMT-treated rats, was increased. However, expression level of IL-10 mRNA was upregulated both in the hippocampus and in the prefrontal cortex 3 weeks after the injection. Concomitantly, within the same post-treatment period, the expression level of the cyclooxygenase-2 was upregulated in both brain structures, indicating the induction of neuroinflammation. Considering that TMT leads to the death of neurons mainly in the hippocampus, we assume that in contrast to the prefrontal cortex, the level of anti-inflammatory cytokine IL-10 in the hippocampus is not sufficiently increased to prevent the damaging effect of the neurotoxicant. Therefore, an exogenous increase in the level of IL-10 may be useful for the survival of neurons in conditions of neurotoxic damage to the hippocampus.
in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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Loss-of-function variants in CREBBP or EP300 result in Rubinstein–Taybi syndrome (RSTS). The previously reported cluster of variants in the last part of exon 30 and the beginning of exon 31 of CREBBP, overlapping with the ZNF2 (zinc finger, ZZ-type; residues 1701 to 1744) and ZNF3 (zinc finger, TAZ-type; residues 1764 to 1853) domains, is associated with atypical RSTS. The main features include developmental delay, short stature, microcephaly, distinctive facial features, autistic behavior, feeding difficulties, recurrent upper airway infections, and hearing impairment. Here, we report a 2-year-7-month-old Chinese girl presenting mild cognitive impairments, developmental delay, short stature, recurrent upper airway infections, and facial dysmorphism that resembled the phenotypes of previously reported atypical RSTS patients. The characteristic facial and limb dysmorphism for RSTS was absent in our patient. In addition, our patient exhibited novel phenotypes including attention deficit hyperactivity disorder (ADHD), sleep problem, and abnormal walking posture. Whole-exome sequencing (WES) identified a novel de novo in-frame deletion variant in the beginning of exon 30 of CREBBP (NM_004380:c.4897_4899delTTC, p.Phe1633del) in the HAT domain where no pathogenic variants have been previously reported to be responsible for atypical RSTS. Our case allows us to more accurately define the borders of the CREBBP coding sequence resulting in atypical RSTS, which are extended to the beginning of exon 30 (residue 1633) at the 5′ end of CREBBP in the HAT domain, and reveals novel phenotypes observed in our atypical Chinese RSTS patient.
in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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KLF4 is a zinc-finger transcription factor that plays an essential role in many biological processes, including neuroinflammation, neuron regeneration, cell proliferation, and apoptosis. Through effects on these processes, KLF4 has likely roles in Alzheimer’s disease, Parkinson’s disease, and traumatic brain injury. However, little is known about the role of KLF4 in more immediate behavioral processes that similarly depend upon broad changes in brain excitability, such as the sleep process. Here, behavioral approaches, western blot, and immunohistochemical experiments were used to explore the role of KLF4 on sedation and the potential mechanisms of those effects. The results showed that overexpression of KLF4 prolonged loss of righting reflex (LORR) duration in pentobarbital-treated mice and increased c-Fos expression in the lateral hypothalamus (LH) and the ventrolateral preoptic nucleus (VLPO), while it decreased c-Fos expression in the tuberomammillary nucleus (TMN). Moreover, overexpression of KLF4 reduced the expression of p53 in the hypothalamus and increased the expression of STAT3 in the hypothalamus. Therefore, these results suggest that KLF4 exerts sedative effects through the regulation of p53 and STAT3 expression, and it indicates a role of KLF4 ligands in the treatment of sleep disorders.
in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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Spinal cord microcirculation plays an important role in maintaining the function of spinal cord neurons and other cells. Previous studies have largely focused on the ability of microtubule stabilization to inhibit the fibroblast migration and promote axon regeneration after spinal cord injury (SCI). However, the effect of microtubule stabilization treatment on microcirculation reconstruction after SCI remains unclear. By using immunofluorescence, we found that microtubule stabilization treatment improved microcirculation reconstruction via increasing the number of microvessels, pericytes, and the perfused microvessels after SCI. To clarify the underlying mechanisms, rat brain microvascular endothelial cells and pericytes were subjected to glucose oxygen deprivation. By using flow cytometry and western blotting, we found that microtubule stabilization treatment inhibited apoptosis and migration of endothelial cells and pericytes but promoted proliferation and survival of endothelial cells and pericytes through upregulated expression of vascular endothelial growth factor A (VEGFA), VEGF receptor 2, platelet-derived growth factor-B (PDGFB), PDGF receptor β, and angiopoietin-1 after SCI. Taken together, this study provides evidence for the mechanisms underlying the promotion of microcirculation reconstruction after SCI by microtubule stabilization treatment. Importantly, this study suggests the potential of microtubule stabilization as a therapeutic target to reduce microcirculation dysfunction after SCI in the clinic.
in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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Parkinson’s disease (PD) is a chronic neurodegenerative condition characterized by motor symptoms such as bradykinesia, resting tremor, and rigidity. PD diagnosis is based on medical history, review of signs, symptoms, neurological and physical examinations. Unfortunately, by the time the disease is diagnosed, dopamine (DA) neuronal loss is often extended, thereby resulting in ineffective therapies. Recent evidence suggests that neuroinflammation may be pivotal during PD onset and progression. However, suitable cellular models and biomarkers to detect early signs of neuroinflammation are still missing. In this study, we developed a well-differentiated DAergic neuronal cell line where we triggered a neuroinflammatory response to assess the temporal expression of the tissue- and urokinase plasminogen activators (tPA and uPA) and their endogenous inhibitor (PAI-1) along with that of pro-inflammatory mediators and the neuronal marker nNOS. Human neuroblastoma cells SH-SY5Y were differentiated into DAergic neuronal-like cells using a combination of 12-O-tetradecanoylphorbol-13-acetate (TPA) and serum depletion. Terminally-differentiated neurons were then exposed to lipopolysaccharide (LPS) for short (up to 24 h) or long term (up to 10 days) to mimic acute or chronic inflammation. Results demonstrated that uPA protein expression was stably upregulated during chronic inflammation, whereas the expression of nNOS protein better reflected the cellular response to acute inflammation. Additional studies revealed that the temporal induction of uPA was associated with increased AKT phosphorylation, but did not seem to involve cAMP-responsive element-binding protein (CREB) activation, nor the mitogen-activated protein kinase (MAPK) pathway. In conclusion, our in vitro data suggests that nNOS and uPA may serve as viable candidate biomarkers of acute and chronic neuroinflammation.
in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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GSK-126 is recognized as an inhibitor of enhancer of zeste homolog-2 (EZH2) activity. Because of its inhibition of EZH2 activation, GSK-126 is considered a potential anti-tumor drug. EZH2 is a histone methyltransferase that catalyzes histone 3 tri-methylation at lysine 27 (H3K27me3), resulting in gene silencing. A previous report showed that decreased H3K27me3 levels in the hippocampus may promote seizure susceptibility, possibly restricting the clinical application of GSK-126. The role of GSK-126 in seizure susceptibility was investigated in this study. We first determined a critical concentration of pentamethazol (PTZ) under which mice exhibit no seizures. We then found that mice pretreated with GSK-126 and injected with the same concentration of PTZ experienced marked convulsions. Peripheral injections of GSK-126 decreased H3K27me3 levels in the hippocampus of mice, while some seizure-related genes (Oasl1, Sox7, armcx5, Ncx3, etc.) were found to be differentially expressed in the hippocampus of those mice . These differences in the expression levels might reflect the crucial role of these genes and related pathways in the promotion of seizure susceptibility. Our results suggest that GSK-126 promotes seizure susceptibility due to its role as an EZH2 inhibitor. These findings may provide evidence to support the development of GSK-126 as a clinical drug.
in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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The mutation of the homeostatic iron regulatory genes (HFE) impaired the hepatic hepcidin transcription leading to the chronic excess of the iron pool, with the adverse consequences of free radical oxidative damages. We herein reported the findings of Thai family members who had the compound of uncommon HFE rs2794719, together with transferrin (TF) rs1867504, transferrin receptor 2 (TfR2) rs7385804, and hemojuvelin (HJV) rs16827043 genetic variants involved in the hepcidin transcriptional pathway. These compounded genetic variants could produce the spectrum of clinical phenotypes that spanned from mild to moderate symptoms of chronic anemia to an established motor neuron disorder. The feasible pathophysiologies were the impairment of the transferrin receptor functions, which affected the endocytic uptake of halo-transferrin into the erythroblast precursors. Such a defect left the erythropoiesis depleted of their iron supply. These alterations also promoted the TfR-independent uptake of iron into other target tissues and left the TrF2/BMP-dependent-hepcidin activation pathway unattended. We used the predicted molecular interactive proteomes to support our speculated dysregulated iron metabolism. During the early stage of an elevated ferritin level, there was no inhibition of ferroportin activities from hepcidin. These pathophysiological processes went on to the point of an iron overload threshold. After that, the hepcidin transcription started to kick in with the resulting decreased serum iron levels and deterioration of clinical symptoms.
in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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Mechanisms and progression of ischemic injuries in the retina are still incompletely clarified. Therefore, the time course of microglia activation as well as resulting cytokine expression and downstream signaling were investigated. Ischemia was induced in one eye by transiently elevated intraocular pressure (60 min) followed by reperfusion; the other eye served as a control. Eyes were processed for RT-qPCR and immunohistochemistry analyses at 2, 6, 12, and 24 h as well as at 3 and 7 days. Already 2 h after ischemia, more microglia/macrophages were in an active state in the ischemia group. This was accompanied by an upregulation of pro-inflammatory cytokines, like IL-1β, IL-6, TNFα, and TGFβ. Activation of TLR3, TLR2, and the adaptor molecule Myd88 was also observed after 2 h. NFκB revealed a wave-like activation pattern. In addition, an extrinsic caspase pathway activation was noted at early time points, while enhanced numbers of cleaved caspase 3+ cells could be observed in ischemic retinae throughout the study. Retinal ischemia induced an early and strong microglia/macrophage response as well as cytokine and apoptotic activation processes. Moreover, in early and late ischemic damaging processes, TLR expression and downstream signaling were involved, suggesting an involvement in neuronal death in ischemic retinae.
in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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The effective prevention of postoperative cognitive dysfunction (POCD) needs to be explored, and the effect of preoperative pain on POCD remains unclear. We established a chronic pain model induced by chronic constriction injury (CCI) and models of acute pain and anxiety without pain in mice that were subsequently subjected to partial hepatectomy surgery. Morris water maze (MWM) tests were performed to evaluate the learning and memory abilities of the mice. ELISA was used to measure IL-1β, IL-6, and TNF-α in serum, and HPLC-MS was used to detect neurotransmitters in the prefrontal cortices and hippocampi of the mice. The results indicated that chronic pain induced by CCI might have significantly impaired the learning and memory abilities of mice, while acute pain and anxiety without pain only affected the memory abilities of mice. Perioperative acute pain increased the level of IL-1β in serum, and CCI might have increased the level of IL-6. CCI and acute pain increased dopamine (DA) levels in the cortex, similar to anxiety. Like anxiety, CCI increased 5-hydroxytryptamine (5-HT) levels in the prefrontal cortex and hippocampus. Acute pain led to a decrease in the acetylcholine (ACH) level in the hippocampus. Our results suggest that acute pain and CCI-induced chronic pain might aggravate postoperative cognitive dysfunction via neurotransmitters and by changing the levels of inflammatory factors such as IL-1β and IL-6.
in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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Multiple sclerosis (MS) is a multifactorial, central nervous system, immune-mediated disease characterized by inflammation, demyelination, and neurodegeneration. Evidence suggests a steady rise in MS prevalence over the past five decades in the United States and around the world. Even with increased understanding of immunology, the specific etiological trigger of MS remains unknown. Evidence suggests that oxidative/nitroxidative stress is an important contributor to MS etiology, progression, and clinical symptoms. A multifaceted treatment approach aimed at counteracting oxidative/nitroxidative stress including MS disease–modifying medications, Mediterranean style diet, stress-relieving activities, smoking and alcohol cessation, exercise, and peer support programs is the best way to treat the disease.
in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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Due to molecular mimicry, maternal antibacterial antibodies are suspected to promote neurodevelopmental changes in the offspring that finally can cause disorders like autism and schizophrenia. Using a human first trimester prenatal brain multiprotein array (MPA), we demonstrate here that antibodies to the digestive tract bacteria Helicobacter pylori (α-HPy) and Campylobacter jejuni (α-CJe) interact with different synaptic proteins, including the calcium sensor synaptotagmin 5 (Syt5). Interactions of both antisera with Syt5 were confirmed by Western blot with a HEK293-cells overexpression lysate of this protein. Immunofluorescence and Western blotting revealed SiMa cells to express Syt5, which also co-migrated with a band/spot labeled by either α-HPy or α-CJe. Functionally, a 12-h pretreatment of SiMa cells with 10 μg/ml of either α-HPy or α-CJe resulted in a significant reduction of acetylcholine(ACh)-dependent calcium signals as compared to controls. Also ACh-dependent vesicle recycling was significantly reduced in cells pretreated with either α-HPy or α-CJe. Similar effects were observed upon pretreatment of SiMa cells with Syt5-specific antibodies. In conclusion, the present study supports the view that prenatal maternal antibacterial immune responses towards HPy and by this to Syt5 are able to cause functional changes, which in the end might contribute also to neurodevelopmental disorders.
in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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Parkinson’s disease (PD) is a progressive neurodegenerative disease affecting the ventral midbrain dopaminergic neurons, resulting in motor defects mainly tremor, rigidity, and bradykinesia along with a wide array of non-motor symptoms. The current study is focused on determining the potential druggable targets of PD by consolidating gene expression profiling and network methodology. Initially, the differentially expressed genes were established from which the central network was constructed by assimilating the interacting partners. Investigating the topological parameters of the network, the genes SYT1, CXCR4, CDC42, KIT, RET, DRD2, NTN1, PRKACB, KDR, NR4A2, SLC18A2, CCK, TH, KCNJ6, and TAC1 were identified as the hub genes and can be explored as potential candidate genes for PD therapeutics. Gene ontology and cluster analysis of the hub genes has provided further insights about the pathophysiology of the disease. Among the hub genes, PRKACB is observed in relatively all the enriched pathways which are modulated by G protein-coupled receptors through protein kinases. Further, we noticed SYT1 as a novel biomarker for PD. Moreover, the regulatory network was constructed with the hub genes as seed nodes with associated transcription factors (TFs) and microRNA (miRNAs). In this analysis, we identified MYC as the major TF and the miRNAs miR-21, miR-155, miR-7, and miR26A1 have a significant role in modulating the hub genes. Briefly, these significant hub genes and their enriched pathways, TFs, and miRNAs have aided in the better understanding of molecular mechanisms underlying PD and its potential core target genes.
in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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Recent studies have shed light on the involvement of long non-coding RNAs (lncRNAs) in the initiation and development of stroke. However, the regulatory function of many lncRNAs in large artery atherosclerosis (LAA) has not been fully elucidated. Based on the competing endogenous RNA (ceRNA) hypothesis recently proposed by Pandolfi, the present study was conducted using experimental techniques and bioinformatics to investigate the expression and regulatory function of a lncRNA involved in the development of LAA. The lncRNAs differentially expressed in stroke were obtained using meta-analysis, and one lncRNA was selected for experimental studies on patients with LAA (n = 100) and healthy controls (n = 100) using quantitative real-time polymerase chain reaction (qRT-PCR). The patients were also evaluated through meta-analysis to identify the function of the selected lncRNA, miRNAs, and mRNAs with altered expression in stroke. Finally, the experimental results and meta-analysis findings were integrated, and different functional groups were assigned. The results indicated that the level of lncRNA-RUNX1-IT1 was significantly lower in the patients with LAA compared to the healthy control subjects (p > 0.05). Logistic regression analyses revealed that the expression of lncRNA-RUNX1-IT1 was inversely correlated with LAA (P = 009, OR = 0.871, 95% CI: 0.786–0.965). In addition, a network of differentially expressed genes (DE genes) was created for miRNAs and mRNAs based on their association with lncRNA-RUNX1-IT1. Functional analysis showed that the DE genes in the network are involved in the apoptosis and alternative splicing of RNAs. The findings of the present study suggest that the downregulation of lncRNA-RUNX1-IT1 is associated with LAA development by interrupting the regulatory network of cells. The results of network analysis demonstrated that the lncRNA-RUNX1-IT1 could influence the expression of mRNAs and miRNAs involved in the apoptosis and alternative splicing of RNAs.
in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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MgSO4 has been used for the past two decades as neuroprotective treatment in a variety of preterm conditions. Despite the putative advantages of MgSO4 as a neuroprotective agent in the preterm brain, the short- and long-term molecular function of MgSO4 as a neuroprotective agent has not been fully elucidated. Neuregulin (NRG1)-ErbB4 signaling plays a critical role in embryonic brain development, in the biology of dopaminergic, GABAergic, and glutamatergic systems. We hypothesize that this pathway may be associated with the neuroprotective role of MgSO4. The current study aims to investigate the ability of MgSO4 to modulate the normal developing expression pattern of selected genes related to the NRG1-ErbB, dopaminergic, GABAergic, and glutamatergic systems. We demonstrate that overall short-term treatment of dam rats with MgSO4 affects the expression of fetal brain NRG1, NRG3, ErbB4, GAD67, tyrosine hydroxylase (TH), dopamine D2 and D1 receptors, GluN1, and GluN2B. More specifically, the administration of MgSO4 alters the expression of NRG-ErbB, GAD67, TH, and D2R at early gestation day 16 (GD16) regardless of the activation of the maternal immune system by lipopolysaccharide (LPS). Our data suggest that MgSO4 treatment may affect the expression of major neuronal systems and pathways mostly at an early gestation day. These changes might be an initial clue (foundation stone) in the molecular mechanism that underlies the beneficial effect of MgSO4 as a neuroprotective agent for the developmental brain.
in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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Psychosocial stress has been widely reported to contribute to psychiatric disturbances. Perturbations in the enzymes of GABAergic and cholinergic systems have been implicated as precursors in different stress-related neuropsychiatric diseases. Targeting glutamic acid decarboxylase-67 kDa (GAD67) and acetylcholinesterase (AChE) via oxidative, nitrergic, and neuroinflammatory mechanisms have been recognized as prospective strategies for the prevention of psychosocial stress-induced behavioral impairments. Naringin, a neuro-active flavonoid compound isolated from citrus fruits, has been shown to produce memory-enhancing, antiepileptic, antidepressant, and anti-inflammatory activities similarly to ginseng, a very potent adaptogen. In this communication, we assessed the effect of naringin on social-defeat stress (SDS)-induced behavioral, GABAergic, cholinergic, oxidative, nitrergic, and neuroinflammatory changes in mice using the resident–intruder paradigm. The intruder male mice were culled into six groups. Groups 1 and 2 (normal- and SDS-controls) received sterile saline, groups 3–5 were given naringin (25-100 mg/kg, i.p.) whereas group 6 had ginseng (50 mg/kg, i.p.) daily for 14 days, but followed by 10 min SDS (physical and psychological) exposure to groups 2–6 with aggressor–resident mice. Behavioral effects using Y-maze, elevated-plus maze, sociability, and tail-suspension tests were assessed on day 14. GAD67, AChE enzymes, and biomarkers of oxidative, nitrergic, and neuroinflammatory changes were assayed in the striatum, prefrontal cortex, and hippocampus. Naringin and ginseng reversed all SDS-induced behavioral impairments. Naringin increased the levels of GAD67 and decreased AChE activities in the striatum, prefrontal cortex, and hippocampus. Furthermore, naringin reduced pro-inflammatory cytokines (TNF-α, IL-6), malondialdehyde, nitrite concentrations, and increased glutathione levels in a region-dependent manner. Our study suggests that naringin attenuated SDS-induced behavioral endophenotypes of neuropsychiatric disease through increased GAD67 synthesis, inhibition of AChE activity, oxidative, nitrergic stress, and neuroinflammatory processes in stress-sensitive brain regions.
in Journal of Molecular Neuroscience on March 01, 2021 12:00 AM.
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At the end of 2020, policy responses to the SARS-CoV-2 outbreak have been shaken by the emergence of virus variants, impacting public health and policy measures worldwide. The emergence of these strains suspected to be more contagious, more severe, or even resistant to antibodies and vaccines, seem to have taken by surprise health services and policymakers, struggling to adapt to the new variants constraints. Anticipating the emergence of these mutations to plan ahead adequate policies, and understanding how human behaviors may affect the evolution of viruses by coevolution, are key challenges. In this article, we propose coevolution with genetic algorithms (GAs) as a credible approach to model this relationship, highlighting its implications, potential and challenges. Because of their qualities of exploration of large spaces of possible solutions, capacity to generate novelty, and natural genetic focus, GAs are relevant for this issue. We present a dual GA model in which both viruses aiming for survival and policy measures aiming at minimising infection rates in the population, competitively evolve. This artificial coevolution system may offer us a laboratory to "debug" our current policy measures, identify the weaknesses of our current strategies, and anticipate the evolution of the virus to plan ahead relevant policies. It also constitutes a decisive opportunity to develop new genetic algorithms capable of simulating much more complex objects. We highlight some structural innovations for GAs for that virus evolution context that may carry promising developments in evolutionary computation, artificial life and AI.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 25, 2021 01:30 AM.
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In this paper, we are introducing a novel model of artificial intelligence, the functional neural network for modeling of human decision-making processes. This neural network is composed of multiple artificial neurons racing in the network. Each of these neurons has a similar structure programmed independently by the users and composed of an intention wheel, a motor core and a sensory core representing the user itself and racing at a specific velocity. The mathematics of the neuron's formulation and the racing mechanism of multiple nodes in the network will be discussed, and the group decision process with fuzzy logic and the transformation of these conceptual methods into practical methods of simulation and in operations will be developed. Eventually, we will describe some possible future research directions in the fields of finance, education and medicine including the opportunity to design an intelligent learning agent with application in business operations supervision. We believe that this functional neural network has a promising potential to transform the way we can compute decision-making and lead to a new generation of neuromorphic chips for seamless human-machine interactions.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 25, 2021 01:30 AM.
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Non-pharmaceutical interventions (NPIs) are effective measures to contain a pandemic. Yet, such control measures commonly have a negative effect on the economy. Here, we propose a macro-level approach to support resolving this Health-Economy Dilemma (HED). First, an extension to the well-known SEIR model is suggested which includes an economy model. Second, a bi-objective optimization problem is defined to study optimal control policies in view of the HED problem. Next, several multi-objective evolutionary algorithms are applied to perform a study on the health-economy performance trade-offs that are inherent to the obtained optimal policies. Finally, the results from the applied algorithms are compared to select a preferred algorithm for future studies. As expected, for the proposed models and strategies, a clear conflict between the health and economy performances is found. Furthermore, the results suggest that the guided usage of NPIs is preferable as compared to refraining from employing such strategies at all. This study contributes to pandemic modeling and simulation by providing a novel concept that elaborates on integrating economic aspects while exploring the optimal moment to enable NPIs.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 25, 2021 01:30 AM.
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We study the problem of modeling a binary operation that satisfies some algebraic requirements. We first construct a neural network architecture for Abelian group operations and derive a universal approximation property. Then, we extend it to Abelian semigroup operations using the characterization of associative symmetric polynomials. Both models take advantage of the analytic invertibility of invertible neural networks. For each case, by repeating the binary operations, we can represent a function for multiset input thanks to the algebraic structure. Naturally, our multiset architecture has size-generalization ability, which has not been obtained in existing methods. Further, we present modeling the Abelian group operation itself is useful in a word analogy task. We train our models over fixed word embeddings and demonstrate improved performance over the original word2vec and another naive learning method.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 25, 2021 01:30 AM.
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Real-world multiobjective optimization problems usually involve conflicting objectives that change over time, which requires the optimization algorithms to quickly track the Pareto optimal front (POF) when the environment changes. In recent years, evolutionary algorithms based on prediction models have been considered promising. However, most existing approaches only make predictions based on the linear correlation between a finite number of optimal solutions in two or three previous environments. These incomplete information extraction strategies may lead to low prediction accuracy in some instances. In this paper, a novel prediction algorithm based on incremental support vector machine (ISVM) is proposed, called ISVM-DMOEA. We treat the solving of dynamic multiobjective optimization problems (DMOPs) as an online learning process, using the continuously obtained optimal solution to update an incremental support vector machine without discarding the solution information at earlier time. ISVM is then used to filter random solutions and generate an initial population for the next moment. To overcome the obstacle of insufficient training samples, a synthetic minority oversampling strategy is implemented before the training of ISVM. The advantage of this approach is that the nonlinear correlation between solutions can be explored online by ISVM, and the information contained in all historical optimal solutions can be exploited to a greater extent. The experimental results and comparison with chosen state-of-the-art algorithms demonstrate that the proposed algorithm can effectively tackle dynamic multiobjective optimization problems.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 25, 2021 01:30 AM.
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Complex systems fail. I argue that failures can be a blueprint characterizing living organisms and biological intelligence, a control mechanism to increase complexity in evolutionary simulations, and an alternative to classical fitness optimization. Imitating biological successes in Artificial Life and Artificial Intelligence can be misleading; imitating failures offers a path towards understanding and emulating life it in artificial systems.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 25, 2021 01:30 AM.
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In recent years, graph neural networks (GNNs) have gained increasing attention, as they possess excellent capability of processing graph-related problems. In practice, hyperparameter optimisation (HPO) is critical for GNNs to achieve satisfactory results, but this process is costly because the evaluations of different hyperparameter settings require excessively training many GNNs. Many approaches have been proposed for HPO which aims to identify promising hyperparameters efficiently. In particular, genetic algorithm (GA) for HPO has been explored, which treats GNNs as a black-box model, of which only the outputs can be observed given a set of hyperparameters. However, because GNN models are extremely sophisticated and the evaluations of hyperparameters on GNNs are expensive, GA requires advanced techniques to balance the exploration and exploitation of the search and make the optimisation more effective given limited computational resources. Therefore, we proposed a tree-structured mutation strategy for GA to alleviate this issue. Meanwhile, we reviewed the recent HPO works which gives the room to the idea of tree-structure to develop, and we hope our approach can further improve these HPO methods in the future.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 25, 2021 01:30 AM.
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Hippocampal reverse replay is thought to contribute to learning, and particularly reinforcement learning, in animals. We present a computational model of learning in the hippocampus that builds on a previous model of the hippocampal-striatal network viewed as implementing a three-factor reinforcement learning rule. To augment this model with hippocampal reverse replay, a novel policy gradient learning rule is derived that associates place cell activity with responses in cells representing actions. This new model is evaluated using a simulated robot spatial navigation task inspired by the Morris water maze. Results show that reverse replay can accelerate learning from reinforcement, whilst improving stability and robustness over multiple trials. As implied by the neurobiological data, our study implies that reverse replay can make a significant positive contribution to reinforcement learning, although learning that is less efficient and less stable is possible in its absence. We conclude that reverse replay may enhance reinforcement learning in the mammalian hippocampal-striatal system rather than provide its core mechanism.
in arXiv: Quantitative Biology: Neurons and Cognition on February 25, 2021 01:30 AM.
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In real-world applications, many optimization problems have the time-linkage property, that is, the objective function value relies on the current solution as well as the historical solutions. Although the rigorous theoretical analysis on evolutionary algorithms has rapidly developed in recent two decades, it remains an open problem to theoretically understand the behaviors of evolutionary algorithms on time-linkage problems. This paper takes the first step to rigorously analyze evolutionary algorithms for time-linkage functions. Based on the basic OneMax function, we propose a time-linkage function where the first bit value of the last time step is integrated but has a different preference from the current first bit. We prove that with probability $1-o(1)$, randomized local search and $(1+1)$ EA cannot find the optimum, and with probability $1-o(1)$, $(\mu+1)$ EA is able to reach the optimum.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 25, 2021 01:30 AM.
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Nature Physics, Published online: 25 February 2021; doi:10.1038/s41567-021-01188-1
SARS, MERS and now SARS-CoV-2 are unlikely to be the last emerging infections we face during our lifetimes. Tracing contacts both forward and backward through our heterogeneous populations will prove essential to future response strategies.in Nature Physics on February 25, 2021 12:00 AM.
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Nature Physics, Published online: 25 February 2021; doi:10.1038/s41567-021-01187-2
Contact tracing is key to epidemic control, but network analysis now suggests that whom you infect may not be as pertinent a question as who infected you. Biases due to contact heterogeneity reveal the efficacy of backward over forward tracing.in Nature Physics on February 25, 2021 12:00 AM.
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Nature Communications, Published online: 25 February 2021; doi:10.1038/s41467-021-21371-5
Treatments for Fabry disease, an inherited lysosomal disorder caused by the deficiency of the enzyme alpha-galactosidase A, are not fully efficacious. Here the authors report a single-arm phase I trial of gene therapy with autologous, lentivirus-transduced, hematopoietic cells that express alpha-galactosidase A to demonstrate that this approach is safe in five patients with Fabry disease.in Nature Communications on February 25, 2021 12:00 AM.
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Nature, Published online: 25 February 2021; doi:10.1038/d41586-021-00496-z
As Horizon Europe issues its first call for grants, Nature reviews some big changes — from open science to goal-oriented 'missions'.in Nature on February 25, 2021 12:00 AM.
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in Journal of Neurology on February 25, 2021 12:00 AM.
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in Experimental Brain Research on February 25, 2021 12:00 AM.
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in The Cerebellum on February 25, 2021 12:00 AM.
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Studies have shown that the cerebellar vermis is involved in the perception of motion. However, it is unclear how the cerebellum influences motion perception. tDCS is a non-invasive brain stimulation technique that can reduce (through cathodal stimulation) or increase neuronal excitability (through anodal stimulation). To explore the nature of the cerebellar involvement on large-field global motion perception (i.e., optic flow-like motion), we applied tDCS on the cerebellar midline while participants performed an optic flow motion discrimination task. Our results show that anodal tDCS improves discrimination threshold for optic flow perception, but only for left-right motion in contrast to up-down motion discrimination. This result was evident within the first 10 min of stimulation and was also found post-stimulation. Cathodal stimulation did not have any significant effects on performance in any direction. The results show that discrimination of optic flow can be improved with tDCS of the cerebellar midline and provide further support for the role of the human midline cerebellum in the perception of optic flow.
in The Cerebellum on February 25, 2021 12:00 AM.
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A noticeable change of the male-to-female sex ratio (SR) has been observed in Amyotrophic Lateral Sclerosis (ALS) leading to an apparent regression of SR with time (SR close to 1:1).
To provide a global SR estimate and investigate its relation with respect to population age.
A systematic review and meta-analysis was conducted including only population-based studies with a high-quality methodology in European ancestral origin population. Male-to-female SR was estimated by three different measures: SR number, SR crude incidence and SR standardized incidence. Standard and dose–response meta-analyses were performed to assess the pooled SR measures (irrespective of population age) and the evolution of the SR measures with respect to population age, respectively. Potential sources of heterogeneity were investigated via meta-regression.
Overall, 3254 articles were retrieved in the literature search. Thirty-nine studies stratified by time periods were included. The overall pooled male-to-female ratio was 1.28 (95% CI 1.23–1.32) for SR number, 1.33 (95% CI 1.29–1.38) for SR crude incidence and 1.35 (95% CI 1.31–1.40) for SR standardized incidence. The SR number with respect to population age reveals a progressive reduction of SR at increasing age, while the SR crude incidence in relation to age displays a U-shaped curve.
The number and the incidence of ALS cases were consistently higher in males than females. Dose–response meta-analysis showed that SR measures change with respect to population age. Further original research is needed to clarify if our findings are reproducible in other populations.
in Journal of Neurology on February 25, 2021 12:00 AM.
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Caregiver burden is high among caregivers of PD patients (CPD). Neuropsychiatric symptoms are leading contributors to CPD burden, but whether different symptoms differentially impact domains of caregiver burden is not known. Our objective was to examine which neuropsychiatric symptoms and demographic factors contribute to different domains of caregiver burden in PD.
This was a cross-sectional online survey study. Participants were recruited from the Fox Insight (FI) study and were eligible if they identified themselves as a CPD. The primary outcome was the Caregiver Burden Inventory (CBI) total score and its 5 sub-domain scores. The Neuropsychiatric Inventory Questionnaire (NPI-Q) assessed caregiver-reported neuropsychiatric symptoms in the care recipient. Multivariable linear regression models were used to characterize the associations between NPI-Q symptom severity scores and CBI scores. Covariates were caregiver age, sex, education, and caregiving duration.
The sample consisted of 450 CPD, mean age 65.87 (SD 10.39) years, 74% females. After adjusting for covariates, CBI total score was predicted by NPI-Q total score (β = 1.96, p < 0.001); model adjusted R2 = 39.2%. Anxiety severity had the largest effect size [standardized β (sβ) = 0.224] on the time-dependency domain, which was also associated with female sex (sβ = − 0.133) and age (sβ = 0.088). Severity of disinhibition (sβ = 0.218), agitation (sβ = 0.199), and female sex (sβ = 0.104) were associated with greater emotional burden.
Our findings indicate that demographic characteristics and specific neuropsychiatric symptoms contribute differentially to domains of caregiver burden. Tailored interventions to support CPD are needed.
in Journal of Neurology on February 25, 2021 12:00 AM.
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The visual, vestibular, and haptic perceptual systems are each able to detect self-motion. Such information can be integrated during locomotion to perceive traversed distances. The process of distance integration is referred to as odometry. Visual odometry relies on information in optic flow patterns. For haptic odometry, such information is associated with leg movement patterns. Recently, it has been shown that haptic odometry is differently calibrated for different types of gaits. Here, we use this fact to examine the relative contributions of the perceptual systems to odometry. We studied a simple homing task in which participants travelled set distances away from an initial starting location (outbound phase), before turning and attempting to walk back to that location (inbound phase). We manipulated whether outbound gait was a walk or a gallop-walk. We also manipulated the outbound availability of optic flow. Inbound reports were performed via walking with eyes closed. Consistent with previous studies of haptic odometry, inbound reports were shorter when the outbound gait was a gallop-walk. We showed that the availability of optic flow decreased this effect. In contrast, the availability of optic flow did not have an observable effect when the outbound gait was walking. We interpreted this to suggest that visual odometry and haptic odometry via walking are similarly calibrated. By measuring the decrease in shortening in the gallop-walk condition, and scaling it relative to the walk condition, we estimated a relative contribution of optic flow to odometry of 41%. Our results present a proof of concept for a new, potentially more generalizable, method for examining the contributions of different perceptual systems to odometry, and by extension, path integration. We discuss implications for understanding human wayfinding.
in Experimental Brain Research on February 25, 2021 12:00 AM.
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Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working capacity and have potential applications in various fields such as rehabilitation, affective computing, robotics, gaming, and neuroscience. Significant research efforts on a global scale have delivered common platforms for technology standardization and help tackle highly complex and non-linear brain dynamics and related feature extraction and classification challenges. Time-variant psycho-neurophysiological fluctuations and their impact on brain signals impose another challenge for BCI researchers to transform the technology from laboratory experiments to plug-and-play daily life. This review summarizes state-of-the-art progress in the BCI field over the last decades and highlights critical challenges.
in Frontiers in Systems Neuroscience on February 25, 2021 12:00 AM.
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Neuropathic pain is a kind of chronic pain that remains difficult to treat due to its complicated underlying mechanisms. Accumulating evidence has indicated that enhanced synaptic plasticity of nociceptive interneurons in the superficial spinal dorsal horn contributes to the development of neuropathic pain. Neuroligin1 (NL1) is a type of excitatory postsynaptic adhesion molecule, which can mediate excitatory synaptic activity, hence promoting neuronal activation. Vglut2 is the most common marker of excitatory glutamatergic neurons. To explore the role of NL1 in excitatory neurons in nociceptive regulation, we used transgenic mice with cre recombinase expression driven by the Vglut2 promoter combined with viral vectors to knockdown the expression of NL1 in excitatory neurons in the spinal dorsal horn. We found that NL1 was upregulated in the L4–L6 spinal dorsal horn in Vglut2-cre+/– mouse subjected to spared nerve injury (SNI). Meanwhile, the expression of phosphorylated cofilin (p-cofilin) and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor subunit 1 (GluR1) was also increased. Spinal microinjection of a cre-dependent NL1-targeting RNAi in Vglut2-cre+/– mouse alleviated the neuropathic pain-induced mechanical hypersensitivity and reduced the increase in p-cofilin and GluR1 caused by SNI. Taken together, NL1 in excitatory neurons regulates neuropathic pain by promoting the SNI-dependent increase in p-cofilin and GluR1 in the spinal dorsal horn. Our study provides a better understanding of the role of NL1 in excitatory neurons, which might represent a possible therapeutic target for alleviating neuropathic pain.
in Frontiers in Molecular Neuroscience on February 25, 2021 12:00 AM.
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Protein homeostasis serves as an important step in regulating diverse cellular processes underlying the function and development of the nervous system. In particular, the ubiquitination proteasome system (UPS), a universal pathway mediating protein degradation, contributes to the development of numerous synaptic structures, including the Drosophila olfactory-associative learning center mushroom body (MB), thereby affecting associated function. Here, we describe the function of a newly characterized Drosophila F-box protein CG5003, an adaptor for the RING-domain type E3 ligase (SCF complex), in MB development. Lacking CG5003 ubiquitously causes MB γ axon pruning defects and selective CG5003 expression in pan-neurons leads to both γ axon and α/β lobe abnormalities. Interestingly, change in CG5003 expression in MB neurons does not cause any abnormalities in axons, suggesting that CG5003 functions in cells extrinsic to MB to regulate its development. Mass spectrum analysis indicates that silencing CG5003 expression in all neurons affects expression levels of proteins in the cell and structural morphogenesis, transcription regulator activity, and catalytic activity. Our findings reinforce the importance of UPS and identify a new factor in regulating neuronal development as exemplified by the synaptic structure MB.
in Frontiers in Molecular Neuroscience on February 25, 2021 12:00 AM.
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Genome-wide sequencing technologies have greatly contributed to our understanding of the genetic basis of neurodevelopmental disorders such as autism spectrum disorder (ASD). Interestingly, a number of ASD-related genes express natural antisense transcripts (NATs). In some cases, these NATs have been shown to play a regulatory role in sense strand gene expression and thus contribute to brain function. However, a detailed study examining the transcriptional relationship between ASD-related genes and their NAT partners is lacking. We performed strand-specific, deep RNA sequencing to profile expression of sense and antisense reads with a focus on 100 ASD-related genes in medial prefrontal cortex (mPFC) and striatum across mouse post-natal development (P7, P14, and P56). Using de novo transcriptome assembly, we generated a comprehensive long non-coding RNA (lncRNA) transcriptome. We conducted BLAST analyses to compare the resultant transcripts with the human genome and identified transcripts with high sequence similarity and coverage. We assembled 32861 de novo antisense transcripts mapped to 12182 genes, of which 1018 are annotated by Ensembl as lncRNA. We validated the expression of a subset of selected ASD-related transcripts by PCR, including Syngap1 and Cntnap2. Our analyses revealed that more than 70% (72/100) of the examined ASD-related genes have one or more expressed antisense transcripts, suggesting more ASD-related genes than previously thought could be subject to NAT-mediated regulation in mice. We found that expression levels of antisense contigs were mostly positively correlated with their cognate coding sense strand RNA transcripts across developmental age. A small fraction of the examined transcripts showed brain region specific enrichment, indicating possible circuit-specific roles. Our BLAST analyses identified 110 of 271 ASD-related de novo transcripts with >90% identity to the human genome at >90% coverage. These findings, which include an assembled de novo antisense transcriptome, contribute to the understanding of NAT regulation of ASD-related genes in mice and can guide NAT-mediated gene regulation strategies in preclinical investigations toward the ultimate goal of developing novel therapeutic targets for ASD.
in Frontiers in Molecular Neuroscience on February 25, 2021 12:00 AM.
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One of the major unsolved mysteries of biological science concerns the question of where and in what form information is stored in the brain. I propose that memory is stored in the brain in a mechanically encoded binary format written into the conformations of proteins found in the cell-extracellular matrix (ECM) adhesions that organise each and every synapse. The MeshCODE framework outlined here represents a unifying theory of data storage in animals, providing read-write storage of both dynamic and persistent information in a binary format. Mechanosensitive proteins that contain force-dependent switches can store information persistently, which can be written or updated using small changes in mechanical force. These mechanosensitive proteins, such as talin, scaffold each synapse, creating a meshwork of switches that together form a code, the so-called MeshCODE. Large signalling complexes assemble on these scaffolds as a function of the switch patterns and these complexes would both stabilise the patterns and coordinate synaptic regulators to dynamically tune synaptic activity. Synaptic transmission and action potential spike trains would operate the cytoskeletal machinery to write and update the synaptic MeshCODEs, thereby propagating this coding throughout the organism. Based on established biophysical principles, such a mechanical basis for memory would provide a physical location for data storage in the brain, with the binary patterns, encoded in the information-storing mechanosensitive molecules in the synaptic scaffolds, and the complexes that form on them, representing the physical location of engrams. Furthermore, the conversion and storage of sensory and temporal inputs into a binary format would constitute an addressable read-write memory system, supporting the view of the mind as an organic supercomputer.
in Frontiers in Molecular Neuroscience on February 25, 2021 12:00 AM.
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Structural network alterations in Alzheimer’s disease (AD) are related to worse cognitive impairment. The aim of this study was to quantify the alterations in gray matter associated with impaired cognition and their pathological biomarkers in AD-spectrum patients.
MethodsWe extracted gray matter networks from 3D-T1 magnetic resonance imaging scans, and a graph theory analysis was used to explore alterations in the network metrics in 34 healthy controls, 70 mild cognitive impairment (MCI) patients, and 40 AD patients. Spearman correlation analysis was computed to investigate the relationships among network properties, neuropsychological performance, and cerebrospinal fluid pathological biomarkers (i.e., Aβ, t-tau, and p-tau) in these subjects.
ResultsAD-spectrum individuals demonstrated higher nodal properties and edge properties associated with impaired memory function, and lower amyloid-β or higher tau levels than the controls. Furthermore, these compensations at the brain regional level in AD-spectrum patients were mainly in the medial temporal lobe; however, the compensation at the whole-brain network level gradually extended from the frontal lobe to become widely distributed throughout the cortex with the progression of AD.
ConclusionThe findings provide insight into the alterations in the gray matter network related to impaired cognition and pathological biomarkers in the progression of AD. The possibility of compensation was detected in the structural networks in AD-spectrum patients; the compensatory patterns at regional and whole-brain levels were different and the clinical significance was highlighted.
in Frontiers in Neuroscience: Brain Imaging Methods on February 25, 2021 12:00 AM.
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Modulating endogenous regenerative processes may represent a suitable treatment for central nervous system (CNS) injuries, such as stroke or trauma. Neural stem/progenitor cells (NS/PCs), which naturally reside in the subventricular zone (SVZ) of the adult brain, proliferate and differentiate to other cell types, and therefore may compensate the negative consequences of ischemic injury. The fate of NS/PCs in the developing brain is largely influenced by Wingless/Integrated (Wnt) signaling; however, its role in the differentiation of adult NS/PCs under ischemic conditions is still enigmatic. In our previous study, we identified the Wnt/β-catenin signaling pathway as a factor promoting neurogenesis at the expense of gliogenesis in neonatal mice. In this study, we used adult transgenic mice in order to assess the impact of the canonical Wnt pathway modulation (inhibition or hyper-activation) on NS/PCs derived from the SVZ, and combined it with the middle cerebral artery occlusion (MCAO) to disclose the effect of focal cerebral ischemia (FCI). Based on the electrophysiological properties of cultured cells, we first identified three cell types that represented in vitro differentiated NS/PCs – astrocytes, neuron-like cells, and precursor cells. Following FCI, we detected fewer neuron-like cells after Wnt signaling inhibition. Furthermore, the immunohistochemical analysis revealed an overall higher expression of cell-type-specific proteins after FCI, indicating increased proliferation and differentiation rates of NS/PCs in the SVZ. Remarkably, Wnt signaling hyper-activation increased the abundance of proliferating and neuron-like cells, while Wnt pathway inhibition had the opposite effect. Finally, the expression profiling at the single cell level revealed an increased proportion of neural stem cells and neuroblasts after FCI. These observations indicate that Wnt signaling enhances NS/PCs-based regeneration in the adult mouse brain following FCI, and supports neuronal differentiation in the SVZ.
in Frontiers in Neuroscience: Neurogenesis on February 25, 2021 12:00 AM.
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Transcranial magnetic stimulation (TMS) with simultaneous electroencephalography applied to the primary motor cortex provides two parameters for cortical excitability: motor evoked potentials (MEPs) and TMS-evoked potentials (TEPs). This study aimed to evaluate the effects of systematic coil shifts on both the TEP N100 component and MEPs in addition to the relationship between both parameters. In 12 healthy adults, the center of a standardized grid was fixed above the hot spot of the target muscle of the left primary motor cortex. Twelve additional positions were arranged in a quadratic grid with positions between 5 and 10 mm from the hot spot. At each of the 13 positions, TMS single pulses were applied. The topographical maximum of the resulting N100 was located ipsilateral and slightly posterior to the stimulation site. A source analysis revealed an equivalent dipole localized more deeply than standard motor cortex coordinates that could not be explained by a single seeded primary motor cortex dipole. The N100 topography might not only reflect primary motor cortex activation, but also sum activation of the surrounding cortex. N100 amplitude and latency decreased significantly during stimulation anterior-medial to the hot spot although MEP amplitudes were smaller at all other stimulation sites. Therefore, N100 amplitudes might be suitable for detecting differences in local cortical excitability. The N100 topography, with its maximum located posterior to the stimulation site, possibly depends on both anatomical characteristics of the stimulated cortex and differences in local excitability of surrounding cortical areas. The less excitable anterior cortex might contribute to a more posterior maximum. There was no correlation between N100 and MEP amplitudes, but a single-trial analysis revealed a trend toward larger N100 amplitudes in trials with larger MEPs. Thus, functionally efficient cortical excitation might increase the probability of higher N100 amplitudes, but TEPs are also generated in the absence of MEPs.
in Frontiers in Neuroscience: Brain Imaging Methods on February 25, 2021 12:00 AM.
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There is great interest in drug discovery programs targeted at the aggregation of the 42-residue form of the amyloid β peptide (Aβ42), since this molecular process is closely associated with Alzheimer’s disease. The use of bicyclic peptides may offer novel opportunities for the effective modification of Aβ42 aggregation and the inhibition of its cytotoxicity, as these compounds combine the molecular recognition ability of antibodies with a relatively small size of about 2 kD. Here, to pursue this approach, we rationally designed a panel of six bicyclic peptides targeting various epitopes along the sequence of Aβ42 to scan its most amyloidogenic region (residues 13–42). Our kinetic analysis and structural studies revealed that at sub-stoichiometric concentrations the designed bicyclic peptides induce a delay in the condensation of Aβ42 and the subsequent transition to a fibrillar state, while at higher concentrations they inhibit such transition. We thus suggest that designed bicyclic peptides can be employed to inhibit amyloid formation by redirecting the aggregation process toward amorphous assemblies.
in Frontiers in Neuroscience: Neurodegeneration on February 25, 2021 12:00 AM.
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The impairment of microvessels can lead to neurologic diseases such as stroke and vascular dementia. The imaging of lumen and vessel wall of perforating arteries requires an extremely high resolution due to their small caliber size. Current imaging techniques have the difficulty in observing the wall of perforating arteries. In this study, we developed a 3D inner-volume (IV) TSE (SPACE) sequence with optimized 2D spatially selective excitation (SSE) RF pulses. The optimized SSE RF pulses were designed through a series of optimization including iterative RF pulse design, trajectory optimization, and phase convention of Carr-Purcell-Meiboom-Gill (CPMG) condition to meet the perforating arteries imaging demands. High resolution of isotropic 0.30 mm within 10 min was achieved for the black- blood images of lenticulostriate artery (LSA). The LSA lumen and vessel wall were imaged by the IV-SPACE sequence simultaneously. Images obtained by the optimized RF pulse has fewer aliasing artifacts from outside of ROI than the traditional pulse. The IV-SPACE images showed clearer delineation of vessel wall and lumen of LSA than conventional SPACE images. IV-SPACE might be a promising method for detecting microvasculopathies of cerebral vascular diseases.
in Frontiers in Neuroscience: Brain Imaging Methods on February 25, 2021 12:00 AM.
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in Frontiers in Neuroscience: Neurodegeneration on February 25, 2021 12:00 AM.
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The reason why dopamine neurons die in Parkinson’s disease remains largely unknown. Emerging evidence points to a role for brain inflammation in neurodegeneration. Essential questions are whether brain inflammation happens sufficiently early so that interfering with this process can be expected to slow down neuronal death and whether the contribution from inflammation is large enough so that anti-inflammatory agents can be expected to work. Here I discuss data from human PD studies indicating that brain inflammation is an early event in PD. I also discuss the role of T-lymphocytes and peripheral inflammation for neurodegeneration. I critically discuss the failure of clinical trials targeting inflammation in PD.
in Frontiers in Neuroscience: Neurodegeneration on February 25, 2021 12:00 AM.
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in Frontiers in Human Neuroscience on February 25, 2021 12:00 AM.
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Background: Maximum safe resection of infiltrative brain tumors in eloquent area is the primary objective in surgical neuro-oncology. This goal can be achieved with direct electrical stimulation (DES) to perform a functional mapping of the brain in patients awake intraoperatively. When awake surgery is not possible, we propose a pipeline procedure that combines advanced techniques aiming at performing a dissection that respects the anatomo-functional connectivity of the peritumoral region. This procedure can benefit from intraoperative monitoring with computerized tomography scan (iCT-scan) and brain shift correction. Associated with this intraoperative monitoring, the additional value of preoperative investigation combining brain mapping by navigated transcranial magnetic stimulation (nTMS) with various neuroimaging modalities (tractography and resting state functional MRI) has not yet been reported.
Case Report: A 42-year-old left-handed man had increased intracranial pressure (IICP), left hand muscle deficit, and dysarthria, related to an infiltrative tumor of the right frontal lobe with large mass effect and circumscribed contrast enhancement in motor and premotor cortical areas. Spectroscopy profile and intratumoral calcifications on CT-scan suggested an WHO grade III glioma, later confirmed by histology. The aforementioned surgical procedure was considered, since standard awake surgery was not appropriate for this patient. In preoperative time, nTMS mapping of motor function (deltoid, first interosseous, and tibialis anterior muscles) was performed, combined with magnetic resonance imaging (MRI)-based tractography reconstruction of 6 neural tracts (arcuate, corticospinal, inferior fronto-occipital, uncinate and superior and inferior longitudinal fasciculi) and resting-state functional MRI connectivity (rs-fMRI) of sensorimotor and language networks. In intraoperative time, DES mapping was performed with motor evoked response recording and tumor resection was optimized using non-rigid image transformation of the preoperative data (nTMS, tractography, and rs-fMRI) to iCT data. Image guidance was updated with correction for brain shift and tissue deformation using biomechanical modeling taking into account brain elastic properties. This correction was done at crucial surgical steps, i.e., when tumor bulged through the craniotomy after dura mater opening and when approaching the presumed eloquent brain regions. This procedure allowed a total resection of the tumor region with contrast enhancement as well as a complete regression of IICP and dysarthria. Hand paresis remained stable with no additional deficit. Postoperative nTMS mapping confirmed the good functional outcome.
Conclusion: This case report and technical note highlights the value of preoperative functional evaluation by nTMS updated intraoperatively with correction of brain deformation by iCT. This multimodal approach may become the optimized technique of reference for patients with brain tumors in eloquent areas that are unsuitable for awake brain surgery.
in Frontiers in Human Neuroscience on February 25, 2021 12:00 AM.
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Transcranial direct current stimulation (TDCS) targeting the primary motor hand area (M1-HAND) may induce lasting shifts in corticospinal excitability, but after-effects show substantial inter-individual variability. Functional magnetic resonance imaging (fMRI) can probe after-effects of TDCS on regional neural activity on a whole-brain level.
ObjectiveUsing a double-blinded cross-over design, we investigated whether the individual change in corticospinal excitability after TDCS of M1-HAND is associated with changes in task-related regional activity in cortical motor areas.
MethodsSeventeen healthy volunteers (10 women) received 20 min of real (0.75 mA) or sham TDCS on separate days in randomized order. Real and sham TDCS used the classic bipolar set-up with the anode placed over right M1-HAND. Before and after each TDCS session, we recorded motor evoked potentials (MEP) from the relaxed left first dorsal interosseus muscle after single-pulse transcranial magnetic stimulation(TMS) of left M1-HAND and performed whole-brain fMRI at 3 Tesla while participants completed a visuomotor tracking task with their left hand. We also assessed the difference in MEP latency when applying anterior-posterior and latero-medial TMS pulses to the precentral hand knob (AP-LM MEP latency).
ResultsReal TDCS had no consistent aftereffects on mean MEP amplitude, task-related activity or motor performance. Individual changes in MEP amplitude, measured directly after real TDCS showed a positive linear relationship with individual changes in task-related activity in the supplementary motor area and AP-LM MEP latency.
ConclusionFunctional aftereffects of classical bipolar anodal TDCS of M1-HAND on the motor system vary substantially across individuals. Physiological features upstream from the primary motor cortex may determine how anodal TDCS changes corticospinal excitability.
in Frontiers in Human Neuroscience on February 25, 2021 12:00 AM.
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Prediction is essential for the efficiency of many cognitive processes; however, this process is not always perfect. Predictive coding theory suggests that the brain generates and updates a prediction to respond to an upcoming event. Although an electrophysiological index of prediction, the stimulus preceding negativity (SPN), has been reported, it remains unknown whether the SPN reflects the prediction accuracy, or whether it is associated with the prediction error, which corresponds to a mismatch between a prediction and an actual input. Thus, the present study aimed to investigate this question using electroencephalography (EEG). Participants were asked to predict the original pictures from pictures that had undergone different levels of pixelation. The SPN amplitude was affected by the level of pixelation and correlated with the subjective evaluation of the prediction accuracy. Furthermore, late positive components (LPC) were negatively correlated with SPN. These results suggest that the amplitude of SPN reflects the prediction accuracy; more accurate prediction increases the SPN and reduces the prediction error, resulting in reduced LPC amplitudes.
in Frontiers in Human Neuroscience on February 25, 2021 12:00 AM.
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Introduction: Falls are the leading cause of fatal and nonfatal injuries among older adults. Studies showed that older adults can reduce the risk of falls after participation in an unexpected perturbation-based balance training (PBBT), a relatively novel approach that challenged reactive balance control. This study aims to investigate the effect of the practice schedule (i.e., contextual interference) on reactive balance function and its transfer to proactive balance function (i.e., voluntary step execution test and Berg balance test). Our primary hypothesis is that improvements in reactive balance control following block PBBT will be not inferior to the improvements following random PBBT.
Methods and Analysis: This is a double-blind randomized controlled trial. Fifty community-dwelling older adults (over 70 years) will be recruited and randomly allocated to a random PBBT group (n = 25) or a block PBBT group (n = 25). The random PBBT group will receive eight training sessions over 4 weeks that include unexpected machine-induced perturbations of balance during hands-free treadmill walking. The block PBBT group will be trained by the same perturbation treadmill system, but only one direction will be trained in each training session, and the direction of the external perturbations will be announced. Both PBBT groups (random PBBT and block PBBT) will receive a similar perturbation intensity during training (which will be customized to participant’s abilities), the same training period, and the same concurrent cognitive tasks during training. The generalization and transfer of learning effects will be measured by assessing the reactive and proactive balance control during standing and walking before and after 1 month of PBBT, for example, step and multiple steps and fall thresholds, Berg balance test, and fear of falls. The dependent variable will be rank transformed prior to conducting the analysis of covariance (ANCOVA) to allow for nonparametric analysis.
Discussion: This research will explore which of the balance retraining paradigms is more effective to improve reactive balance and proactive balance control in older adults (random PBBT vs. block PBBT) over 1 month. The research will address key issues concerning balance retraining: older adults’ neuromotor capacities to optimize training responses and their applicability to real-life challenges.
Clinical Trial Registration: Helsinki research ethics approval has been received (Soroka Medical Center approval #0396-16-SOR; MOH_2018-07-22_003536; www.ClinicalTrials.gov, NCT04455607).
in Frontiers in Human Neuroscience on February 25, 2021 12:00 AM.
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The present study is the first to measure event-related potentials associated with the processing of the emotional Stroop task (EST) with the use of an orthogonal factorial manipulation for emotional valence, arousal, and subjective significance (the importance of the current experience for goals and plans for the future). The current study aimed to investigate concurrently the role of the three dimensions describing the emotion-laden words for interference control measured in the classical version of the EST paradigm. The results showed that reaction times were affected by the emotional valence of presented words and the interactive effect of valence and arousal. The expected emotional arousal effect was only found in behavioral results for neutrally valenced words. Electrophysiological results showed valence and subjective significance correlated with the amplitude differences in the P2 component. Moreover, the amplitude of the N450 component varied with the level of subjective significance. This study also demonstrated that exploratory event-related potential analysis provides additional information beyond the classical component-based analysis. The obtained results show that cognitive control effects in the EST may be altered by manipulation in the subjective significance dimension.
in Frontiers in Human Neuroscience on February 25, 2021 12:00 AM.
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Patients with Wilson’s disease (WD) suffer from prospective memory (PM) impairment, and some of patients develop cognitive impairment. However, very little is known about how brain structure and function changes effect PM in WD. Here, we employed multimodal neuroimaging data acquired from 22 WD patients and 26 healthy controls (HC) who underwent three-dimensional T1-weighted, diffusion tensor imaging (DTI), and resting state functional magnetic resonance imaging (RS-fMRI). We investigated gray matter (GM) volumes with voxel-based morphometry, DTI metrics using the fiber tractography method, and RS-fMRI using the seed-based functional connectivity method. Compared with HC, WD patients showed GM volume reductions in the basal ganglia (BG) and occipital fusiform gyrus, as well as volume increase in the visual association cortex. Moreover, whiter matter (WM) tracks of WD were widely impaired in association and limbic fibers. WM tracks in association fibers are significant related to PM in WD patients. Relative to HC, WD patients showed that the visual association cortex functionally connects to the thalamus and hippocampus, which is associated with global cognitive function in patients with WD. Together, these findings suggested that PM impairment in WD may be modulated by aberrant WM in association fibers, and that GM volume changes in the association cortex has no direct effect on cognitive status, but indirectly affect global cognitive function by its aberrant functional connectivity (FC) in patients with WD. Our findings may provide a new window to further study how WD develops into cognitive impairment, and deepen our understanding of the cognitive status and neuropathology of WD.
in Frontiers in Human Neuroscience on February 25, 2021 12:00 AM.
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An increasing number of studies demonstrated the involvement of the cerebellum in (social) sequence processing. The current preliminary study is the first to investigate the causal involvement of the cerebellum in sequence generation, using low-frequency repetitive transcranial magnetic stimulation (LF-rTMS). By targeting the posterior cerebellum, we hypothesized that the induced neuro-excitability modulation would lead to altered performance on a Picture and Story sequencing task, which involve the generation of the correct chronological order of various social and non-social stories depicted in cartoons or sentences. Our results indicate that participants receiving LF-rTMS over the cerebellum, as compared to sham participants, showed a stronger learning effect from pre to post stimulation for both tasks and for all types of sequences (i.e. mechanical, social scripts, false belief, true belief). No differences between sequence types were observed. Our results suggest a positive effect of LF-rTMS on sequence generation. We conclude that the cerebellum is causally involved in the generation of sequences of social and nonsocial events. Our discussion focuses on recommendations for future studies.
in Frontiers in Human Neuroscience on February 25, 2021 12:00 AM.
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The prelimbic (PL) region of the medial prefrontal cortex (mPFC) has been implicated in both driving and suppressing motivated behaviors, including cocaine-seeking in rats. These seemingly opposing functions may be mediated by different efferent targets of PL projections, such as the nucleus accumbens (NAc) core and rostromedial tegmental nucleus (RMTg), which have contrasting roles in reward-seeking behaviors. We sought to characterize the anatomical connectivity differences between PL neurons projecting to NAc core and RMTg. We used conventional retrograde tracers to reveal distinct subpopulations of PL neurons projecting to NAc core vs. RMTg in rats, with very little overlap. To examine potential differences in input specificity for these two PL subpopulations, we then used Cre-dependent rabies virus (EnvA-RV-EGFP) as a monosynaptic retrograde tracer and targeted specific PL neurons via injections of retrograde CAV2-Cre in either NAc core or RMTg. We observed a similar catalog of cortical, thalamic, and limbic afferents for both NAc- and RMTg-projecting populations, with the primary source of afferent information arising from neighboring prefrontal neurons in ipsilateral PL and infralimbic cortex (IL). However, when the two subpopulations were directly compared, we found that RMTg-projecting PL neurons received a greater proportion of input from ipsilateral PL and IL, whereas NAc-projecting PL neurons received a greater proportion of input from most other cortical areas, mediodorsal thalamic nucleus, and several other subcortical areas. NAc-projecting PL neurons also received a greater proportion of contralateral cortical input. Our findings reveal that PL subpopulations differ not only in their efferent target but also in the input specificity from afferent structures. These differences in connectivity are likely to be critical to functional differences of PL subpopulations.
in Frontiers in Neural Circuits on February 25, 2021 12:00 AM.
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There are more than 1000 odorant receptor (OR) genes in the mouse genome. Each olfactory sensory neuron expresses only one of these genes, in a monoallelic fashion. The transcript abundance of homologous OR genes vary between distinct mouse strains. Here we analyzed the expression of the OR gene Olfr17 (also named P2) in different genomic contexts. Olfr17 is expressed at higher levels in the olfactory epithelium from 129 mice than from C57BL/6 (B6) mice. However, we found that in P2-IRES-tauGFP knock-in mice, the transcript levels of the 129 Olfr17 allele are highly reduced when compared to the B6 Olfr17 allele. To address the mechanisms involved in this variation we compared the 5′ region sequence and DNA methylation patterns of the B6 and 129 Olfr17 alleles. Our results show that genetic variations in cis regulatory regions can lead to differential DNA methylation frequencies in these OR gene alleles. They also show that expression of the Olfr17 alleles is largely affected by the genetic background, and suggest that in knock-in mice, expression can be affected by epigenetic modifications in the region of the targeted locus.
in Frontiers in Cellular Neuroscience on February 25, 2021 12:00 AM.
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Noradrenaline is a major neuromodulator in the central nervous system (CNS). It is released from varicosities on neuronal efferents, which originate principally from the main noradrenergic nuclei of the brain – the locus coeruleus – and spread throughout the parenchyma. Noradrenaline is released in response to various stimuli and has complex physiological effects, in large part due to the wide diversity of noradrenergic receptors expressed in the brain, which trigger diverse signaling pathways. In general, however, its main effect on CNS function appears to be to increase arousal state. Although the effects of noradrenaline have been researched extensively, the majority of studies have assumed that noradrenaline exerts its effects by acting directly on neurons. However, neurons are not the only cells in the CNS expressing noradrenaline receptors. Astrocytes are responsive to a range of neuromodulators – including noradrenaline. In fact, noradrenaline evokes robust calcium transients in astrocytes across brain regions, through activation of α1-adrenoreceptors. Crucially, astrocytes ensheath neurons at synapses and are known to modulate synaptic activity. Hence, astrocytes are in a key position to relay, or amplify, the effects of noradrenaline on neurons, most notably by modulating inhibitory transmission. Based on a critical appraisal of the current literature, we use this review to argue that a better understanding of astrocyte-mediated noradrenaline signaling is therefore essential, if we are ever to fully understand CNS function. We discuss the emerging concept of astrocyte heterogeneity and speculate on how this might impact the noradrenergic modulation of neuronal circuits. Finally, we outline possible experimental strategies to clearly delineate the role(s) of astrocytes in noradrenergic signaling, and neuromodulation in general, highlighting the urgent need for more specific and flexible experimental tools.
in Frontiers in Cellular Neuroscience on February 25, 2021 12:00 AM.
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As a physiological response to injury in the internal body organs, inflammation is responsible for removing dangerous stimuli and initiating healing. However, persistent and exaggerative chronic inflammation causes undesirable negative effects in the organs. Inflammation occurring in the brain and spinal cord is known as neuroinflammation, with microglia acting as the central cellular player. There is increasing evidence suggesting that chronic neuroinflammation is the most relevant pathological feature of Alzheimer’s disease (AD), regulating other pathological features, such as the accumulation of amyloid-β (Aβ) and hyperphosphorylation of Tau. Systemic inflammatory signals caused by systemic disorders are known to strongly influence neuroinflammation as a consequence of microglial activation, inflammatory mediator production, and the recruitment of peripheral immune cells to the brain, resulting in neuronal dysfunction. However, the neuroinflammation-accelerated neuronal dysfunction in AD also influences the functions of peripheral organs. In the present review, we highlight the link between systemic inflammatory disorders and AD, with inflammation serving as the common explosion. We discuss the molecular mechanisms that govern the crosstalk between systemic inflammation and neuroinflammation. In our view, inflammation spreading indicates a negative spiral between systemic diseases and AD. Therefore, “dampening inflammation” through the inhibition of cathepsin (Cat)B or CatS may be a novel therapeutic approach for delaying the onset of and enacting early intervention for AD.
in Frontiers in Cellular Neuroscience on February 25, 2021 12:00 AM.
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Strokes are the most common types of cerebrovascular disease and remain a major cause of death and disability worldwide. Cerebral ischemic stroke is caused by a reduction in blood flow to the brain. In this disease, two major zones of injury are identified: the lesion core, in which cells rapidly progress toward death, and the ischemic penumbra (surrounding the lesion core), which is defined as hypoperfusion tissue where cells may remain viable and can be repaired. Two methods that are approved by the Food and Drug Administration (FDA) include intravenous thrombolytic therapy and endovascular thrombectomy, however, the narrow therapeutic window poses a limitation, and therefore a low percentage of stroke patients actually receive these treatments. Developments in stem cell therapy have introduced renewed hope to patients with ischemic stroke due to its potential effect for reversing the neurological sequelae. Over the last few decades, animal tests and clinical trials have been used to treat ischemic stroke experimentally with various types of stem cells. However, several technical and ethical challenges must be overcome before stem cells can become a choice for the treatment of stroke. In this review, we summarize the mechanisms, processes, and challenges of using stem cells in stroke treatment. We also discuss new developing trends in this field.
in Frontiers in Cellular Neuroscience on February 25, 2021 12:00 AM.
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Dorsal and median raphe nuclei (DR and MR, respectively) are members of the reticular activating system and play important role in the regulation of the sleep-wakefulness cycle, movement, and affective states. M-current is a voltage-gated potassium current under the control of neuromodulatory mechanisms setting neuronal excitability. Our goal was to determine the proportion of DR and MR serotonergic neurons possessing M-current and whether they are organized topographically. Electrophysiological parameters of raphe serotonergic neurons influenced by this current were also investigated. We performed slice electrophysiology on genetically identified serotonergic neurons. Neurons with M-current are located rostrally in the DR and dorsally in the MR. M-current determines firing rate, afterhyperpolarization amplitude, and adaptation index (AI) of these neurons, but does not affect input resistance, action potential width, and high threshold oscillations.These findings indicate that M-current has a strong impact on firing properties of certain serotonergic neuronal subpopulations and it might serve as an effective contributor to cholinergic and local serotonergic neuromodulatory actions.
in Frontiers in Cellular Neuroscience on February 25, 2021 12:00 AM.
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Background and Aims: Numerous studies have demonstrated thalamus-related structural, functional, and metabolic abnormalities in minimal hepatic encephalopathy (MHE). We conducted the first study to investigate thalamic structural connectivity alterations in MHE.
MethodsDiffusion tensor imaging (DTI)-based probabilistic tractography was employed to determine the structural linkage between the thalamus and cortical/subcortical regions in 52 cirrhotic patients [22 with MHE; 30 without MHE (NHE)] and 30 controls. We measured these thalamic connections, which included connectivity strength (CS), fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), and then compared these among the three groups. Neurocognitive assessment was also performed. Correlation analysis was conducted to investigate the relationship between neurocognitive performance and the above measurements. Classification analysis was performed to determine whether thalamic connection measurements can distinguish MHE from NHE.
ResultsThe probabilistic tractography revealed thalamic structural connections, which were disrupted in cirrhotic patients (as reflected by a decrease in CS/FA and an increase in MD/AD/RD). Abnormal thalamic connections primarily involved the prefrontal cortex, sensorimotor cortex, parietal cortex, medial temporal cortex and hippocampus, and striatum. Thalamic connectivity abnormalities deteriorated from NHE to MHE, and they were correlated with patients’ neurocognitive performance. The moderate classification accuracy was obtained using CS and MD as discriminating indexes.
ConclusionOur results demonstrated the altered thalamic structural connectivity involving both cortical and subcortical regions in MHE, which could be regarded as representative of MHE-related widespread impairments in white matter pathways. The disturbed thalamic connectivity may underlie the mechanism of cognitive deficits in MHE and may potentially be utilized as a biomarker for diagnosing MHE and in monitoring disease progression. In addition to thalamic–cortical/subcortical connections, further studies are recommended to explore the structural alterations in other white matter pathways in MHE.
in Frontiers in Neuroanatomy on February 25, 2021 12:00 AM.
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Aging of the brain can manifest itself as a memory and cognitive decline, which has been shown to frequently coincide with changes in the structural plasticity of dendritic spines. Decreased number and maturity of spines in aged animals and humans, together with changes in synaptic transmission, may reflect aberrant neuronal plasticity directly associated with impaired brain functions. In extreme, a neurodegenerative disease, which completely devastates the basic functions of the brain, may develop. While cellular senescence in peripheral tissues has recently been linked to aging and a number of aging-related disorders, its involvement in brain aging is just beginning to be explored. However, accumulated evidence suggests that cell senescence may play a role in the aging of the brain, as it has been documented in other organs. Senescent cells stop dividing and shift their activity to strengthen the secretory function, which leads to the acquisition of the so called senescence-associated secretory phenotype (SASP). Senescent cells have also other characteristics, such as altered morphology and proteostasis, decreased propensity to undergo apoptosis, autophagy impairment, accumulation of lipid droplets, increased activity of senescence-associated-β-galactosidase (SA-β-gal), and epigenetic alterations, including DNA methylation, chromatin remodeling, and histone post-translational modifications that, in consequence, result in altered gene expression. Proliferation-competent glial cells can undergo senescence both in vitro and in vivo, and they likely participate in neuroinflammation, which is characteristic for the aging brain. However, apart from proliferation-competent glial cells, the brain consists of post-mitotic neurons. Interestingly, it has emerged recently, that non-proliferating neuronal cells present in the brain or cultivated in vitro can also have some hallmarks, including SASP, typical for senescent cells that ceased to divide. It has been documented that so called senolytics, which by definition, eliminate senescent cells, can improve cognitive ability in mice models. In this review, we ask questions about the role of senescent brain cells in brain plasticity and cognitive functions impairments and how senolytics can improve them. We will discuss whether neuronal plasticity, defined as morphological and functional changes at the level of neurons and dendritic spines, can be the hallmark of neuronal senescence susceptible to the effects of senolytics.
in Frontiers in Ageing Neuroscience on February 25, 2021 12:00 AM.
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Neurofibrillary tangles (NFTs) are a major pathologic hallmark of Alzheimer’s disease (AD). Several studies have shown that amyloid β oligomers (Aβo) and tau oligomers mediate their toxicity, in part, via binding to cellular prion protein (PrPC) and that some anti-PrP antibodies can block this interaction. We have generated a novel monoclonal anti-PrP antibody (TW1) and assessed the efficacy of passive immunization with it in a mouse model of AD with extensive tau pathology: hTau/PS1 transgenic (Tg) mice. These mice were injected intraperitoneally once a week with TW1 starting at 5 months of age. Behavior was assessed at 8 months of age and brain tissue was subsequently harvested for analysis of treatment efficacy at 9 months. Mice treated with TW1 did not show any significant difference in sensorimotor testing including traverse beam, rotarod, and locomotor activity compared to controls. Significant cognitive benefits were observed with the novel object recognition test (ORT) in the immunized mice (two-tailed, t-test p = 0.0019). Immunized mice also showed cognitive benefits on the closed field symmetrical maze (day 1 two-tailed t-test p = 0.0001; day 2 two-tailed t-test p = 0.0015; day 3 two-tailed t-test p = 0.0002). Reduction of tau pathology was observed with PHF-1 immunohistochemistry in the piriform cortex by 60% (two-tailed t-test p = 0.01) and in the dentate gyrus by 50% (two-tailed t-test p = 0.02) in animals treated with TW1 compared to controls. There were no significant differences in astrogliosis or microgliosis observed between treated and control mice. As assessed by Western blots using PHF-1, the TW1 therapy reduced phosphorylated tau pathology (two-tailed t-test p = 0.03) and improved the ratio of pathological soluble tau to tubulin (PHF1/tubulin; two-tailed t-test p = 0.0006). Reduction of tau pathology also was observed using the CP13 antibody (two-tailed t-test p = 0.0007). These results indicate that passive immunization with the TW1 antibody can significantly decrease tau pathology as assessed by immunohistochemical and biochemical methods, resulting in improved cognitive function in a tau transgenic mouse model of AD.
in Frontiers in Ageing Neuroscience on February 25, 2021 12:00 AM.
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Tumor necrosis factor receptor 2 (TNFR2) promotes neuronal survival downstream. This longitudinal study evaluated whether the TNFRSF1B gene encoding TNFR2 and levels of its soluble form (sTNFR2) affect Alzheimer disease (AD) biomarkers and clinical outcomes. Data analyzed included 188 patients in the Alzheimer's Disease Neuroimaging Initiative (ADNI) who had mild cognitive impairment (MCI) and AD dementia. Further, a replication study was performed in 48 patients with MCI with positive AD biomarkers who were treated at a memory clinic. Cerebrospinal fluid (CSF) sTNFR2 levels along with two related TNFRSF1B gene single nucleotide polymorphisms (SNPs) rs976881 and rs1061622 were assessed. General linear models were used to evaluate the effect of CSF sTNFR2 levels and each SNP in relationship to CSF t-tau and p-tau, cognitive domains, MRI brain measures, and longitudinal cognitive changes after adjustments were made for covariates such as APOE ε4 status. In the ADNI cohort, a significant interaction between rs976881 and CSF sTNFR2 modulates CSF t-tau and p-tau levels; hippocampal and whole brain volumes; and Digit Span Forwards subtest scores. In the replication cohort, a significant interaction between rs976881 and CSF sTNFR2 modulates CSF p-tau. A significant interaction between rs976881 and CSF sTNFR2 also impacts Clinical Dementia Rating Sum of Boxes scores over 12 months in the ADNI cohort. The interaction between TNFRSF1B variant rs976881 and CSF sTNFR2 levels was noted to modulate multiple AD-associated severity markers and cognitive domains. This interaction impacts resilience-related clinical outcomes in AD and lends support to sTNFR2 as a promising candidate for therapeutic targeting to improve clinical outcomes of interest.
in Frontiers in Ageing Neuroscience on February 25, 2021 12:00 AM.
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Purpose: The retina and the brain share similar neuronal and microvascular features, therein we aimed to assess the structural and microvascular changes in the macula and choriocapillaris (CC) in patients with cerebral infarction when compared with healthy controls using optical coherence tomography angiography (OCTA).
Methods: OCTA was used to image and measure the capillary density in the radial peripapillary capillaries (RPC), superficial capillary plexus (SCP), deep capillary plexus (DCP), choriocapillaris (CC), and mean area of the foveal avascular zone (FAZ) in all participants. Twenty-two cerebral infarction patients based on their magnetic resonance imaging (MRI) and 25 healthy controls were included in our study.
Results: Density of the RPC (P < 0.001), SCP (P = 0.001), DCP (P < 0.001) and CC (P < 0.001) were significantly reduced in cerebral infarction patients when compared with healthy controls, respectively. Retinal thickness measurements (P < 0.05) were significantly reduced in cerebral infarction patients when compared with healthy controls. The mean FAZ area was significantly larger (P = 0.012) in cerebral infarction patients when compared with healthy controls. National Institute of HealthStroke Scale (NIHSS) inversely correlated with SCP density in cerebral infarction patients (Rho = −0.409, P = 0.001). Receiver operating characteristics curve analysis showed that the blood flow of the choriocapillaris had the highest index [area under the receiver operatingcharacteristic (AUROC) = 0.964] to discriminate cerebral infarction patients from the healthy controls.
Conclusions: Our study suggests that cerebral microcirculation dysfunction which occurs in cerebral infarction is mirrored in the macula and choroidal microcirculation. OCTA has the potential to non-invasively characterize the macula and choroidal changes in cerebral infarction in vivo.
in Frontiers in Ageing Neuroscience on February 25, 2021 12:00 AM.
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Background: This meta-analysis aimed to evaluate the relationship between serum uric acid (UA) and the risk of dementia and its subtypes.
Methods: Embase, PubMed, and Web of Science were searched from inception to July 2020. Random-effect models were employed to analyze the standard mean difference (SMD) with the corresponding 95% confidence intervals (CI).
Results: Twenty-three eligible studies involving 5,575 participants were identified. The overall results showed lower levels of UA in dementia relative to non-dementia controls [SMD = −0.32 (−0.64; −0.01) p = 0.04]. The subgroup analysis of the type of dementia demonstrated a significant association of UA with Alzheimer's disease (AD) [SMD = −0.58 (−1.02; −0.15) p = 0.009] and Parkinson's disease with dementia (PDD) [SMD = −0.33 (−0.52; −0.14) p = 0.001] but not with vascular dementia (VaD). The stratification analysis of the concentrations of UA revealed that the UA quartile 1–2 was negatively correlated with dementia and neurodegenerative subtypes (p < 0.05), whereas a positive correlation of UA quartile 4 with dementia was noted (p = 0.028). Additionally, the meta-regression analysis on confounders showed that not age, body mass index, diabetes mellitus, hypertension, or smoking but education (p = 0.003) exerted an influence of the UA in the risk estimate of dementia.
Conclusions: Low concentrations of UA (< 292 μmol/L or 4.91 mg/dL) is a potential risk factor for AD and PDD but not for VaD. The mechanism of different concentrations of the UA in dementia needs to be confirmed through further investigation.
in Frontiers in Ageing Neuroscience on February 25, 2021 12:00 AM.
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Older adults with mild or no hearing loss make more errors and expend more effort listening to speech. Cochlear implants (CI) restore hearing to deaf patients but with limited fidelity. We hypothesized that patient-reported hearing and health-related quality of life in CI patients may similarly vary according to age. Speech Spatial Qualities (SSQ) of hearing scale and Health Utilities Index Mark III (HUI) questionnaires were administered to 543 unilaterally implanted adults across Europe, South Africa, and South America. Data were acquired before surgery and at 1, 2, and 3 years post-surgery. Data were analyzed using linear mixed models with visit, age group (18–34, 35–44, 45–54, 55–64, and 65+), and side of implant as main factors and adjusted for other covariates. Tinnitus and dizziness prevalence did not vary with age, but older groups had more preoperative hearing. Preoperatively and postoperatively, SSQ scores were significantly higher (Δ0.75–0.82) for those aged <45 compared with those 55+. However, gains in SSQ scores were equivalent across age groups, although postoperative SSQ scores were higher in right-ear implanted subjects. All age groups benefited equally in terms of HUI gain (0.18), with no decrease in scores with age. Overall, younger adults appeared to cope better with a degraded hearing before and after CI, leading to better subjective hearing performance.
in Frontiers in Ageing Neuroscience on February 25, 2021 12:00 AM.
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in eLife on February 25, 2021 12:00 AM.
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in eLife on February 25, 2021 12:00 AM.
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in bioRxiv: Neuroscience on February 25, 2021 12:00 AM.
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in bioRxiv: Neuroscience on February 25, 2021 12:00 AM.
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in bioRxiv: Neuroscience on February 25, 2021 12:00 AM.
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in bioRxiv: Neuroscience on February 25, 2021 12:00 AM.
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in PNAS on February 24, 2021 07:07 PM.
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in PNAS on February 24, 2021 07:07 PM.
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in PNAS on February 24, 2021 07:07 PM.
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in PNAS on February 24, 2021 07:07 PM.
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in PNAS on February 24, 2021 07:07 PM.
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in PNAS on February 24, 2021 07:07 PM.
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in PNAS on February 24, 2021 07:07 PM.
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in PNAS on February 24, 2021 07:07 PM.
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in PNAS on February 24, 2021 07:07 PM.
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in PNAS on February 24, 2021 07:07 PM.
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in PNAS on February 24, 2021 07:07 PM.
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in PNAS on February 24, 2021 07:07 PM.
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Publication date: Available online 24 February 2021
Source: Neural Networks
Author(s): Cheng Xie, Hongxin Xiang, Ting Zeng, Yun Yang, Beibei Yu, Qing Liu
in Neural Networks on February 24, 2021 02:00 PM.
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Publication date: Available online 24 February 2021
Source: Neural Networks
Author(s): Jung-Jun Kim, Dong-Gyu Lee, Jialin Wu, Hong-Gyu Jung, Seong-Whan Lee
in Neural Networks on February 24, 2021 02:00 PM.
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Publication date: Available online 24 February 2021
Source: Neural Networks
Author(s): Junyi Wang, Zhanshan Wang, Xiangyong Chen, Jianlong Qiu
in Neural Networks on February 24, 2021 02:00 PM.
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by Caglar Cakan, Klaus Obermayer
in PLoS Computational Biology on February 24, 2021 02:00 PM.
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by Pascal F. Hagolani, Roland Zimm, Renske Vroomans, Isaac Salazar-Ciudad
How does morphological complexity evolve? This study suggests that the likelihood of mutations increasing phenotypic complexity becomes smaller when the phenotype itself is complex. In addition, the complexity of the genotype-phenotype map (GPM) also increases with the phenotypic complexity. We show that complex GPMs and the above mutational asymmetry are inevitable consequences of how genes need to be wired in order to build complex and robust phenotypes during development. We randomly wired genes and cell behaviors into networks in EmbryoMaker. EmbryoMaker is a mathematical model of development that can simulate any gene network, all animal cell behaviors (division, adhesion, apoptosis, etc.), cell signaling, cell and tissues biophysics, and the regulation of those behaviors by gene products. Through EmbryoMaker we simulated how each random network regulates development and the resulting morphology (i.e. a specific distribution of cells and gene expression in 3D). This way we obtained a zoo of possible 3D morphologies. Real gene networks are not random, but a random search allows a relatively unbiased exploration of what is needed to develop complex robust morphologies. Compared to the networks leading to simple morphologies, the networks leading to complex morphologies have the following in common: 1) They are rarer; 2) They need to be finely tuned; 3) Mutations in them tend to decrease morphological complexity; 4) They are less robust to noise; and 5) They have more complex GPMs. These results imply that, when complexity evolves, it does so at a progressively decreasing rate over generations. This is because as morphological complexity increases, the likelihood of mutations increasing complexity decreases, morphologies become less robust to noise, and the GPM becomes more complex. We find some properties in common, but also some important differences, with non-developmental GPM models (e.g. RNA, protein and gene networks in single cells).in PLoS Computational Biology on February 24, 2021 02:00 PM.
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by Mengmeng Niu, Yajun He, Jing Xu, Liangping Ding, Tao He, Yong Yi, Mengyuan Fu, Rongtian Guo, Fengtian Li, Hu Chen, Ye-Guang Chen, Zhi-Xiong Jim Xiao
Transforming growth factor-β (TGF-β) signaling plays a critical role in promoting epithelial-to-mesenchymal transition (EMT), cell migration, invasion, and tumor metastasis. ΔNp63α, the major isoform of p63 protein expressed in epithelial cells, is a key transcriptional regulator of cell adhesion program and functions as a critical metastasis suppressor. It has been documented that the expression of ΔNp63α is tightly controlled by oncogenic signaling and is frequently reduced in advanced cancers. However, whether TGF-β signaling regulates ΔNp63α expression in promoting metastasis is largely unclear. In this study, we demonstrate that activation of TGF-β signaling leads to stabilization of E3 ubiquitin ligase FBXO3, which, in turn, targets ΔNp63α for proteasomal degradation in a Smad-independent but Erk-dependent manner. Knockdown of FBXO3 or restoration of ΔNp63α expression effectively rescues TGF-β-induced EMT, cell motility, and tumor metastasis in vitro and in vivo. Furthermore, clinical analyses reveal a significant correlation among TGF-β receptor I (TβRI), FBXO3, and p63 protein expression and that high expression of TβRI/FBXO3 and low expression of p63 are associated with poor recurrence-free survival (RFS). Together, these results demonstrate that FBXO3 facilitates ΔNp63α degradation to empower TGF-β signaling in promoting tumor metastasis and that the TβRI-FBXO3-ΔNp63α axis is critically important in breast cancer development and clinical prognosis. This study suggests that FBXO3 may be a potential therapeutic target for advanced breast cancer treatment.in PLoS Biology on February 24, 2021 02:00 PM.
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by Tracey L. Weissgerber
Meta-research, or the science of science, is a powerful technique that scientists can use to improve science, however most scientists are unaware that meta-research exists and courses are rare. This initiative demonstrates the feasibility of a participant-guided “learn by doing” approach, in which a multidisciplinary, global team of early career researchers learned meta-research skills by working together to design, conduct and publish a meta-research study. This Community Page article describes a participant-guided "learn by doing" initiative, in which a multidisciplinary, global team of early career researchers learned meta-research skills by working together to design, conduct and publish a meta-research (science of science) study. Participants can now apply these skills to solve problems in their own fields.in PLoS Biology on February 24, 2021 02:00 PM.
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in Annals of Neurology on February 24, 2021 01:19 PM.
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in Annals of Neurology on February 24, 2021 10:14 AM.
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in Annals of Neurology on February 24, 2021 10:02 AM.
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Author(s): Boris P. Belotserkovskii
Many biological processes involve macromolecules searching for their specific targets that are surrounded by other objects, and binding to these objects affects the target search. Acceleration of the target search by nonspecific binders was observed experimentally and analyzed theoretically, for exa...
[Phys. Rev. E 103, 022413] Published Wed Feb 24, 2021
in Physical Review E: Biological physics on February 24, 2021 10:00 AM.
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in Journal of Comparative Neurology on February 24, 2021 04:54 AM.
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Over the last ten years, developments in whole-brain microscopy now allow for high-resolution imaging of intact brains of small rodents such as mice. These complex images contain a wealth of information, but many neuroscience laboratories do not have all of the computational knowledge and tools needed to process these data. We review recent open source tools for registration of images to atlases, and the segmentation, visualisation and analysis of brain regions and labelled structures such as neurons. Since the field lacks fully integrated analysis pipelines for all types of whole-brain microscopy analysis, we propose a pathway for tool developers to work together to meet this challenge.
in arXiv: Quantitative Biology: Neurons and Cognition on February 24, 2021 01:30 AM.
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In recent years, to improve the evolutionary algorithms used to solve optimization problems involving a large number of decision variables, many attempts have been made to simplify the problem solution space of a given problem for the evolutionary search. In the literature, the existing approaches can generally be categorized as decomposition-based methods and dimension-reduction-based methods. The former decomposes a large-scale problem into several smaller subproblems, while the latter transforms the original high-dimensional solution space into a low-dimensional space. However, it is worth noting that a given large-scale optimization problem may not always be decomposable, and it is also difficult to guarantee that the global optimum of the original problem is preserved in the reduced low-dimensional problem space. This paper thus proposes a new search paradigm, namely the multi-space evolutionary search, to enhance the existing evolutionary search methods for solving large-scale optimization problems. In contrast to existing approaches that perform an evolutionary search in a single search space, the proposed paradigm is designed to conduct a search in multiple solution spaces that are derived from the given problem, each possessing a unique landscape. The proposed paradigm makes no assumptions about the large-scale optimization problem of interest, such as that the problem is decomposable or that a certain relationship exists among the decision variables. To verify the efficacy of the proposed paradigm, comprehensive empirical studies in comparison to four state-of-the-art algorithms were conducted using the CEC2013 large-scale benchmark problems.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 24, 2021 01:30 AM.
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Sexual selection is a fundamental aspect of evolution for all eukaryotic organisms with mating types. This paper suggests intersexual selection is best viewed as a mechanism to compensate for the unavoidable dynamics of coevolution between sexes that emerge with isogamy. Using the NK model of fitness landscapes, the conditions under which allosomes emerge are first explored. This extends previous work on the evolution of sex where the fitness landscape smoothing of a rudimentary form of the Baldwin effect is suggested as the underlying cause. The NKCS model of coevolution is then used to show how varying fitness landscape size, ruggedness, and connectedness can vary the conditions under which a very simple sexual selection mechanism proves beneficial. This is found to be the case whether one or both sexes exploit sexual selection.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 24, 2021 01:30 AM.
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Aided by recent advances in Deep Learning, Image Caption Generation has seen tremendous progress over the last few years. Most methods use transfer learning to extract visual information, in the form of image features, with the help of pre-trained Convolutional Neural Network models followed by transformation of the visual information using a Caption Generator module to generate the output sentences. Different methods have used different Convolutional Neural Network Architectures and, to the best of our knowledge, there is no systematic study which compares the relative efficacy of different Convolutional Neural Network architectures for extracting the visual information. In this work, we have evaluated 17 different Convolutional Neural Networks on two popular Image Caption Generation frameworks: the first based on Neural Image Caption (NIC) generation model and the second based on Soft-Attention framework. We observe that model complexity of Convolutional Neural Network, as measured by number of parameters, and the accuracy of the model on Object Recognition task does not necessarily co-relate with its efficacy on feature extraction for Image Caption Generation task.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 24, 2021 01:30 AM.
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Consumer grade cyber-physical systems are becoming an integral part of our life, automatizing and simplifying everyday tasks; they are almost always capable of connection to the network allowing remote monitoring and programming. They rely on powerful programming languages, cloud infrastructures, and ultimately on complex software stacks. Indeed, due to complex interactions between hardware, networking and software, developing and testing such systems is known to be a challenging task. Ensuring properties such as dependability, security or data confidentiality is far from obvious. Various quality assurance and testing strategies have been proposed.
The most common approach for pre-deployment testing is to model the system and run simulations with models or software in the loop. In practice, most often, tests are run for a small number of simulations, which are selected based on the engineers' domain knowledge and experience.
We have implemented our approach in Python, using standard frameworks and used it to generate scenarios violating temperature constraints for a smart thermostat implemented as a part of our IoT testbed. Data collected from an application managing a smart building have been used to learn models of the environment under ever changing conditions. The suggested approach allowed us to identify several pit-fails, scenarios (i.e. environment conditions), where the system behaves not as expected.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 24, 2021 01:30 AM.
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Generating diverse populations of high quality solutions has gained interest as a promising extension to the traditional optimization tasks. We contribute to this line of research by studying evolutionary diversity optimization for two of the most prominent permutation problems, namely the Traveling Salesperson Problem (TSP) and Quadratic Assignment Problem (QAP). We explore the worst-case performance of a simple mutation-only evolutionary algorithm with different mutation operators, using an established diversity measure. Theoretical results show most mutation operators for both problems ensure production of maximally diverse populations of sufficiently small size within cubic expected run-time. We perform experiments on QAPLIB instances in unconstrained and constrained settings, and reveal much more optimistic practical performances. Our results should serve as a baseline for future studies.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 24, 2021 01:30 AM.
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With the goal to provide absolute lower bounds for the best possible running times that can be achieved by $(1+\lambda)$-type search heuristics on common benchmark problems, we recently suggested a dynamic programming approach that computes optimal expected running times and the regret values inferred when deviating from the optimal parameter choice.
Our previous work is restricted to problems for which transition probabilities between different states can be expressed by relatively simple mathematical expressions. With the goal to cover broader sets of problems, we suggest in this work an extension of the dynamic programming approach to settings in which the transition probabilities cannot necessarily be computed exactly, but in which they can be approximated numerically, up to arbitrary precision, by Monte Carlo sampling.
We apply our hybrid Monte Carlo dynamic programming approach to a concatenated jump function and demonstrate how the obtained bounds can be used to gain a deeper understanding into parameter control schemes.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 24, 2021 01:30 AM.
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If machine failures can be detected preemptively, then maintenance and repairs can be performed more efficiently, reducing production costs. Many machine learning techniques for performing early failure detection using vibration data have been proposed; however, these methods are often power and data-hungry, susceptible to noise, and require large amounts of data preprocessing. Also, training is usually only performed once before inference, so they do not learn and adapt as the machine ages. Thus, we propose a method of performing online, real-time anomaly detection for predictive maintenance using Hierarchical Temporal Memory (HTM). Inspired by the human neocortex, HTMs learn and adapt continuously and are robust to noise. Using the Numenta Anomaly Benchmark, we empirically demonstrate that our approach outperforms state-of-the-art algorithms at preemptively detecting real-world cases of bearing failures and simulated 3D printer failures. Our approach achieves an average score of 64.71, surpassing state-of-the-art deep-learning (49.38) and statistical (61.06) methods.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 24, 2021 01:30 AM.
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Nonlinear network dynamics are notoriously difficult to understand. Here we study a class of recurrent neural networks called combinatorial threshold-linear networks (CTLNs) whose dynamics are determined by the structure of a directed graph. They are a special case of TLNs, a popular framework for modeling neural activity in computational neuroscience. In prior work, CTLNs were found to be surprisingly tractable mathematically. For small networks, the fixed points of the network dynamics can often be completely determined via a series of {\it graph rules} that can be applied directly to the underlying graph. For larger networks, it remains a challenge to understand how the global structure of the network interacts with local properties. In this work, we propose a method of covering graphs of CTLNs with a set of smaller {\it directional graphs} that reflect the local flow of activity. While directional graphs may or may not have a feedforward architecture, their fixed point structure is indicative of feedforward dynamics. The combinatorial structure of the graph cover is captured by the {\it nerve} of the cover. The nerve is a smaller, simpler graph that is more amenable to graphical analysis. We present three nerve theorems that provide strong constraints on the fixed points of the underlying network from the structure of the nerve. We then illustrate the power of these theorems with some examples. Remarkably, we find that the nerve not only constrains the fixed points of CTLNs, but also gives insight into the transient and asymptotic dynamics. This is because the flow of activity in the network tends to follow the edges of the nerve.
in arXiv: Quantitative Biology: Neurons and Cognition on February 24, 2021 01:30 AM.
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In a first-of-its-kind study, this paper proposes the formulation of constructing prediction intervals (PIs) in a time series as a bi-objective optimization problem and solves it with the help of Nondominated Sorting Genetic Algorithm (NSGA-II). We also proposed modeling the chaos present in the time series as a preprocessor in order to model the deterministic uncertainty present in the time series. Even though the proposed models are general in purpose, they are used here for quantifying the uncertainty in macroeconomic time series forecasting. Ideal PIs should be as narrow as possible while capturing most of the data points. Based on these two objectives, we formulated a bi-objective optimization problem to generate PIs in 2-stages, wherein reconstructing the phase space using Chaos theory (stage-1) is followed by generating optimal point prediction using NSGA-II and these point predictions are in turn used to obtain PIs (stage-2). We also proposed a 3-stage hybrid, wherein the 3rd stage invokes NSGA-II too in order to solve the problem of constructing PIs from the point prediction obtained in 2nd stage. The proposed models when applied to the macroeconomic time series, yielded better results in terms of both prediction interval coverage probability (PICP) and prediction interval average width (PIAW) compared to the state-of-the-art Lower Upper Bound Estimation Method (LUBE) with Gradient Descent (GD). The 3-stage model yielded better PICP compared to the 2-stage model but showed similar performance in PIAW with added computation cost of running NSGA-II second time.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 24, 2021 01:30 AM.
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Humans can quickly associate stimuli to solve problems in novel contexts. Our novel neural network model learns state representations of facts that can be composed to perform such associative inference. To this end, we augment the LSTM model with an associative memory, dubbed Fast Weight Memory (FWM). Through differentiable operations at every step of a given input sequence, the LSTM updates and maintains compositional associations stored in the rapidly changing FWM weights. Our model is trained end-to-end by gradient descent and yields excellent performance on compositional language reasoning problems, meta-reinforcement-learning for POMDPs, and small-scale word-level language modelling.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 24, 2021 01:30 AM.
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Deep reinforcement learning approaches have shown impressive results in a variety of different domains, however, more complex heterogeneous architectures such as world models require the different neural components to be trained separately instead of end-to-end. While a simple genetic algorithm recently showed end-to-end training is possible, it failed to solve a more complex 3D task. This paper presents a method called Deep Innovation Protection (DIP) that addresses the credit assignment problem in training complex heterogenous neural network models end-to-end for such environments. The main idea behind the approach is to employ multiobjective optimization to temporally reduce the selection pressure on specific components in multi-component network, allowing other components to adapt. We investigate the emergent representations of these evolved networks, which learn to predict properties important for the survival of the agent, without the need for a specific forward-prediction loss.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 24, 2021 01:30 AM.
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in Journal of Neuroscience Research on February 24, 2021 01:28 AM.
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Nature Methods, Published online: 24 February 2021; doi:10.1038/s41592-021-01086-7
Beyond the well-known pantheon of model organisms are others. A shift is underway to level the playing field.in Nature Methods on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/s41586-021-03304-w
γ-ray spectroscopy experiments on the origin of spin in the products of nuclear fission of spin-zero nuclei suggest that the fission fragments acquire their spin after scission, rather than before.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/s41586-021-03298-5
A peri-arteriolar niche in the bone marrow for osteogenesis and lymphopoiesis is maintained by mechanical stimulation and is depleted during ageing.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/s41586-021-03288-7
High-fidelity deterministic quantum state transfer and multi-qubit entanglement are demonstrated in a quantum network comprising two superconducting quantum nodes one metre apart, with each node including three interconnected qubits.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/s41586-021-03285-w
An improved device design for perovskite-based photovoltaic cells enables a certified power conversion efficiency of 25.2 per cent, translating to 80.5 per cent of the thermodynamic limit for its bandgap, which approaches those achieved by silicon solar cells.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/s41586-021-03284-x
Two complete volumetric reconstructions of the Caenorhabditis elegans main neuropil (the nerve ring) reveal multi-scale spatial organization that supports both conserved and variable circuitry, and enables the derivation of a modular structure–function model of the neuropil.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/s41586-021-03282-z
Quark–antiquark annihilation measurements provide a precise determination of the ratio of down and up antiquarks within protons as a function of momentum, which confirms the asymmetry between the abundance of down and up antiquarks.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/s41586-021-03272-1
Exposure to a novel experience can ‘reset’ connections between the hippocampus and prefrontal cortex in mice, allowing them to overcome an existing learned behaviour and to replace it with a new one.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/s41586-021-03270-3
Depriving unicellular Dictyostelium discoideum of nutrients generates reactive oxygen species that sequester cysteine within glutathione, which maintains this amoeba in a nonproliferating state that promotes aggregation into a multicellular organism.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/s41586-021-03269-w
Breaks in mitochondrial DNA cause leakage of mitochondrial RNA into the cytoplasm, enhancing immune surveillance and synergizing with nuclear DNA damage to mount a robust type-I interferon immune response.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/s41586-021-03247-2
In a rat model of short bowel syndrome, transplantation of small intestinal organoids into the colon partially restores intestinal function and improves survival—a proof of principle that organoid transplantation might have therapeutic benefit.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/s41586-021-03241-8
Absolute microbial abundances delineate longitudinal dynamics of bacteria, fungi and archaea in the infant gut microbiome, uncovering drivers of microbiome development masked by relative abundances and revealing notable parallels to macroscopic ecosystem assemblies.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/s41586-021-03235-6
Identification of a metabolic checkpoint involving lipid signalling that is specific to regulatory T cells (Treg cells) in the tumour microenvironment raises the possibility of targeting this checkpoint for treatment of cancer.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/s41586-021-03232-9
Spatial and temporal variations among individual human cell proteomes are comprehensively mapped across the cell cycle using proteomic imaging and transcriptomics.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/s41586-021-03212-z
A strategy that combines freeze-casting and salting-out treatments produces strong, tough, stretchable and fatigue-resistant poly(vinyl alcohol) hydrogels.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/s41586-021-03203-0
The mechanism of steady-state electron microbunching is demonstrated, providing a basis that will enable its full implementation in electron storage rings to generate high-repetition, high-power coherent radiation.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/s41586-020-03169-5
The C. elegans neuropil is shown to be organized into four strata composed of related behavioural circuits, and its design principles are linked to the developmental processes that underpin its assembly.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/s41586-020-03157-9
A reinforcement learning algorithm that explicitly remembers promising states and returns to them as a basis for further exploration solves all as-yet-unsolved Atari games and out-performs previous algorithms on Montezuma’s Revenge and Pitfall.in Nature on February 24, 2021 12:00 AM.
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Nature Physics, Published online: 24 February 2021; doi:10.1038/s41567-021-01192-5
Publisher Correction: Charge radii of exotic potassium isotopes challenge nuclear theory and the magic character of N = 32in Nature Physics on February 24, 2021 12:00 AM.
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Nature Photonics, Published online: 24 February 2021; doi:10.1038/s41566-021-00775-1
Reply to ‘Ideal solar cell efficiencies’in Nature Photomics on February 24, 2021 12:00 AM.
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Nature Photonics, Published online: 24 February 2021; doi:10.1038/s41566-021-00772-4
Ideal solar cell efficienciesin Nature Photomics on February 24, 2021 12:00 AM.
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Nature Communications, Published online: 24 February 2021; doi:10.1038/s41467-021-21544-2
Various methods have been proposed to identify synthetic lethality interactions, but selective treatment opportunities for various tumors have not yet been explored. Here, the authors develop the Synthetic Lethality Knowledge Graph webserver (SLKG, http://www.slkg.net) to explore the comprehensive tumor therapy landscape and uncover cancer-specific susceptibilities based on the principle of synthetic lethality.in Nature Communications on February 24, 2021 12:00 AM.
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Nature Communications, Published online: 24 February 2021; doi:10.1038/s41467-021-21532-6
Erasure of DNA methylation from the parental genomes is critical to reset the methylome of differentiated gametes to pluripotent cells in the blastocyst. Here, the authors present a high-throughput single-cell method that enables strand-specific quantification of DNA methylation and identify distinct modes of DNA demethylation dynamics during early mammalian development.in Nature Communications on February 24, 2021 12:00 AM.
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Nature Communications, Published online: 24 February 2021; doi:10.1038/s41467-021-21531-7
Well-developed prototype interface materials for electronics thermal management are limited to a low thermal conductivity or high elastic modulus. Here, the authors report flexible thermal interfaces through self-assembled manufacturing of polymetric composites based on the high thermal conductivity of cubic boron arsenide.in Nature Communications on February 24, 2021 12:00 AM.
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Nature Communications, Published online: 24 February 2021; doi:10.1038/s41467-021-21516-6
The question as to how the soma regulates the germline has been much studied. Here, the authors show in C. elegans that the poly-U specific endoribonuclease ENDU-2 is secreted from the soma and taken-up by the germline, binding mature mRNA, repressing expression of somatic transcripts and maintaining germline immortality.in Nature Communications on February 24, 2021 12:00 AM.
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Nature Communications, Published online: 24 February 2021; doi:10.1038/s41467-021-21504-w
Atmospheric rivers are responsible for much of the poleward water vapour transport in the mid-latitudes and can cause extreme precipitation after landfall. Here, the authors show that ocean fronts and eddies can influence atmospheric rivers and increase the associated precipitation along the North American west coast.in Nature Communications on February 24, 2021 12:00 AM.
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Nature Communications, Published online: 24 February 2021; doi:10.1038/s41467-021-21396-w
Resistance to ALK inhibitors such as lorlatinib often arise due to on-target mutations. Here, the authors show the multi-kinase inhibitor gilteritinib is effective against different mutations that arise during lorlatinib in ALK fusion positive lung cancer to cause resistance.in Nature Communications on February 24, 2021 12:00 AM.
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Nature Communications, Published online: 24 February 2021; doi:10.1038/s41467-021-21247-8
Alternative lengthening of telomeres (ALT) is associated with a poor outcome in neuroblastoma. Here, the authors find that ALT is associated with mutated ATRX and/or reduced protein abundance, frequent telomeric repeat loci and heterochromatic telomeric chromatin.in Nature Communications on February 24, 2021 12:00 AM.
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Nature Communications, Published online: 24 February 2021; doi:10.1038/s41467-021-21231-2
A recent finding of tuning critical current in metallic nanowires by application of small gate voltages seems at odds with general understanding. Here, Ritter et al. study similar nanowires and link the origin of the critical current suppression to tunneling of few high-energy electrons between gate and nanowire, ruling out direct tuning by electric fields.in Nature Communications on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/d41586-021-00509-x
The surprising structure of protons, and a method for growing small intestines for transplantation.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/d41586-021-00503-3
It’s a new beginning.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/d41586-021-00490-5
Open repository will give free access to more than 160 million data points with details about individual infections.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/d41586-021-00479-0
Ozone Nobel prizewinner who coined the term Anthropocene.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/d41586-021-00477-2
To scientists’ surprise, a 10,000-year-old bone found in an Alaskan cave belonged to a domestic dog — one of the earliest known from the Americas.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/d41586-021-00470-9
Game theory suggests that donating doses can help nations of all income levels.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/d41586-021-00469-2
Scientists and artists are working together as never before, finds a Nature poll. Both sides need to invest time, and embrace surprise and challenge.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/d41586-021-00459-4
The latest science news, in brief.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/d41586-021-00431-2
The structure of matter can be explored using the light emitted by particle accelerators. An experiment demonstrates how the properties of two such light sources — synchrotrons and free-electron lasers — can be combined.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/d41586-021-00430-3
Protons are found in all atoms, so it might be surprising to learn that they contain antimatter. It now emerges that there is an imbalance in the types of antimatter in the proton — a finding for which there is no agreed theoretical explanation.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/d41586-021-00429-w
Damage to DNA in a cellular organelle called the mitochondrion triggers an immune response in the nucleus. Mechanistic insights into this process shed light on how organelles communicate.in Nature on February 24, 2021 12:00 AM.
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Nature, Published online: 24 February 2021; doi:10.1038/d41586-021-00421-4
Cancer can evade destruction by the immune system if aided by immunosuppressive regulatory T cells. These cells depend on a lipid-production pathway in the tumour environment, a vulnerability that might be used to target them.in Nature on February 24, 2021 12:00 AM.
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Low arousal threshold plays a part in the pathogenesis of obstructive sleep apnea (OSA) and may be improved by sedatives. Sedative antidepressants are frequently prescribed for stroke patients due to their high prevalence of insomnia and depression. However, the effect of sedative antidepressants on the severity of OSA in stroke patients has not been studied well.
In a double-blinded randomized crossover pilot study, 22 post-acute ischemic stroke patients (mean age, 61.7 ± 10.6 y) with OSA received 100 mg of trazodone or a placebo just before polysomnography, with approximately 1 week between measures. The study also measured baseline heart rate variability and 24-h ambulatory blood pressure.
Administration of trazodone significantly increased the percentage time of slow-wave sleep (31.5 ± 13.2 vs. 18.4 ± 8.7%; P < 0.001) and improved almost all the parameters of OSA severity, including the apnea–hypopnea index (AHI, 25.4 ± 15.4 vs. 39.1 ± 18.4 events/h; P < 0.001), the respiratory arousal index (9.8 (5.8–11.95) vs. 14.1 (11.3–18.7) events/h; P < 0.001), and the minimum oxygen saturation (80.2 ± 9.1 vs. 77.1 ± 9.6%; P = 0.016). Responders to therapy (AHI reduced by > 50%; n = 7/22) had predominant OSA during rapid-eye-movement sleep and decreased sympathetic tone, as reflected in significantly lower mean blood pressure, diastolic blood pressure, and normalized low-frequency power.
Obstructive sleep apnea with comorbid ischemic stroke may be a distinctive phenotype which responds quite well to trazodone, decreasing OSA severity without increasing nocturnal hypoxia.
Clinicaltrials.gov: NCT04162743, 2019/11/10.
in Journal of Neurology on February 24, 2021 12:00 AM.
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Late-onset Pompe disease (LOPD) is a rare autosomal recessive disorder caused by mutations in the GAA gene, leading to progressive weakness of locomotor and respiratory muscles. Enzyme replacement therapy (ERT), administered every second week, has been proven to slow down disease progression and stabilize pulmonary function. Due to the COVID-19 pandemic in Germany, ERT was interrupted at our centre for 29 days. As reports on ERT discontinuation in LOPD are rare, our study aimed to analyse the impact of ERT interruption on the change in clinical outcome.
We performed a prospective cohort study in 12 LOPD patients. Clinical assessments were performed after ERT interruption and after the next three consecutive infusions. We assessed motor function by muscle strength testing, a 6-minute-walk-test, pulmonary function tests, and adverse events. For statistical analysis, an estimated baseline was calculated based on the individual yearly decline.
The mean time of ERT interruption was 49.42 days (SD ± 12.54). During ERT interruption, seven patients reported 14 adverse events and two of them were severe. Frequent symptoms were reduced muscle endurance/increased muscle fatigability and shortness of breath/worsening of breathing impairment. After ERT interruption, significant deterioration was found for MIP%pred (p = 0.026) and MRC%pred, as well as a trend to clinical deterioration in FVC%pred and the 6MWT%pred.
Interruption of ERT was associated with a deterioration in the core clinical outcome measures. Therefore, an interruption of ERT should be kept as short as possible.
in Journal of Neurology on February 24, 2021 12:00 AM.
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We intended to clarify the phenotypic and molecular diversities of spinocerebellar ataxia type 2 (SCA2) in Japan.
DNA was extracted from the peripheral blood of 436 patients, including 126 patients with chronic neuropathy, 108 with amyotrophic lateral sclerosis, and 202 with cerebellar ataxia. We then PCR-amplified and sequenced the ATXN2 gene. The biopsied sural nerves of mutation-positive patients were subjected to light-microscopic and electron-microscopic analyses. Transfection analyses were performed using a Schwann cell line, IMS32.
We found PCR-amplified products potentially corresponding to expanded CAG repeats in four patients. Two patients in the chronic neuropathy group had a full repeat expansion or an intermediate expansion (39 or 32 repeats), without limb ataxia. The sural nerve biopsy findings of the two patients included axonal neuropathy and mixed neuropathy (axonal changes with demyelination). Schwann cells harbored either cytoplasmic or nuclear inclusions on electron microscopic examination. Both patients recently exhibited pyramidal signs. In the third patient in the cerebellar ataxia group, we identified a novel 21-base duplication mutation near 22 CAG repeats (c.432_452dup). The transfection study revealed that the 21-base-duplication mutant Ataxin-2 proteins aggregated in IMS32 and rendered cells susceptible to oxidative stress, similar to a CAG-expanded mutant. The fourth patient, with 41 repeats, had ataxia and spasticity. The two patients with cerebellar ataxia also had peripheral neuropathy.
Patients with expanded CAG repeats can exhibit a neuropathy-dominant phenotype not described previously. The novel 21-base-duplication mutant seems to share the aggregation properties of polyglutamine-expanded mutants.
in Journal of Neurology on February 24, 2021 12:00 AM.
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Beside its widely studied role in the pathogenesis of Alzheimer's disease (AD), β-amyloid (Aβ) is a normal and soluble product of neuronal metabolism that regulates several key physiological functions, exerting neuromodulatory effects on synaptic plasticity, memory, and neurotransmitter release. Such effects have been observed to occur in a hormetic fashion, with Aβ exhibiting a dual role influenced by its concentration, the different isoforms, or aggregation forms of the peptide. However, to date, our knowledge about the physiological functions of Aβ and, in particular, its modulatory role on synaptic activity and neurotransmission in the normal brain is fragmentary, thus hindering a clear comprehension of the biological mechanisms underlying the derangement from function to dysfunction. In particular, according to the amyloid cascade hypothesis, the switch from physiology to pathology is linked to the abnormal increase in Aβ levels, due to an imbalance in Aβ production and clearance. In this regard, increased Aβ levels have been hypothesized to induce early defects in synaptic function and such alterations have been suggested to account, at least in part, for the onset of neuropsychiatric symptoms (e.g., apathy, anxiety, changes in mood, depression, and agitation/aggression), frequently observed in the prodromal stage of AD. Therefore, understanding the biological mechanisms underlying early synaptic alterations in AD is a key starting point to frame the relevant time windows for AD treatment and to gain insight into AD etiopathogenesis.
in Frontiers in Molecular Neuroscience on February 24, 2021 12:00 AM.
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Traumatic brain injury (TBI) has been linked with tauopathy. However, imaging methods that can non-invasively detect tau-protein abnormalities following TBI need further investigation. This study aimed to investigate the potential of diffusion tensor imaging (DTI) to detect tauopathy following TBI in P301L mutant-tau-transgenic-pR5-mice. A total of 24 9-month-old pR5 mice were randomly assigned to sham and TBI groups. Controlled cortical injuries/craniotomies were performed for TBI/sham groups followed by DTI data acquisition on days 1 and 7 post-injury. DTI data were analyzed by using voxelwise analysis and track-based spatial statistics for gray matter and white matter. Further, immunohistochemistry was performed for total-tau and phosphorylated-tau, astrocytes, and microglia. To detect the association of DTI with these pathological markers, a correlation analysis was performed between DTI and histology findings. At day 1 post-TBI, DTI revealed a widespread reduction in fractional anisotropy (FA) and axial diffusivity (AxD) in the TBI group compared to shams. On day 7, further reduction in FA, AxD, and mean diffusivity and increased radial diffusivity were observed. FA was significantly increased in the amygdala and cortex. Correlation results showed that in the ipsilateral hemisphere FA reduction was associated with increased phosphorylated-tau and glial-immunoreactivity, whereas in the contralateral regions, the FA increase was associated with increased immunostaining for astrocytes. This study is the first to exploit DTI to investigate the effect of TBI in tau-transgenic mice. We show that alterations in the DTI signal were associated with glial activity following TBI and would most likely reflect changes that co-occur with/without phosphorylated-tau. In addition, FA may be a promising measure to identify discrete pathological processes such as increased astroglia activation, tau-hyperphosphorylation or both in the brain following TBI.
in Frontiers in Neuroscience: Brain Imaging Methods on February 24, 2021 12:00 AM.
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The clinical characteristics and biological effects on the nervous system of infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain poorly understood. The aim of this study is to advance epidemiological and mechanistic understanding of the neurological manifestations of coronavirus disease 2019 (COVID-19) using stroke as a case study. In this study, we performed a meta-analysis of clinical studies reporting stroke history, intensive inflammatory response, and procoagulant state C-reactive protein (CRP), Procalcitonin (PCT), and coagulation indicator (D-dimer) in patients with COVID-19. Via network-based analysis of SARS-CoV-2 host genes and stroke-associated genes in the human protein-protein interactome, we inspected the underlying inflammatory mechanisms between COVID-19 and stroke. Finally, we further verified the network-based findings using three RNA-sequencing datasets generated from SARS-CoV-2 infected populations. We found that the overall pooled prevalence of stroke history was 2.98% (95% CI, 1.89–4.68; I2=69.2%) in the COVID-19 population. Notably, the severe group had a higher prevalence of stroke (6.06%; 95% CI 3.80–9.52; I2 = 42.6%) compare to the non-severe group (1.1%, 95% CI 0.72–1.71; I2 = 0.0%). There were increased levels of CRP, PCT, and D-dimer in severe illness, and the pooled mean difference was 40.7 mg/L (95% CI, 24.3–57.1), 0.07 μg/L (95% CI, 0.04–0.10) and 0.63 mg/L (95% CI, 0.28–0.97), respectively. Vascular cell adhesion molecule 1 (VCAM-1), one of the leukocyte adhesion molecules, is suspected to play a vital role of SARS-CoV-2 mediated inflammatory responses. RNA-sequencing data analyses of the SARS-CoV-2 infected patients further revealed the relative importance of inflammatory responses in COVID-19-associated neurological manifestations. In summary, we identified an elevated vulnerability of those with a history of stroke to severe COVID-19 underlying inflammatory responses (i.e., VCAM-1) and procoagulant pathways, suggesting monotonic relationships, thus implicating causality.
in Frontiers in Neuroscience: Systems Biology on February 24, 2021 12:00 AM.
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Photoacoustic tomography (PAT) is a propitious imaging modality, which is helpful for biomedical study. However, fast PAT imaging and denoising is an exigent task in medical research. To address the problem, recently, methods based on compressed sensing (CS) have been proposed, which accede the low computational cost and high resolution for implementing PAT. Nevertheless, the imaging results of the sparsity-based methods strictly rely on sparsity and incoherence conditions. Furthermore, it is onerous to ensure that the experimentally acquired photoacoustic data meets CS’s prerequisite conditions. In this work, a deep learning–based PAT (Deep-PAT)method is instigated to overcome these limitations. By using a neural network, Deep-PAT is not only able to reconstruct PAT from a fewer number of measurements without considering the prerequisite conditions of CS, but also can eliminate undersampled artifacts effectively. The experimental results demonstrate that Deep-PAT is proficient at recovering high-quality photoacoustic images using just 5% of the original measurement data. Besides this, compared with the sparsity-based method, it can be seen through statistical analysis that the quality is significantly improved by 30% (approximately), having average SSIM = 0.974 and PSNR = 29.88 dB with standard deviation ±0.007 and ±0.089, respectively, by the proposed Deep-PAT method. Also, a comparsion of multiple neural networks provides insights into choosing the best one for further study and practical implementation.
in Frontiers in Neuroscience: Brain Imaging Methods on February 24, 2021 12:00 AM.
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In this work fMRI BOLD datasets are shown to contain slice-dependent non-stationarities. A model containing slice-dependent, non-stationary signal power is proposed to address time-varying signal power during BOLD data acquisition. The impact of non-stationary power on functional MRI connectivity is analytically derived, establishing that pairwise connectivity estimates are scaled by a function of the time-varying signal power, with magnitude upper bound by 1, and that the variance of sample correlation is increased, thereby inducing spurious connectivity. Consequently, we make the observation that time-varying power during acquisition of BOLD timeseries has the propensity to diminish connectivity estimates. To ameliorate the impact of non-stationary signal power, a simple correction for slice-dependent non-stationarity is proposed. Our correction is analytically shown to restore both signal stationarity and, subsequently, the integrity of connectivity estimates. Theoretical results are corroborated with empirical evidence demonstrating the utility of our correction. In addition, slice-dependent non-stationary variance is experimentally determined to be optimally characterized by an inverse Gamma distribution. The resulting distribution of a voxel's signal intensity is analytically derived to be a generalized Student's-t distribution, providing support for the Gaussianity assumption typically imposed by fMRI connectivity methods.
in Frontiers in Neuroscience: Brain Imaging Methods on February 24, 2021 12:00 AM.
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Objective: To examine changes in patients’ desired control of the deep brain stimulator (DBS) and perception of global life control throughout DBS.
Methods: A consecutive cohort of 52 patients with Parkinson’s disease (PD) was recruited to participate in a prospective longitudinal study over three assessment points (pre-surgery, post-surgery months 3 and 6). Semi-structured interviews assessing participants’ desire for stimulation control and perception of global control were conducted at all three points. Qualitative data were coded using content analysis. Visual analog scales were embedded in the interviews to quantify participants’ perceptions of control over time.
Results: Participants reported significant increases in their perception of global control over time and significant declines in their desired control of the stimulation. These changes were unrelated to improvements in motor symptoms. Improvements in global control were negatively correlated with a decline in desired stimulation control. Qualitative data indicate that participants have changed, nuanced levels of desired control over their stimulators. Increased global life control following DBS may be attributed to increased control over PD symptoms, increased ability to engage in valued activities, and increased overall self-regulation, while other domains related to global control remained unaffected by DBS.
Conclusions: There are few empirical data documenting patients’ desire for stimulation control throughout neuromodulation and how stimulation control is related to other aspects of control despite the growing application of neuromodulation devices to treat a variety of disorders. Our data highlight distinctions in different types of control and have implications for the development of patient-controlled neurostimulation devices.
in Frontiers in Human Neuroscience on February 24, 2021 12:00 AM.
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The lifetime prevalence of major depressive disorder (MDD) in adolescents is reported to be as high as 20%; thus, MDD constitutes a significant social and public health burden. MDD is often associated with nonsuicidal self-injury (NSSI) behavior, but the contributing factors including cognitive function have not been investigated in detail. To this end, the present study evaluated cognitive impairment and psychosocial factors in associated with MDD with NSSI behavior. Eighteen and 21 drug-naïve patients with first-episode MDD with or without NSSI (NSSI+/– group) and 24 healthy control subjects (HC) were enrolled in the study. The Hamilton Anxiety Scale (HAMA), Hamilton Depression Scale (HAMD), Adolescent Self-injury Questionnaire, Beck Scale for Suicide Ideation–Chinese Version (BSI-CV), Shame Scale for Middle School Students, Sensation Seeking Scale (SSS) and Childhood Trauma Questionnaire (CTQ) were used to assess depression-related behaviors, and event-related potentials (ERPs) were recorded as a measure of cognitive function. The latency of the N1, N2, P3a, P3b, and P50 components of ERPs at the Cz electrode point; P50 amplitude and P50 inhibition (S1/S2) showed significant differences between the 3 groups. CTQ scores also differed across three groups, and the NSSI– and NSSI+ groups showed significant differences in scores on the Shame Scale for Middle School Students. Thus, cognitive function was impaired in adolescents with MDD with NSSI behavior, which was mainly manifested as memory decline, attention and executive function deficits, and low anti-interference ability. We also found that childhood abuse, lack of social support, and a sense of shame contributed to NSSI behavior. These findings provide insight into the risk factors for MDD with NSSI behavior, which can help mental health workers more effectively diagnose and treat these patients.
in Frontiers in Human Neuroscience on February 24, 2021 12:00 AM.
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A high percent of oxidative energy metabolism is needed to support brain growth during infancy. Unhealthy diets and limited nutrition, as well as other environmental insults, can compromise these essential developmental processes. In particular, iron deficiency anemia (IDA) has been found to undermine both normal brain growth and neurobehavioral development. Even moderate ID may affect neural maturation because when iron is limited, it is prioritized first to red blood cells over the brain. A primate model was used to investigate the neural effects of a transient ID and if deficits would persist after iron treatment. The large size and postnatal growth of the monkey brain makes the findings relevant to the metabolic and iron needs of human infants, and initiating treatment upon diagnosis of anemia reflects clinical practice. Specifically, this analysis determined whether brain maturation would still be compromised at 1 year of age if an anemic infant was treated promptly once diagnosed. The hematology and iron status of 41 infant rhesus monkeys was screened at 2-month intervals. Fifteen became ID; 12 met clinical criteria for anemia and were administered iron dextran and B vitamins for 1–2 months. MRI scans were acquired at 1 year. The volumetric and diffusion tensor imaging (DTI) measures from the ID infants were compared with monkeys who remained continuously iron sufficient (IS). A prior history of ID was associated with smaller total brain volumes, driven primarily by significantly less total gray matter (GM) and smaller GM volumes in several cortical regions. At the macrostructual level, the effect on white matter volumes (WM) was not as overt. However, DTI analyses of WM microstructure indicated two later-maturating anterior tracts were negatively affected. The findings reaffirm the importance of iron for normal brain development. Given that brain differences were still evident even after iron treatment and following recovery of iron-dependent hematological indices, the results highlight the importance of early detection and preemptive supplementation to limit the neural consequences of ID.
in Frontiers in Human Neuroscience on February 24, 2021 12:00 AM.
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Rationale: High-frequency oscillations (HFOs) in intracranial EEG (iEEG) are used to delineate the epileptogenic zone during presurgical diagnostic assessment in patients with epilepsy. HFOs are historically divided into ripples (80–250 Hz), fast ripples (FR, >250 Hz), and their co-occurrence (FRandR). In a previous study, we had validated the rate of FRandRs during deep sleep to predict seizure outcome. Here, we ask whether epileptic FRandRs might be confounded by physiological FRandRs that are unrelated to epilepsy.
Methods: We recorded iEEG in the medial temporal lobe MTL (hippocampus, entorhinal cortex, and amygdala) in 17 patients while they performed cognitive tasks. The three cognitive tasks addressed verbal working memory, visual working memory, and emotional processing. In our previous studies, these tasks activated the MTL. We re-analyzed the data of these studies with the automated detector that focuses on the co-occurrence of ripples and FRs (FRandR).
Results: For each task, we identified those channels in which the HFO rate was modulated during the task condition compared to the control condition. However, the number of these channels did not exceed the chance level. Interestingly, even during wakefulness, the HFO rate was higher for channels within the seizure onset zone (SOZ) than for channels outside the SOZ.
Conclusion: Our prospective definition of an epileptic HFO, the FRandR, is not confounded by physiological HFOs that might be elicited by our cognitive tasks. This is reassuring for the clinical use of FRandR as a biomarker of the EZ.
in Frontiers in Human Neuroscience on February 24, 2021 12:00 AM.
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Embodied theories of grounded semantics postulate that, when word meaning is first acquired, a link is established between symbol (word form) and corresponding semantic information present in modality-specific—including primary—sensorimotor cortices of the brain. Direct experimental evidence documenting the emergence of such a link (i.e., showing that presentation of a previously unknown, meaningless word sound induces, after learning, category-specific reactivation of relevant primary sensory or motor brain areas), however, is still missing. Here, we present new neuroimaging results that provide such evidence. We taught participants aspects of the referential meaning of previously unknown, senseless novel spoken words (such as “Shruba” or “Flipe”) by associating them with either a familiar action or a familiar object. After training, we used functional magnetic resonance imaging to analyze the participants’ brain responses to the new speech items. We found that hearing the newly learnt object-related word sounds selectively triggered activity in the primary visual cortex, as well as secondary and higher visual areas.These results for the first time directly document the formation of a link between the novel, previously meaningless spoken items and corresponding semantic information in primary sensory areas in a category-specific manner, providing experimental support for perceptual accounts of word-meaning acquisition in the brain.
in Frontiers in Human Neuroscience on February 24, 2021 12:00 AM.
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Recurrent cortical networks provide reservoirs of states that are thought to play a crucial role for sequential information processing in the brain. However, classical reservoir computing requires manual adjustments of global network parameters, particularly of the spectral radius of the recurrent synaptic weight matrix. It is hence not clear if the spectral radius is accessible to biological neural networks. Using random matrix theory, we show that the spectral radius is related to local properties of the neuronal dynamics whenever the overall dynamical state is only weakly correlated. This result allows us to introduce two local homeostatic synaptic scaling mechanisms, termed flow control and variance control, that implicitly drive the spectral radius toward the desired value. For both mechanisms the spectral radius is autonomously adapted while the network receives and processes inputs under working conditions. We demonstrate the effectiveness of the two adaptation mechanisms under different external input protocols. Moreover, we evaluated the network performance after adaptation by training the network to perform a time-delayed XOR operation on binary sequences. As our main result, we found that flow control reliably regulates the spectral radius for different types of input statistics. Precise tuning is however negatively affected when interneural correlations are substantial. Furthermore, we found a consistent task performance over a wide range of input strengths/variances. Variance control did however not yield the desired spectral radii with the same precision, being less consistent across different input strengths. Given the effectiveness and remarkably simple mathematical form of flow control, we conclude that self-consistent local control of the spectral radius via an implicit adaptation scheme is an interesting and biological plausible alternative to conventional methods using set point homeostatic feedback controls of neural firing.
in Frontiers in Computational Neuroscience on February 24, 2021 12:00 AM.
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The advent of optogenetics has revolutionized experimental research in the field of Neuroscience and the possibility to selectively stimulate neurons in 3D volumes has opened new routes in the understanding of brain dynamics and functions. The combination of multiphoton excitation and optogenetic methods allows to identify and excite specific neuronal targets by means of the generation of cloud of excitation points. The most widely employed approach to produce the points cloud is through a spatial light modulation (SLM) which works with a refresh rate of tens of Hz. However, the computational time requested to calculate 3D patterns ranges between a few seconds and a few minutes, strongly limiting the overall performance of the system. The maximum speed of SLM can in fact be employed either with high quality patterns embedded into pre-calculated sequences or with low quality patterns for real time update. Here, we propose the implementation of a recently developed compressed sensing Gerchberg-Saxton algorithm on a consumer graphical processor unit allowing the generation of high quality patterns at video rate. This, would in turn dramatically reduce dead times in the experimental sessions, and could enable applications previously impossible, such as the control of neuronal network activity driven by the feedback from single neurons functional signals detected through calcium or voltage imaging or the real time compensation of motion artifacts.
in Frontiers in Cellular Neuroscience on February 24, 2021 12:00 AM.
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Increased innate immune activation and inflammation are common findings in psychotic and affective (mood) disorders such as schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD), including increased numbers and activation of monocytes and macrophages. These findings often differ depending on the disorder, for example, we previously found increases in circulating inflammatory cytokines associated with monocytes and macrophages in SCZ, while BD had increases in anti-inflammatory cytokines. Despite these differences, few studies have specifically compared immune dysfunction in affective versus non-affective psychotic disorders and none have compared functional monocyte responses across these disorders. To address this, we recruited 25 first episode psychosis (FEP) patients and 23 healthy controls (HC). FEP patients were further grouped based on the presence (AFF) or absence (NON) of mood disorder. We isolated peripheral blood mononuclear cells and cultured them for 1 week with M-CSF to obtain monocyte-derived macrophages. These cells were then stimulated for 24 h to skew them to inflammatory and alternative phenotypes, in order to identify differences in these responses. Following stimulation with LPS and LPS plus IFNγ, we found that macrophages from the NON-group had diminished inflammatory responses compared to both HC and AFF groups. Interestingly, when skewing macrophages to an alternative phenotype using LPS plus IL-4, the AFF macrophages increased production of inflammatory cytokines. Receiver operating curve analysis showed predictive power of inflammatory cytokine concentrations after LPS stimulation in the AFF group versus NON-group. Our results suggest dysfunctional monocyte responses in both affective and non-affective psychotic disorder, with varying types of immune dysfunction depending on the presence or absence of a mood component.
in Frontiers in Cellular Neuroscience on February 24, 2021 12:00 AM.
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Parkinson’s disease (PD) is one of the most common neurodegenerative maladies with unforeseen complex pathologies. While this neurodegenerative disorder’s neuropathology is reasonably well known, its etiology remains a mystery, making it challenging to aim therapy. Glial cell-line derived neurotrophic factor (GDNF) remains an auspicious therapeutic molecule for treating PD. Neurotrophic factor derived from glial cell lines is effective in rodents and nonhuman primates, but clinical findings have been equivocal. Laborious exertions have been made over the past few decades to improve and assess GDNF in treating PD (clinical studies). Definitive clinical trials have, however, failed to demonstrate a survival advantage. Consequently, there seemed to be a doubt as to whether GDNF has merit in the potential treatment of PD. The purpose of this cutting edge review is to speculate as to why the clinical trials have failed to meet the primary endpoint. We introduce a hypothesis, “Failure of GDNF in clinical trials succumbed by nuclear receptor-related factor 1 (Nurr1) shortfall.” We demonstrate how Nurr1 binds to GDNF to induce dopaminergic neuron synthesis. Due to its undisputable neuro-protection aptitude, we display Nurr1 (also called Nr4a2) as a promising therapeutic target for PD.
in Frontiers in Ageing Neuroscience on February 24, 2021 12:00 AM.
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Background: Parkinson’s disease (PD) and osteoporosis are both common aging diseases. It is reported that PD has a close relationship with osteoporosis and bone secretory proteins may be involved in disease progression.
Objectives: To detect the bone-derived factors in plasma and cerebrospinal fluid (CSF) of patients with PD and evaluate their correlations with C-reaction protein (CRP) level, motor impairment, and Hoehn-Yahr (HY) stage of the disease.
Methods: We included 250 PD patients and 250 controls. Levels of osteocalcin (OCN), osteopontin (OPN), osteoprotegerin (OPG), Sclerostin (SO), Bone morphogenetic protein 2 (BMP2), and Dickkopf-1 (DKK-1) in plasma and CSF were measured by custom protein antibody arrays. Data were analyzed using Mann–Whitney U-test and Spearman’s receptor activator of NF-κB (RANK) correlation.
Results: Plasma levels of OCN and OPN were correlated with CRP levels and HY stage and motor impairment of PD. Furthermore, the plasma assessment with CSF detection may enhance their potential prediction on PD.
Conclusions: OCN and OPN may serve as potential biomarkers for PD. The inflammation response may be involved in the cross-talk between the two factors and PD.
in Frontiers in Ageing Neuroscience on February 24, 2021 12:00 AM.
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Background: Despite known associations between low blood hemoglobin level and Alzheimer's disease (AD) or cognitive impairment, the underlying neuropathological links are poorly understood. We aimed to examine the relationships of blood hemoglobin levels with in vivo AD pathologies (i.e., cerebral beta-amyloid [Aβ] deposition, tau deposition, and AD-signature degeneration) and white matter hyperintensities (WMHs), which are a measure of cerebrovascular injury. We also investigated the association between hemoglobin level and cognitive performance, and then assessed whether such an association is mediated by brain pathologies.
Methods: A total of 428 non-demented older adults underwent comprehensive clinical assessments, hemoglobin level measurement, and multimodal brain imaging, including Pittsburgh compound B-positron emission tomography (PET), AV-1451 PET, fluorodeoxyglucose (FDG)-PET, and magnetic resonance imaging. Episodic memory score and global cognition scores were also measured.
Results: A lower hemoglobin level was significantly associated with reduced AD-signature cerebral glucose metabolism (AD-CM), but not Aβ deposition, tau deposition, or WMH volume. A lower hemoglobin level was also significantly associated with poorer episodic memory and global cognition scores, but such associations disappeared when AD-CM was controlled as a covariate, indicating that AD-CM has a moderating effect.
Conclusion: The present findings suggest that low blood hemoglobin in older adults is associated with cognitive decline via reduced brain metabolism, which seems to be independent of those aspects of AD-specific protein pathologies and cerebrovascular injury that are reflected in PET and MRI measures.
in Frontiers in Ageing Neuroscience on February 24, 2021 12:00 AM.
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Aging affects the overall physiology, including the image-forming and non-image forming visual systems. Among the components of the latter, the thalamic retinorecipient inter-geniculate leaflet (IGL) and ventral lateral geniculate (vLGN) nucleus conveys light information to subcortical regions, adjusting visuomotor, and circadian functions. It is noteworthy that several visual related cells, such as neuronal subpopulations in the IGL and vLGN are neurochemically characterized by the presence of calcium binding proteins. Calretinin (CR), a representative of such proteins, denotes region-specificity in a temporal manner by variable day–night expression. In parallel, age-related brain dysfunction and neurodegeneration are associated with abnormal intracellular concentrations of calcium. Here, we investigated whether daily changes in the number of CR neurons are a feature of the aged IGL and vLGN in rats. To this end, we perfused rats, ranging from 3 to 24 months of age, within distinct phases of the day, namely zeitgeber times (ZTs). Then, we evaluated CR immunolabeling through design-based stereological cell estimation. We observed distinct daily rhythms of CR expression in the IGL and in both the retinorecipient (vLGNe) and non-retinorecipient (vLGNi) portions of the vLGN. In the ZT 6, the middle of the light phase, the CR cells are reduced with aging in the IGL and vLGNe. In the ZT 12, the transition between light to dark, an age-related CR loss was found in all nuclei. While CR expression predominates in specific spatial domains of vLGN, age-related changes appear not to be restricted at particular portions. No alterations were found in the dark/light transition or in the middle of the dark phase, ZTs 0, and 18, respectively. These results are relevant in the understanding of how aging shifts the phenotype of visual related cells at topographically organized channels of visuomotor and circadian processing.
in Frontiers in Ageing Neuroscience on February 24, 2021 12:00 AM.
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Objective: To define resilience metrics for cognitive decline based on plasma and cerebrospinal fluid (CSF) amyloid-β (Aβ) and examine the demographic, genetic, and neuroimaging factors associated with interindividual differences among metrics of resilience and to demonstrate the ability of such metrics to predict the diagnostic conversion to mild cognitive impairment (MCI).
Methods: In this study, cognitively normal (CN) participants with Aβ-positive were included from the Sino Longitudinal Study on Cognitive Decline (SILCODE, n = 100) and Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 144). Using a latent variable model of data, metrics of resilience [brain resilience (BR), cognitive resilience (CR), and global resilience (GR)] were defined based on the plasma Aβ and CSF Aβ. Linear regression analyses were applied to investigate the association between characteristics of individuals (age, sex, educational level, genetic, and neuroimaging factors) and their resilience. The plausibility of these metrics was tested using linear mixed-effects models and Cox regression models in longitudinal analyses. We also compared the effectiveness of these metrics with conventional metrics in predicting the clinical progression.
Results: Although individuals in the ADNI cohort were older (74.68 [5.65] vs. 65.38 [4.66], p < 0.001) and had higher educational levels (16.3 [2.6] vs. 12.6 [2.8], p < 0.001) than those in the SILCODE cohort, similar loadings between resilience and its indicators were found within both models. BR and GR were mainly associated with age, women, and brain volume in both cohorts. Prediction models showed that higher CR and GR were related to better cognitive performance, and specifically, all types of resilience to CSF Aβ could predict longitudinal cognitive decline.
Conclusion: Different phenotypes of resilience depending on cognition and brain volumes were associated with different factors. Such comprehensive resilience provided insight into the mechanisms of susceptibility for Alzheimer's disease (AD) at the individual level, and interindividual differences in resilience had the potential to predict the disease progression in CN people.
in Frontiers in Ageing Neuroscience on February 24, 2021 12:00 AM.
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Background: The incidence of obstructive sleep apnea (OSA) in the elderly is high, and the disorder is associated with a variety of chronic diseases. Microvesicles (MVs) are extracellular vesicles secreted by various cells during stimulation or apoptosis that play an important role in the pathogenesis of OSA. However, concentrations of circulating MVs in elderly patients with OSA remain unclear.
Methods: Patients aged >60 years old were recruited and underwent polysomnography. Circulating plasma MV concentrations, including annexin V+MVs, endothelial MVs (EMVs), platelet MVs (PMVs), and leukocyte MVs (LMVs) levels, were measured using a flow cytometer with different labeling methods. Potential factors affecting the concentration of circulating MVs in elderly patients with OSA were determined via Spearman's correlation and multiple linear regression analysis.
Results: Levels of circulating MVs, including both single- (annexin V+MVs, CD144+EMVs, CD41a+PMVs, and CD45+LMVs) and dual-labeled MVs (annexin V+CD144+EMVs), were elevated in elderly patients with OSA. Circulating MVs were positively correlated with OSA severity (AHI, ODI, and SPO2min). To some extent, obesity affected the MV concentrations in elderly patients with OSA. In addition, age and comorbidities may be associated with MV levels, but the correlations between the MV levels and age or comorbidities were not significant.
Conclusion: Concentrations of circulating MVs in elderly patients with OSA are associated with the labeling method used, OSA severity, and obesity. The effects of age and comorbidities on circulating MV levels require further verification using a larger sample size.
in Frontiers in Ageing Neuroscience on February 24, 2021 12:00 AM.
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Network efficiency characterizes how information flows within a network, and it has been used to study the neural basis of cognitive intelligence in adolescence, young adults, and elderly adults, in terms of the white matter in the human brain and functional connectivity networks. However, there were few studies investigating whether the human brain at different ages exhibited different underpins of cognitive and emotional intelligence (EI) from young adults to the middle-aged group, especially in terms of the morphological similarity networks in the human brain. In this study, we used 65 datasets (aging 18–64), including sMRI and behavioral measurements, to study the associations of network efficiency with cognitive intelligence and EI in young adults and the middle-aged group. We proposed a new method of defining the human brain morphological networks using the morphological distribution similarity (including cortical volume, surface area, and thickness). Our results showed inverted age × network efficiency interactions in the relationship of surface-area network efficiency with cognitive intelligence and EI: a negative age × global efficiency (nodal efficiency) interaction in cognitive intelligence, while a positive age × global efficiency (nodal efficiency) interaction in EI. In summary, this study not only proposed a new method of morphological similarity network but also emphasized the developmental effects on the brain mechanisms of intelligence from young adult to middle-aged groups and may promote mental health study on the middle-aged group in the future.
in Frontiers in Ageing Neuroscience on February 24, 2021 12:00 AM.
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Aberrant secretion and accumulation of α-synuclein (α-Syn) as well as the loss of parkin function are associated with the pathogenesis of Parkinson’s disease (PD). Our previous study suggested a functional interaction between those two proteins, showing that the extracellular α-Syn evoked post-translational modifications of parkin, leading to its autoubiquitination and degradation. While parkin plays an important role in mitochondrial biogenesis and turnover, including mitochondrial fission/fusion as well as mitophagy, the involvement of parkin deregulation in α-Syn-induced mitochondrial damage is largely unknown. In the present study, we demonstrated that treatment with exogenous α-Syn triggers mitochondrial dysfunction, reflected by the depolarization of the mitochondrial membrane, elevated synthesis of the mitochondrial superoxide anion, and a decrease in cellular ATP level. At the same time, we observed a protective effect of parkin overexpression on α-Syn-induced mitochondrial dysfunction. α-Syn-dependent disturbances of mitophagy were also shown to be directly related to reduced parkin levels in mitochondria and decreased ubiquitination of mitochondrial proteins. Also, α-Syn impaired mitochondrial biosynthesis due to the parkin-dependent reduction of PGC-1α protein levels. Finally, loss of parkin function as a result of α-Syn treatment induced an overall breakdown of mitochondrial homeostasis that led to the accumulation of abnormal mitochondria. These findings may thus provide the first compelling evidence for the direct association of α-Syn-mediated parkin depletion to impaired mitochondrial function in PD. We suggest that improvement of parkin function may serve as a novel therapeutic strategy to prevent mitochondrial impairment and neurodegeneration in PD (thereby slowing the progression of the disease).
in Frontiers in Ageing Neuroscience on February 24, 2021 12:00 AM.
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in eLife on February 24, 2021 12:00 AM.
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in Cerebellum and Ataxias on February 24, 2021 12:00 AM.
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in bioRxiv: Neuroscience on February 24, 2021 12:00 AM.
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in PNAS on February 23, 2021 04:50 PM.
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in PNAS on February 23, 2021 04:26 PM.
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in PNAS on February 23, 2021 04:26 PM.
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in PNAS on February 23, 2021 04:26 PM.
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in PNAS on February 23, 2021 04:26 PM.
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in PNAS on February 23, 2021 04:26 PM.
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in PNAS on February 23, 2021 04:26 PM.
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in PNAS on February 23, 2021 04:26 PM.
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in PNAS on February 23, 2021 04:26 PM.
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in PNAS on February 23, 2021 04:25 PM.
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Publication date: Available online 23 February 2021
Source: Neural Networks
Author(s): Yongdai Kim, Ilsang Ohn, Dongha Kim
in Neural Networks on February 23, 2021 02:00 PM.
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Publication date: Available online 23 February 2021
Source: Neural Networks
Author(s): Yuanyuan Qing, Yijie Zeng, Qi Cao, Guang-Bin Huang
in Neural Networks on February 23, 2021 02:00 PM.
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Publication date: Available online 23 February 2021
Source: Neural Networks
Author(s): Dongpo Xu, Shengdong Zhang, Huisheng Zhang, Danilo P. Mandic
in Neural Networks on February 23, 2021 02:00 PM.
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by Rahmatullah Roche, Sutanu Bhattacharya, Debswapna Bhattacharya
Crystallography and NMR system (CNS) is currently a widely used method for fragment-free ab initio protein folding from inter-residue distance or contact maps. Despite its widespread use in protein structure prediction, CNS is a decade-old macromolecular structure determination system that was originally developed for solving macromolecular geometry from experimental restraints as opposed to predictive modeling driven by interaction map data. As such, the adaptation of the CNS experimental structure determination protocol for ab initio protein folding is intrinsically anomalous that may undermine the folding accuracy of computational protein structure prediction. In this paper, we propose a new CNS-free hierarchical structure modeling method called DConStruct for folding both soluble and membrane proteins driven by distance and contact information. Rigorous experimental validation shows that DConStruct attains much better reconstruction accuracy than CNS when tested with the same input contact map at varying contact thresholds. The hierarchical modeling with iterative self-correction employed in DConStruct scales at a much higher degree of folding accuracy than CNS with the increase in contact thresholds, ultimately approaching near-optimal reconstruction accuracy at higher-thresholded contact maps. The folding accuracy of DConStruct can be further improved by exploiting distance-based hybrid interaction maps at tri-level thresholding, as demonstrated by the better performance of our method in folding free modeling targets from the 12th and 13th rounds of the Critical Assessment of techniques for protein Structure Prediction (CASP) experiments compared to popular CNS- and fragment-based approaches and energy-minimization protocols, some of which even using much finer-grained distance maps than ours. Additional large-scale benchmarking shows that DConStruct can significantly improve the folding accuracy of membrane proteins compared to a CNS-based approach. These results collectively demonstrate the feasibility of greatly improving the accuracy of ab initio protein folding by optimally exploiting the information encoded in inter-residue interaction maps beyond what is possible by CNS.in PLoS Computational Biology on February 23, 2021 02:00 PM.
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by Richard P. Mann
The collective behaviour of animal and human groups emerges from the individual decisions and actions of their constituent members. Recent research has revealed many ways in which the behaviour of groups can be influenced by differences amongst their constituent individuals. The existence of individual differences that have implications for collective behaviour raises important questions. How are these differences generated and maintained? Are individual differences driven by exogenous factors, or are they a response to the social dilemmas these groups face? Here I consider the classic case of patch selection by foraging agents under conditions of social competition. I introduce a multilevel model wherein the perceptual sensitivities of agents evolve in response to their foraging success or failure over repeated patch selections. This model reveals a bifurcation in the population, creating a class of agents with no perceptual sensitivity. These agents exploit the social environment to avoid the costs of accurate perception, relying on other agents to make fitness rewards insensitive to the choice of foraging patch. This provides a individual-based evolutionary basis for models incorporating perceptual limits that have been proposed to explain observed deviations from the Ideal Free Distribution (IFD) in empirical studies, while showing that the common assumption in such models that agents share identical sensory limits is likely false. Further analysis of the model shows how agents develop perceptual strategic niches in response to environmental variability. The emergence of agents insensitive to reward differences also has implications for societal resource allocation problems, including the use of financial and prediction markets as mechanisms for aggregating collective wisdom.in PLoS Computational Biology on February 23, 2021 02:00 PM.
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by Sarah A. Head, Xavier Hernandez-Alias, Jae-Seong Yang, Ludovica Ciampi, Violeta Beltran-Sastre, Antonio Torres-Méndez, Manuel Irimia, Martin H. Schaefer, Luis Serrano
RNA splicing is widely dysregulated in cancer, frequently due to altered expression or activity of splicing factors (SFs). Microexons are extremely small exons (3–27 nucleotides long) that are highly evolutionarily conserved and play critical roles in promoting neuronal differentiation and development. Inclusion of microexons in mRNA transcripts is mediated by the SF Serine/Arginine Repetitive Matrix 4 (SRRM4), whose expression is largely restricted to neural tissues. However, microexons have been largely overlooked in prior analyses of splicing in cancer, as their small size necessitates specialized computational approaches for their detection. Here, we demonstrate that despite having low expression in normal nonneural tissues, SRRM4 is further silenced in tumors, resulting in the suppression of normal microexon inclusion. Remarkably, SRRM4 is the most consistently silenced SF across all tumor types analyzed, implying a general advantage of microexon down-regulation in cancer independent of its tissue of origin. We show that this silencing is favorable for tumor growth, as decreased SRRM4 expression in tumors is correlated with an increase in mitotic gene expression, and up-regulation of SRRM4 in cancer cell lines dose-dependently inhibits proliferation in vitro and in a mouse xenograft model. Further, this proliferation inhibition is accompanied by induction of neural-like expression and splicing patterns in cancer cells, suggesting that SRRM4 expression shifts the cell state away from proliferation and toward differentiation. We therefore conclude that SRRM4 acts as a proliferation brake, and tumors gain a selective advantage by cutting off this brake.in PLoS Biology on February 23, 2021 02:00 PM.
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Dynamic causal modeling (DCM) is a Bayesian framework to infer directed connections between compartments, and has been used to describe the interactions between underlying neural populations based on functional neuroimaging data. DCM is typically analyzed with the expectation-maximization (EM) algorithm. However, because the inversion of a large-scale continuous system is difficult when noisy observations are present, DCM by EM is typically limited to a small number of compartments ($<10$). Another drawback with the current method is its complexity; when the forward model changes, the posterior mean changes, and we need to re-derive the algorithm for optimization. In this project, we propose the Multiple-Shooting Adjoint (MSA) method to address these limitations. MSA uses the multiple-shooting method for parameter estimation in ordinary differential equations (ODEs) under noisy observations, and is suitable for large-scale systems such as whole-brain analysis in functional MRI (fMRI). Furthermore, MSA uses the adjoint method for accurate gradient estimation in the ODE; since the adjoint method is generic, MSA is a generic method for both linear and non-linear systems, and does not require re-derivation of the algorithm as in EM. We validate MSA in extensive experiments: 1) in toy examples with both linear and non-linear models, we show that MSA achieves better accuracy in parameter value estimation than EM; furthermore, MSA can be successfully applied to large systems with up to 100 compartments; and 2) using real fMRI data, we apply MSA to the estimation of the whole-brain effective connectome and show improved classification of autism spectrum disorder (ASD) vs. control compared to using the functional connectome. The package is provided \url{https://jzkay12.github.io/TorchDiffEqPack}
in arXiv: Quantitative Biology: Neurons and Cognition on February 23, 2021 01:30 AM.
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The auto feature extraction capability of deep neural networks (DNN) endows them the potentiality for analysing complicated electroencephalogram (EEG) data captured from brain functionality research. This work investigates the potential coherent correspondence between the region-of-interest (ROI) for DNN to explore, and ROI for conventional neurophysiological oriented methods to work with, exemplified in the case of working memory study. The attention mechanism induced by global average pooling (GAP) is applied to a public EEG dataset of working memory, to unveil these coherent ROIs via a classification problem. The result shows the alignment of ROIs from different research disciplines. This work asserts the confidence and promise of utilizing DNN for EEG data analysis, albeit in lack of the interpretation to network operations.
in arXiv: Quantitative Biology: Neurons and Cognition on February 23, 2021 01:30 AM.
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With the continued innovations of deep neural networks, spiking neural networks (SNNs) that more closely resemble biological brain synapses have attracted attention owing to their low power consumption. However, for continuous data values, they must employ a coding process to convert the values to spike trains. Thus, they have not yet exceeded the performance of artificial neural networks (ANNs), which handle such values directly. To this end, we combine an ANN and an SNN to build versatile hybrid neural networks (HNNs) that improve the concerned performance.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 23, 2021 01:30 AM.
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In the past decade, the heterogeneous information network (HIN) has become an important methodology for modern recommender systems. To fully leverage its power, manually designed network templates, i.e., meta-structures, are introduced to filter out semantic-aware information. The hand-crafted meta-structure rely on intense expert knowledge, which is both laborious and data-dependent. On the other hand, the number of meta-structures grows exponentially with its size and the number of node types, which prohibits brute-force search. To address these challenges, we propose Genetic Meta-Structure Search (GEMS) to automatically optimize meta-structure designs for recommendation on HINs. Specifically, GEMS adopts a parallel genetic algorithm to search meaningful meta-structures for recommendation, and designs dedicated rules and a meta-structure predictor to efficiently explore the search space. Finally, we propose an attention based multi-view graph convolutional network module to dynamically fuse information from different meta-structures. Extensive experiments on three real-world datasets suggest the effectiveness of GEMS, which consistently outperforms all baseline methods in HIN recommendation. Compared with simplified GEMS which utilizes hand-crafted meta-paths, GEMS achieves over $6\%$ performance gain on most evaluation metrics. More importantly, we conduct an in-depth analysis on the identified meta-structures, which sheds light on the HIN based recommender system design.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 23, 2021 01:30 AM.
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A semi-supervised learning method for spiking neural networks is proposed. The proposed method consists of supervised learning by backpropagation and subsequent unsupervised learning by spike-timing-dependent plasticity (STDP), which is a biologically plausible learning rule. Numerical experiments show that the proposed method improves the accuracy without additional labeling when a small amount of labeled data is used. This feature has not been achieved by existing semi-supervised learning methods of discriminative models. It is possible to implement the proposed learning method for event-driven systems. Hence, it would be highly efficient in real-time problems if it were implemented on neuromorphic hardware. The results suggest that STDP plays an important role other than self-organization when applied after supervised learning, which differs from the previous method of using STDP as pre-training interpreted as self-organization.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 23, 2021 01:30 AM.
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Many real-world mission-critical applications require continual online learning from noisy data and real-time decision making with a defined confidence level. Probabilistic models and stochastic neural networks can explicitly handle uncertainty in data and allow adaptive learning-on-the-fly, but their implementation in a low-power substrate remains a challenge. Here, we introduce a novel hardware fabric that implements a new class of stochastic NN called Neural-Sampling-Machine that exploits stochasticity in synaptic connections for approximate Bayesian inference. Harnessing the inherent non-linearities and stochasticity occurring at the atomic level in emerging materials and devices allows us to capture the synaptic stochasticity occurring at the molecular level in biological synapses. We experimentally demonstrate in-silico hybrid stochastic synapse by pairing a ferroelectric field-effect transistor -based analog weight cell with a two-terminal stochastic selector element. Such a stochastic synapse can be integrated within the well-established crossbar array architecture for compute-in-memory. We experimentally show that the inherent stochastic switching of the selector element between the insulator and metallic state introduces a multiplicative stochastic noise within the synapses of NSM that samples the conductance states of the FeFET, both during learning and inference. We perform network-level simulations to highlight the salient automatic weight normalization feature introduced by the stochastic synapses of the NSM that paves the way for continual online learning without any offline Batch Normalization. We also showcase the Bayesian inferencing capability introduced by the stochastic synapse during inference mode, thus accounting for uncertainty in data. We report 98.25%accuracy on standard image classification task as well as estimation of data uncertainty in rotated samples.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 23, 2021 01:30 AM.
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It has been already shown that combinatorial evolution - the creation of new things through the combination of existing things - can be a powerful way to evolve rather than design technical objects such as electronic circuits in a computer simulation. Intriguingly, only a few iterations seem to be required to already achieve complex objects. In the present paper we want to employ combinatorial evolution in software development. Our research question is whether it is possible to generate computer programs of increasing complexity using automatic programming through combinatorial evolution. Specifically, we ask what kind of basic code blocks are needed at the beginning, how are these code blocks implemented to allow them to combine, and how can code complexity be measured. We implemented a computer program simulating combinatorial evolution of code blocks stored in a database to make them available for combinations. Automatic programming is achieved by evaluating regular expressions. We found that reserved key words of a programming language are suitable for defining the basic code blocks at the beginning of the simulation. We also found that placeholders can be used to combine code blocks and that code complexity can be described in terms of the importance to the programming language. As in the previous combinatorial evolution simulation of electronic circuits, complexity increased from simple keywords and special characters to more complex variable declarations, to class definitions, to methods, and to classes containing methods and variable declarations. Combinatorial evolution, therefore, seems to be a promising approach for automatic programming.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 23, 2021 01:30 AM.
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Many physical, biological and neural systems behave as coupled oscillators, with characteristic phase coupling across different frequencies. Methods such as $n:m$ phase locking value and bi-phase locking value have previously been proposed to quantify phase coupling between two resonant frequencies (e.g. $f$, $2f/3$) and across three frequencies (e.g. $f_1$, $f_2$, $f_1+f_2$), respectively. However, the existing phase coupling metrics have their limitations and limited applications. They cannot be used to detect or quantify phase coupling across multiple frequencies (e.g. $f_1$, $f_2$, $f_3$, $f_4$, $f_1+f_2+f_3-f_4$), or coupling that involves non-integer multiples of the frequencies (e.g. $f_1$, $f_2$, $2f_1/3+f_2/3$). To address the gap, this paper proposes a generalized approach, named multi-phase locking value (M-PLV), for the quantification of various types of instantaneous multi-frequency phase coupling. Different from most instantaneous phase coupling metrics that measure the simultaneous phase coupling, the proposed M-PLV method also allows the detection of delayed phase coupling and the associated time lag between coupled oscillators. The M-PLV has been tested on cases where synthetic coupled signals are generated using white Gaussian signals, and a system comprised of multiple coupled R\"ossler oscillators. Results indicate that the M-PLV can provide a reliable estimation of the time window and frequency combination where the phase coupling is significant, as well as a precise determination of time lag in the case of delayed coupling. This method has the potential to become a powerful new tool for exploring phase coupling in complex nonlinear dynamic systems.
in arXiv: Quantitative Biology: Neurons and Cognition on February 23, 2021 01:30 AM.
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Mental health problems impact quality of life of millions of people around the world. However, diagnosis of mental health disorders is a challenging problem that often relies on self-reporting by patients about their behavioral patterns. Therefore, there is a need for new strategies for diagnosis of mental health problems. The recent introduction of body-area networks consisting of a plethora of accurate sensors embedded in smartwatches and smartphones and deep neural networks (DNNs) points towards a possible solution. However, disease diagnosis based on WMSs and DNNs, and their deployment on edge devices, remains a challenging problem. To this end, we propose a framework called MHDeep that utilizes commercially available WMSs and efficient DNN models to diagnose three important mental health disorders: schizoaffective, major depressive, and bipolar. MHDeep uses eight different categories of data obtained from sensors integrated in a smartwatch and smartphone. Due to limited available data, MHDeep uses a synthetic data generation module to augment real data with synthetic data drawn from the same probability distribution. We use the synthetic dataset to pre-train the DNN models, thus imposing a prior on the weights. We use a grow-and-prune DNN synthesis approach to learn both the architecture and weights during the training process. We use three different data partitions to evaluate the MHDeep models trained with data collected from 74 individuals. We conduct data instance level and patient level evaluations. MHDeep achieves an average test accuracy of 90.4%, 87.3%, and 82.4%, respectively, for classifications between healthy instances and schizoaffective disorder instances, major depressive disorder instances, and bipolar disorder instances. At the patient level, MHDeep DNNs achieve an accuracy of 100%, 100%, and 90.0% for the three mental health disorders, respectively.
in arXiv: Computer Science: Neural and Evolutionary Computing on February 23, 2021 01:30 AM.
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in Journal of Neuroscience Research on February 23, 2021 12:58 AM.
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Nature Photonics, Published online: 23 February 2021; doi:10.1038/s41566-021-00781-3
Publisher Correction: Nanometric axial localization of single fluorescent molecules with modulated excitationin Nature Photomics on February 23, 2021 12:00 AM.
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Nature Photonics, Published online: 23 February 2021; doi:10.1038/s41566-021-00773-3
A new paradigm is emerging in which molecular properties are controlled by modifying the local electromagnetic environment, rather than the traditional approach of changing their composition or structure. Now, a tool to investigate such effects has been demonstrated that should accelerate progress in this exciting field.in Nature Photomics on February 23, 2021 12:00 AM.
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Nature Communications, Published online: 23 February 2021; doi:10.1038/s41467-021-21726-y
Author Correction: An all-to-all approach to the identification of sequence-specific readers for epigenetic DNA modifications on cytosinein Nature Communications on February 23, 2021 12:00 AM.
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Nature Communications, Published online: 23 February 2021; doi:10.1038/s41467-021-21647-w
Publisher Correction: Rapid 14C excursion at 3372-3371 BCE not observed at two different locationsin Nature Communications on February 23, 2021 12:00 AM.
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Nature Communications, Published online: 23 February 2021; doi:10.1038/s41467-021-21616-3
Author Correction: Cryo-EM structure of trimeric Mycobacterium smegmatis succinate dehydrogenase with a membrane-anchor SdhFin Nature Communications on February 23, 2021 12:00 AM.
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Nature Communications, Published online: 23 February 2021; doi:10.1038/s41467-021-21556-y
Author Correction: Intratumoural immune heterogeneity as a hallmark of tumour evolution and progression in hepatocellular carcinomain Nature Communications on February 23, 2021 12:00 AM.
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Nature Communications, Published online: 23 February 2021; doi:10.1038/s41467-021-21509-5
Here, the authors present two local methods for analyzing cryo-EM maps: LocSpiral and LocBSharpen that enhance high-resolution features of cryoEM maps, while preventing map distortions. They also introduce LocBFactor and LocOccupancy, which allow obtaining local B-factors and electron density occupancy maps from cryo-EM reconstructions and the authors demonstrate that these methods improve the interpretability and analysis of cryo-EM maps using different test cases among them recent SARS-CoV-2 spike glycoprotein structures.in Nature Communications on February 23, 2021 12:00 AM.
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Nature Communications, Published online: 23 February 2021; doi:10.1038/s41467-021-21489-6
Enantioenriched medium-sized silicon-stereogenic heterocycles are in high demand due to the potential use in functional materials. Here, the authors show a rhodium-catalyzed enantioselective synthesis of six- and seven-membered tri-organosubstituted silicon-stereogenic heterocycles.in Nature Communications on February 23, 2021 12:00 AM.
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Nature Communications, Published online: 23 February 2021; doi:10.1038/s41467-021-21469-w
The configuration of past ice sheets, and therefore sea level, is highly uncertain. Here, the authors provide a global reconstruction of ice sheets for the past 80,000 years that allows to test proxy based sea level reconstructions and helps to reconcile disagreements with sea level changes inferred from models.in Nature Communications on February 23, 2021 12:00 AM.
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Nature Communications, Published online: 23 February 2021; doi:10.1038/s41467-021-21445-4
Several mechanisms of resistance to T cell-engaging therapies have been described for solid tumors. Here, by using T cell bispecific antibodies and chimeric antigen receptors (CAR) T cells targeting HER2, the authors show that cancer cell intrinsic disruption of interferon-gamma signalling, including downregulation of JAK2, confers resistance to T-cell mediated cytotoxicity.in Nature Communications on February 23, 2021 12:00 AM.
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Nature Communications, Published online: 23 February 2021; doi:10.1038/s41467-021-21439-2
Reply to “A Thermodynamic assessment of the reported room-temperature chemical synthesis of C2”in Nature Communications on February 23, 2021 12:00 AM.
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Nature Communications, Published online: 23 February 2021; doi:10.1038/s41467-021-21433-8
A thermodynamic assessment of the reported room-temperature chemical synthesis of C2in Nature Communications on February 23, 2021 12:00 AM.
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Nature Communications, Published online: 23 February 2021; doi:10.1038/s41467-021-21405-y
Sniff frequency naturally varies with animal type due to allometric scaling. Using data from live animals and a machine olfactory system, Spencer et al. reveal a deeper reason for sniffing with implications for designing gas detectors: the sniff is adapted to efficient odor detection.in Nature Communications on February 23, 2021 12:00 AM.
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Nature Communications, Published online: 23 February 2021; doi:10.1038/s41467-020-20836-3
Disentangling the various pathways by which climate change may drive community shifts in real-world ecosystems is challenging. Here the authors apply a trend attribution approach to a large dataset from the MASTIF database to assess the contribution of direct and indirect effects of climate on tree fecundity in North America, finding that the latter dominate trends by affecting tree growth and size and thereby fecundity.in Nature Communications on February 23, 2021 12:00 AM.
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Perineuronal nets (PNNs) are specialized, reticular structures of the extracellular matrix (ECM) that can be found covering the soma and proximal dendrites of a neuronal subpopulation. Recent studies have shown that PNNs can highly influence synaptic plasticity and are disrupted in different neuropsychiatric disorders like schizophrenia. Interestingly, there is a growing evidence that microglia can promote the loss of PNNs and contribute to neuropsychiatric disorders. Based on this knowledge, we analyzed the impact of activated microglia on hippocampal neuronal networks in vitro. Therefore, primary cortical microglia were cultured and stimulated via polyinosinic-polycytidylic acid (Poly I:C; 50 μg/ml) administration. The Poly I:C treatment induced the expression and secretion of different cytokines belonging to the CCL- and CXCL-motif chemokine family as well as interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α). In addition, the expression of matrix metalloproteinases (MMPs) could be verified via RT-PCR analysis. Embryonic hippocampal neurons were then cultured for 12 days in vitro (DIV) and treated for 24 h with microglial conditioned medium. Interestingly, immunocytochemical staining of the PNN component Aggrecan revealed a clear disruption of PNNs accompanied by a significant increase of glutamatergic and a decrease of γ-aminobutyric acid-(GABA)ergic synapse numbers on PNN wearing neurons. In contrast, PNN negative neurons showed a significant reduction in both, glutamatergic and GABAergic synapses. Electrophysiological recordings were performed via multielectrode array (MEA) technology and unraveled a significantly increased spontaneous network activity that sustained also 24 and 48 h after the administration of microglia conditioned medium. Taken together, we could observe a strong impact of microglial secreted factors on PNN integrity, synaptic plasticity and electrophysiological properties of cultured neurons. Our observations might enhance the understanding of neuron-microglia interactions considering the ECM.
in Frontiers in Synaptic Neuroscience on February 23, 2021 12:00 AM.
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Traumatic brain injury (TBI) is a leading cause of death in young adults and a risk factor for acquired epilepsy. Severe TBI, after a period of time, causes numerous neuropsychiatric and neurodegenerative problems with varying comorbidities; and brain homeostasis may never be restored. As a consequence of disrupted equilibrium, neuropathological changes such as circuit remodeling, reorganization of neural networks, changes in structural and functional plasticity, predisposition to synchronized activity, and post-translational modification of synaptic proteins may begin to dominate the brain. These pathological changes, over the course of time, contribute to conditions like Alzheimer disease, dementia, anxiety disorders, and post-traumatic epilepsy (PTE). PTE is one of the most common, devastating complications of TBI; and of those affected by a severe TBI, more than 50% develop PTE. The etiopathology and mechanisms of PTE are either unknown or poorly understood, which makes treatment challenging. Although anti-epileptic drugs (AEDs) are used as preventive strategies to manage TBI, control acute seizures and prevent development of PTE, their efficacy in PTE remains controversial. In this review, we discuss novel mechanisms and risk factors underlying PTE. We also discuss dysfunctions of neurovascular unit, cell-specific neuroinflammatory mediators and immune response factors that are vital for epileptogenesis after TBI. Finally, we describe current and novel treatments and management strategies for preventing PTE.
in Frontiers in Molecular Neuroscience on February 23, 2021 12:00 AM.
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Friedreich’s ataxia (FRDA) is the most frequent autosomal recessive ataxia in western countries, with a mean age of onset at 10–15 years. Patients manifest progressive cerebellar and sensory ataxia, dysarthria, lower limb pyramidal weakness, and other systemic manifestations. Previously, we described a family displaying two expanded GAA alleles not only in the proband affected by late-onset FRDA but also in the two asymptomatic family members: the mother and the younger sister. Both of them showed a significant reduction of frataxin levels, without any disease manifestation. Here, we analyzed if a protective mechanism might contribute to modulate the phenotype in this family. We particularly focused on the transcription factor nuclear factor erythroid 2-related factor 2 (NRF2), the first line of antioxidant defense in cells, and on the glutathione (GSH) system, an index of reactive oxygen species (ROS) detoxification ability. Our findings show a great reactivity of the GSH system to the frataxin deficiency, particularly in the asymptomatic mother, where the genes of GSH synthesis [glutamate–cysteine ligase (GCL)] and GSSG detoxification [GSH S-reductase (GSR)] were highly responsive. The GSR was activated even in the asymptomatic sister and in the proband, reflecting the need of buffering the GSSG increase. Furthermore, and contrasting the NRF2 expression documented in FRDA tissues, NRF2 was highly activated in the mother and in the younger sister, while it was constitutively low in the proband. This suggests that, also under frataxin depletion, the endogenous stimulation of NRF2 in asymptomatic FRDA subjects may contribute to protect against the progressive oxidative damage, helping to prevent the onset of neurological symptoms and highlighting an “out-brain origin” of the disease.
in Frontiers in Neuroscience: Neurodegeneration on February 23, 2021 12:00 AM.
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Multimodal neuroimaging provides a rich source of data for identifying brain regions associated with disease progression and aging. However, present studies still typically analyze modalities separately or aggregate voxel-wise measurements and analyses to the structural level, thus reducing statistical power. As a central example, previous works have used two quantitative MRI parameters—R2* and quantitative susceptibility (QS)—to study changes in iron associated with aging in healthy and multiple sclerosis subjects, but failed to simultaneously account for both. In this article, we propose a unified framework that combines information from multiple imaging modalities and regularizes estimates for increased interpretability, generalizability, and stability. Our work focuses on joint region detection problems where overlap between effect supports across modalities is encouraged but not strictly enforced. To achieve this, we combine L1 (lasso), total variation (TV), and L2 group lasso penalties. While the TV penalty encourages geometric regularization by controlling estimate variability and support boundary geometry, the group lasso penalty accounts for similarities in the support between imaging modalities. We address the computational difficulty in this regularization scheme with an alternating direction method of multipliers (ADMM) optimizer. In a neuroimaging application, we compare our method against independent sparse and joint sparse models using a dataset of R2* and QS maps derived from MRI scans of 113 healthy controls: our method produces clinically-interpretable regions where specific iron changes are associated with healthy aging. Together with results across multiple simulation studies, we conclude that our approach identifies regions that are more strongly associated with the variable of interest (e.g., age), more accurate, and more stable with respect to training data variability. This work makes progress toward a stable and interpretable multimodal imaging analysis framework for studying disease-related changes in brain structure and can be extended for classification and disease prediction tasks.
in Frontiers in Human Neuroscience on February 23, 2021 12:00 AM.
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This article concerns sound aesthetic preferences for European foreign languages. We investigated the phonetic-acoustic dimension of the linguistic aesthetic pleasure to describe the “music” found in European languages. The Romance languages, French, Italian, and Spanish, take a lead when people talk about melodious language – the music-like effects in the language (a.k.a., phonetic chill). On the other end of the melodiousness spectrum are German and Arabic that are often considered sounding harsh and un-attractive. Despite the public interest, limited research has been conducted on the topic of phonaesthetics, i.e., the subfield of phonetics that is concerned with the aesthetic properties of speech sounds (Crystal, 2008). Our goal is to fill the existing research gap by identifying the acoustic features that drive the auditory perception of language sound beauty. What is so music-like in the language that makes people say “it is music in my ears”? We had 45 central European participants listening to 16 auditorily presented European languages and rating each language in terms of 22 binary characteristics (e.g., beautiful – ugly and funny – boring) plus indicating their language familiarities, L2 backgrounds, speaker voice liking, demographics, and musicality levels. Findings revealed that all factors in complex interplay explain a certain percentage of variance: familiarity and expertise in foreign languages, speaker voice characteristics, phonetic complexity, musical acoustic properties, and finally musical expertise of the listener. The most important discovery was the trade-off between speech tempo and so-called linguistic melody (pitch variance): the faster the language, the flatter/more atonal it is in terms of the pitch (speech melody), making it highly appealing acoustically (sounding beautiful and sexy), but not so melodious in a “musical” sense.
in Frontiers in Human Neuroscience on February 23, 2021 12:00 AM.
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White matter damage (WMD) was defined as the appearance of rough and uneven echo enhancement in the white matter around the ventricle. The aim of this study was to develop and validate a risk prediction model for neonatal WMD.
Materials and MethodsWe collected data for 1,733 infants hospitalized at the Department of Neonatology at The First Affiliated Hospital of Zhengzhou University from 2017 to 2020. Infants were randomly assigned to training (n = 1,216) or validation (n = 517) cohorts at a ratio of 7:3. Multivariate logistic regression and least absolute shrinkage and selection operator (LASSO) regression analyses were used to establish a risk prediction model and web-based risk calculator based on the training cohort data. The predictive accuracy of the model was verified in the validation cohort.
ResultsWe identified four variables as independent risk factors for brain WMD in neonates by multivariate logistic regression and LASSO analysis, including gestational age, fetal distress, prelabor rupture of membranes, and use of corticosteroids. These were used to establish a risk prediction nomogram and web-based calculator (https://caowenjun.shinyapps.io/dynnomapp/). The C-index of the training and validation sets was 0.898 (95% confidence interval: 0.8745–0.9215) and 0.887 (95% confidence interval: 0.8478–0.9262), respectively. Decision tree analysis showed that the model was highly effective in the threshold range of 1–61%. The sensitivity and specificity of the model were 82.5 and 81.7%, respectively, and the cutoff value was 0.099.
ConclusionThis is the first study describing the use of a nomogram and web-based calculator to predict the risk of WMD in neonates. The web-based calculator increases the applicability of the predictive model and is a convenient tool for doctors at primary hospitals and outpatient clinics, family doctors, and even parents to identify high-risk births early on and implementing appropriate interventions while avoiding excessive treatment of low-risk patients.
in Frontiers in Human Neuroscience on February 23, 2021 12:00 AM.
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Enhanced neuronal activity in the healthy brain can induce de novo myelination and behavioral changes. As neuronal activity can be achieved using non-invasive measures, it may be of interest to utilize the innate ability of neuronal activity to instruct myelination as a novel strategy for myelin repair in demyelinating disorders such as multiple sclerosis (MS). Preclinical studies indicate that stimulation of neuronal activity in demyelinated lesions indeed has the potential to improve remyelination and that the stimulation paradigm is an important determinant of success. However, future studies will need to reveal the most efficient stimulation protocols as well as the biological mechanisms implicated. Nonetheless, clinical studies have already explored non-invasive brain stimulation as an attractive therapeutic approach that ameliorates MS symptomatology. However, whether symptom improvement is due to improved myelin repair remains unclear. In this mini-review, we discuss the neurobiological basis and potential of enhancing neuronal activity as a novel therapeutic approach in MS.
in Frontiers in Cellular Neuroscience on February 23, 2021 12:00 AM.
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Background: Exercise training induces beneficial effects on neurodegenerative diseases, and specifically on multiple sclerosis (MS) and it’s model experimental autoimmune encephalomyelitis (EAE). However, it is unclear whether exercise training exerts direct protective effects on the central nervous system (CNS), nor are the mechanisms of neuroprotection fully understood. In this study, we investigated the direct neuroprotective effects of high-intensity continuous training (HICT) against the development of autoimmune neuroinflammation and the role of resident microglia.
Methods: We used the transfer EAE model to examine the direct effects of training on the CNS. Healthy mice performed HICT by treadmill running, followed by injection of encephalitogenic proteolipid (PLP)-reactive T-cells to induce EAE. EAE severity was assessed clinically and pathologically. Brain microglia from sedentary (SED) and HICT healthy mice, as well as 5-days post EAE induction (before the onset of disease), were analyzed ex vivo for reactive oxygen species (ROS) and nitric oxide (NO) formation, mRNA expression of M1/M2 markers and neurotrophic factors, and secretion of cytokines and chemokines.
Results: Transfer of encephalitogenic T-cells into HICT mice resulted in milder EAE, compared to sedentary mice, as indicated by reduced clinical severity, attenuated T-cell, and neurotoxic macrophage/microglial infiltration, and reduced loss of myelin and axons. In healthy mice, HICT reduced the number of resident microglia without affecting their profile. Isolated microglia from HICT mice after transfer of encephalitogenic T-cells exhibited reduced ROS formation and released less IL-6 and monocyte chemoattractant protein (MCP) in response to PLP-stimulation.
Conclusions: These findings point to the critical role of training intensity in neuroprotection. HICT protects the CNS against autoimmune neuroinflammation by reducing microglial-derived ROS formation, neurotoxicity, and pro-inflammatory responses involved in the propagation of autoimmune neuroinflammation.
in Frontiers in Cellular Neuroscience on February 23, 2021 12:00 AM.
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Extracellular vesicles or EVs are secreted by most, if not all, eukaryote cell types and recaptured by neighboring or distant cells. Their cargo, composed of a vast diversity of proteins, lipids, and nucleic acids, supports the EVs’ inter-cellular communication. The role of EVs in many cellular processes is now well documented both in physiological and pathological conditions. In this review, we focus on the role of EVs in the central nervous system (CNS) in physiological as well as pathological conditions such as neurodegenerative diseases or brain cancers. We also discuss the future of EVs in clinical research, in particular, their value as biomarkers as well as innovative therapeutic agents. While an increasing number of studies reveal EV research as a promising field, progress in the standardization of protocols and innovation in analysis as well as in research tools is needed to make a breakthrough in our understanding of their impact in the pathophysiology of the brain.
in Frontiers in Cellular Neuroscience on February 23, 2021 12:00 AM.
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Herpes simplex virus type 1 (HSV-1) is a widespread neurotropic virus. Primary infection of HSV-1 in facial epithelium leads to retrograde axonal transport to the central nervous system (CNS) where it establishes latency. Under stressful conditions, the virus reactivates, and new progeny are transported anterogradely to the primary site of infection. During the late stages of neuronal infection, axonal damage can occur, however, the impact of HSV-1 infection on the morphology and functional integrity of neuronal dendrites during the early stages of infection is unknown. We previously demonstrated that acute HSV-1 infection in neuronal cell lines selectively enhances Arc protein expression - a major regulator of long-term synaptic plasticity and memory consolidation, known for being a protein-interaction hub in the postsynaptic dendritic compartment. Thus, HSV-1 induced Arc expression may alter the functionality of infected neurons and negatively impact dendritic spine dynamics. In this study we demonstrated that HSV-1 infection induces structural disassembly and functional deregulation in cultured cortical neurons, an altered glutamate response, Arc accumulation within the somata, and decreased expression of spine scaffolding-like proteins such as PSD-95, Drebrin and CaMKIIβ. However, whether these alterations are specific to the HSV-1 infection mechanism or reflect a secondary neurodegenerative process remains to be determined.
in Frontiers in Cellular Neuroscience on February 23, 2021 12:00 AM.
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Neuroserpin is a serine protease inhibitor that regulates the activity of tissue-type plasminogen activator (tPA) in the nervous system. Neuroserpin is strongly expressed during nervous system development as well as during adulthood, when it is predominantly found in regions eliciting synaptic plasticity. In the hippocampus, neuroserpin regulates developmental neurogenesis, synaptic maturation and in adult mice it modulates synaptic plasticity and controls cognitive and social behavior. High expression levels of neuroserpin in the neocortex starting from prenatal stage and persisting during adulthood suggest an important role for the serpin in the formation of this brain region and in the maintenance of cortical functions. In order to uncover neuroserpin function in the murine neocortex, in this work we performed a comprehensive investigation of its expression pattern during development and in the adulthood. Moreover, we assessed the role of neuroserpin in cortex formation by comparing cortical lamination and neuronal maturation between neuroserpin-deficient and control mice. Finally, we evaluated a possible regulatory role of neuroserpin at cortical synapses in neuroserpin-deficient mice. We observed that neuroserpin is expressed starting from the beginning of corticogenesis until adulthood throughout the neocortex in several classes of glutamatergic projection neurons and GABA-ergic interneurons. However, in the absence of neuroserpin we did not detect any alteration either in cortical layer formation, or in neuronal soma size and dendritic length. Furthermore, no significant quantitative changes were observed in the proteome of cortical synapses upon neuroserpin deficiency. We conclude that, although strongly expressed in the neocortex, absence of neuroserpin does not lead to gross developmental abnormalities, and does not perturb the composition of the cortical synaptic proteome.
in Frontiers in Neuroanatomy on February 23, 2021 12:00 AM.
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Alzheimer’s disease (AD) is the most common type of neurodegenerative diseases. There are over 44 million people living with the disease worldwide. While there are currently no effective treatments for AD, induced pluripotent stem cell-derived brain organoids have the potential to provide a better understanding of Alzheimer’s pathogenesis. Nevertheless, developing brain organoid models is expensive, time consuming and often does not reflect disease progression. Using accurate and inexpensive computer simulations of human brain organoids can overcome the current limitations. Induced whole brain organoids (aiWBO) will greatly expand our ability to model AD and can guide wet lab research. In this study, we have successfully developed and validated artificially induced a whole brain organoid platform (NEUBOrg) using our previously validated machine learning platform, DeepNEU (v6.1). Using NEUBorg platform, we have generated aiWBO simulations of AD and provided a novel approach to test genetic risk factors associated with AD progression and pathogenesis.
in Frontiers in Ageing Neuroscience on February 23, 2021 12:00 AM.
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The pathogenesis of Alzheimer’s disease (AD) involves activation of many NLRP3 inflammatory bodies, which may be related to amyloid β peptide and aggregation of misfolded proteins. Autophagy is an important regulator of inflammatory bodies. However, autophagy shows dynamic changes in the development of AD, and its role in inflammation remains controversial. In this study, the key link between autophagic disorders and the NLRP3 inflammasome in AD was investigated. APP/PS1 double transgenic mice and C57 mice with Aβ25–35 injected into the lateral ventricle were used as two animal models of AD. Immunofluorescence staining and Western blot analysis showed that NLRP3 inflammasome-related proteins and inflammatory cytokines, such as IL-1α, IL-1β, IL-6, IL-12, and TNF-α, were increased and microglia were activated in the brains of both AD animal models. Endogenous overexpression of the APPswe gene and exogenous addition of Aβ25–35 increased the expression of NLRP3 inflammasome-related proteins, while exogenous Aβ25–35 intervention more significantly activated inflammation. Furthermore, LC3 was increased in the AD animal and cell models, and the level of Lamp1 decreased. After overexpression of the primary regulator of lysosomal biogenesis, TFEB, the lysosome protein Lamp1 was increased, and LC3 and inflammatory protein expression were decreased. These results suggest that the NLRP3 inflammasome-mediated inflammatory response is activated in AD animal and cell models, which may be related to the decline in autolysosome function. Overexpression of the TFEB protein can reduce the inflammatory response by improving autolysosome function in AD model cells.
in Frontiers in Ageing Neuroscience on February 23, 2021 12:00 AM.
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in eLife on February 23, 2021 12:00 AM.
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in eLife on February 23, 2021 12:00 AM.
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in eLife on February 23, 2021 12:00 AM.
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in eLife on February 23, 2021 12:00 AM.
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in eLife on February 23, 2021 12:00 AM.
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in eLife on February 23, 2021 12:00 AM.
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in BMC Neuroscience on February 23, 2021 12:00 AM.
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in bioRxiv: Neuroscience on February 23, 2021 12:00 AM.
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in bioRxiv: Neuroscience on February 23, 2021 12:00 AM.
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in bioRxiv: Neuroscience on February 23, 2021 12:00 AM.
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in bioRxiv: Neuroscience on February 23, 2021 12:00 AM.
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in bioRxiv: Neuroscience on February 23, 2021 12:00 AM.
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in bioRxiv: Neuroscience on February 23, 2021 12:00 AM.
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in PNAS on February 22, 2021 08:04 PM.
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in PNAS on February 22, 2021 08:04 PM.
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in PNAS on February 22, 2021 08:04 PM.
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Publication date: Available online 21 February 2021
Source: Neural Networks
Author(s): Hiroyuki Kambara, Atsushi Takagi, Haruka Shimizu, Toshihiro Kawase, Natsue Yoshimura, Nicolas Schweighofer, Yasuharu Koike
in Neural Networks on February 22, 2021 02:00 PM.
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by Michael A. Henson
Approximately 30% of patients who have Clostridioides difficile infection (CDI) will suffer at least one incident of reinfection. While the underlying causes of CDI recurrence are poorly understood, interactions between C. difficile and commensal gut bacteria are thought to play an important role. In this study, an in silico pipeline was used to process 16S rRNA gene amplicon sequence data of 225 stool samples from 93 CDI patients into sample-specific models of bacterial community metabolism. Clustered metabolite production rates generated from post-diagnosis samples generated a high Enterobacteriaceae abundance cluster containing disproportionately large numbers of recurrent samples and patients. This cluster was predicted to have significantly reduced capabilities for secondary bile acid synthesis but elevated capabilities for aromatic amino acid catabolism. When applied to 16S sequence data of 40 samples from fecal microbiota transplantation (FMT) patients suffering from recurrent CDI and their stool donors, the community modeling method generated a high Enterobacteriaceae abundance cluster with a disproportionate large number of pre-FMT samples. This cluster also was predicted to exhibit reduced secondary bile acid synthesis and elevated aromatic amino acid catabolism. Collectively, these in silico predictions suggest that Enterobacteriaceae may create a gut environment favorable for C. difficile spore germination and/or toxin synthesis.in PLoS Computational Biology on February 22, 2021 02:00 PM.
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by Mark R. Winter, Miri Morgulis, Tsvia Gildor, Andrew R. Cohen, Smadar Ben-Tabou de-Leon
Biomineralization is the process by which organisms use minerals to harden their tissues and provide them with physical support. Biomineralizing cells concentrate the mineral in vesicles that they secret into a dedicated compartment where crystallization occurs. The dynamics of vesicle motion and the molecular mechanisms that control it, are not well understood. Sea urchin larval skeletogenesis provides an excellent platform for investigating the kinetics of mineral-bearing vesicles. Here we used lattice light-sheet microscopy to study the three-dimensional (3D) dynamics of calcium-bearing vesicles in the cells of normal sea urchin embryos and of embryos where skeletogenesis is blocked through the inhibition of Vascular Endothelial Growth Factor Receptor (VEGFR). We developed computational tools for displaying 3D-volumetric movies and for automatically quantifying vesicle dynamics. Our findings imply that calcium vesicles perform an active diffusion motion in both, calcifying (skeletogenic) and non-calcifying (ectodermal) cells of the embryo. The diffusion coefficient and vesicle speed are larger in the mesenchymal skeletogenic cells compared to the epithelial ectodermal cells. These differences are possibly due to the distinct mechanical properties of the two tissues, demonstrated by the enhanced f-actin accumulation and myosinII activity in the ectodermal cells compared to the skeletogenic cells. Vesicle motion is not directed toward the biomineralization compartment, but the vesicles slow down when they approach it, and probably bind for mineral deposition. VEGFR inhibition leads to an increase of vesicle volume but hardly changes vesicle kinetics and doesn’t affect f-actin accumulation and myosinII activity. Thus, calcium vesicles perform an active diffusion motion in the cell of the sea urchin embryo, with diffusion length and speed that inversely correlate with the strength of the actomyosin network. Overall, our studies provide an unprecedented view of calcium vesicle 3D-dynamics and point toward cytoskeleton remodeling as an important effector of the motion of mineral-bearing vesicles.in PLoS Computational Biology on February 22, 2021 02:00 PM.
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by Christof Fehrman, Tyler D. Robbins, C. Daniel Meliza
Neurons exhibit diverse intrinsic dynamics, which govern how they integrate synaptic inputs to produce spikes. Intrinsic dynamics are often plastic during development and learning, but the effects of these changes on stimulus encoding properties are not well known. To examine this relationship, we simulated auditory responses to zebra finch song using a linear-dynamical cascade model, which combines a linear spectrotemporal receptive field with a dynamical, conductance-based neuron model, then used generalized linear models to estimate encoding properties from the resulting spike trains. We focused on the effects of a low-threshold potassium current (KLT) that is present in a subset of cells in the zebra finch caudal mesopallium and is affected by early auditory experience. We found that KLT affects both spike adaptation and the temporal filtering properties of the receptive field. The direction of the effects depended on the temporal modulation tuning of the linear (input) stage of the cascade model, indicating a strongly nonlinear relationship. These results suggest that small changes in intrinsic dynamics in tandem with differences in synaptic connectivity can have dramatic effects on the tuning of auditory neurons.in PLoS Computational Biology on February 22, 2021 02:00 PM.
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by Philipp Mergenthaler, Santosh Hariharan, James M. Pemberton, Corey Lourenco, Linda Z. Penn, David W. Andrews
Phenotypic profiling of large three-dimensional microscopy data sets has not been widely adopted due to the challenges posed by cell segmentation and feature selection. The computational demands of automated processing further limit analysis of hard-to-segment images such as of neurons and organoids. Here we describe a comprehensive shallow-learning framework for automated quantitative phenotyping of three-dimensional (3D) image data; using unsupervised data-driven voxel-based feature learning, which enables computationally facile classification, clustering and advanced data visualization. We demonstrate the analysis potential on complex 3D images by investigating the phenotypic alterations of: neurons in response to apoptosis-inducing treatments and morphogenesis for oncogene-expressing human mammary gland acinar organoids. Our novel implementation of image analysis algorithms called Phindr3D allowed rapid implementation of data-driven voxel-based feature learning into 3D high content analysis (HCA) operations and constitutes a major practical advance as the computed assignments represent the biology while preserving the heterogeneity of the underlying data. Phindr3D is provided as Matlab code and as a stand-alone program (https://github.com/DWALab/Phindr3D).in PLoS Computational Biology on February 22, 2021 02:00 PM.
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by Daniel J. A. Derrick, Kathryn Wolton, Richard A. Currie, Marcus John Tindall
Effective regulation of the sonic hedgehog (Shh) signalling pathway is essential for normal development in a wide variety of species. Correct Shh signalling requires the formation of Shh aggregates on the surface of producing cells. Shh aggregates subsequently diffuse away and are recognised in receiving cells located elsewhere in the developing embryo. Various mechanisms have been postulated regarding how these aggregates form and what their precise role is in the overall signalling process. To understand the role of these mechanisms in the overall signalling process, we formulate and analyse a mathematical model of Shh aggregation using nonlinear ordinary differential equations. We consider Shh aggregate formation to comprise of multimerisation, association with heparan sulfate proteoglycans (HSPG) and binding with lipoproteins. We show that the size distribution of the Shh aggregates formed on the producing cell surface resembles an exponential distribution, a result in agreement with experimental data. A detailed sensitivity analysis of our model reveals that this exponential distribution is robust to parameter changes, and subsequently, also to variations in the processes by which Shh is recruited by HSPGs and lipoproteins. The work demonstrates the time taken for different sized Shh aggregates to form and the important role this likely plays in Shh diffusion.in PLoS Computational Biology on February 22, 2021 02:00 PM.
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by Satyabrata Parida, Hari Bharadwaj, Michael G. Heinz
Significant scientific and translational questions remain in auditory neuroscience surrounding the neural correlates of perception. Relating perceptual and neural data collected from humans can be useful; however, human-based neural data are typically limited to evoked far-field responses, which lack anatomical and physiological specificity. Laboratory-controlled preclinical animal models offer the advantage of comparing single-unit and evoked responses from the same animals. This ability provides opportunities to develop invaluable insight into proper interpretations of evoked responses, which benefits both basic-science studies of neural mechanisms and translational applications, e.g., diagnostic development. However, these comparisons have been limited by a disconnect between the types of spectrotemporal analyses used with single-unit spike trains and evoked responses, which results because these response types are fundamentally different (point-process versus continuous-valued signals) even though the responses themselves are related. Here, we describe a unifying framework to study temporal coding of complex sounds that allows spike-train and evoked-response data to be analyzed and compared using the same advanced signal-processing techniques. The framework uses a set of peristimulus-time histograms computed from single-unit spike trains in response to polarity-alternating stimuli to allow advanced spectral analyses of both slow (envelope) and rapid (temporal fine structure) response components. Demonstrated benefits include: (1) novel spectrally specific temporal-coding measures that are less confounded by distortions due to hair-cell transduction, synaptic rectification, and neural stochasticity compared to previous metrics, e.g., the correlogram peak-height, (2) spectrally specific analyses of spike-train modulation coding (magnitude and phase), which can be directly compared to modern perceptually based models of speech intelligibility (e.g., that depend on modulation filter banks), and (3) superior spectral resolution in analyzing the neural representation of nonstationary sounds, such as speech and music. This unifying framework significantly expands the potential of preclinical animal models to advance our understanding of the physiological correlates of perceptual deficits in real-world listening following sensorineural hearing loss.in PLoS Computational Biology on February 22, 2021 02:00 PM.
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by Boris I. Ratnikov, Piotr Cieplak, Albert G. Remacle, Elise Nguyen, Jeffrey W. Smith
Proteases are an important class of enzymes, whose activity is central to many physiologic and pathologic processes. Detailed knowledge of protease specificity is key to understanding their function. Although many methods have been developed to profile specificities of proteases, few have the diversity and quantitative grasp necessary to fully define specificity of a protease, both in terms of substrate numbers and their catalytic efficiencies. We have developed a concept of “selectome”; the set of substrate amino acid sequences that uniquely represent the specificity of a protease. We applied it to two closely related members of the Matrixin family–MMP-2 and MMP-9 by using substrate phage display coupled with Next Generation Sequencing and information theory-based data analysis. We have also derived a quantitative measure of substrate specificity, which accounts for both the number of substrates and their relative catalytic efficiencies. Using these advances greatly facilitates elucidation of substrate selectivity between closely related members of a protease family. The study also provides insight into the degree to which the catalytic cleft defines substrate recognition, thus providing basis for overcoming two of the major challenges in the field of proteolysis: 1) development of highly selective activity probes for studying proteases with overlapping specificities, and 2) distinguishing targeted proteolysis from bystander proteolytic events.in PLoS Computational Biology on February 22, 2021 02:00 PM.
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in Annals of Neurology on February 22, 2021 12:29 PM.
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in Annals of Neurology on February 22, 2021 12:24 PM.
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in Annals of Neurology on February 22, 2021 11:28 AM.
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Author(s): X. Chen, P. Ciarletta, and H.-H. Dai
Mushroom species display distinctive morphogenetic features. For example, Amanita muscaria and Mycena chlorophos grow in a similar manner, their caps expanding outward quickly and then turning upward. However, only the latter finally develops a central depression in the cap. Here we use a mathematic...
[Phys. Rev. E 103, 022412] Published Mon Feb 22, 2021
in Physical Review E: Biological physics on February 22, 2021 10:00 AM.
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Author(s): Pierre A. Haas and Raymond E. Goldstein
During development, plant and animal tissues undergo large bending deformations that are outside the validity of frequently used thin-shell theories. This work uses asymptotic expansion of a three-dimensional system to develop a theory of incompressible shells that is valid for large bending transformations and improves on the classical thin-shell theories. The theory is applied to the green alga Volvox, which has a spherical embryonic cell sheet that turns itself inside out during development.
[Phys. Rev. E 103, 022411] Published Mon Feb 22, 2021
in Physical Review E: Biological physics on February 22, 2021 10:00 AM.
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Nature Neuroscience, Published online: 22 February 2021; doi:10.1038/s41593-021-00802-y
Gordon et al. use genome-wide unbiased approaches to show that human cerebral cortical organoids, when cultured for many months, start to resemble stages of postnatal brain development, with a timeline that parallels in vivo development.in Nature Neuroscience on February 22, 2021 12:00 AM.
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Nature Neuroscience, Published online: 22 February 2021; doi:10.1038/s41593-021-00798-5
Examination of neural activity reveals that performing a rapid sequence of actions depends not upon fusing those actions into a holistic unit, but upon the ability of motor cortex to swiftly prepare the next action while the present unfolds.in Nature Neuroscience on February 22, 2021 12:00 AM.
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Nature Neuroscience, Published online: 22 February 2021; doi:10.1038/s41593-021-00797-6
Spikes of deep-layer ID2+Nkx2.1+ cortical neurons are anticorrelated with spiking of all principal cells and interneurons, prominently during down states of sleep, and shape the sequential firing of neurons at down–up transitions.in Nature Neuroscience on February 22, 2021 12:00 AM.
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Nature Methods, Published online: 22 February 2021; doi:10.1038/s41592-021-01075-w
The DRACO algorithm deconvolutes coexisting RNA structures from mutational profiling experiments, and can be applied to bacterial regulatory structures and elements from the SARS-CoV-2 genome.in Nature Methods on February 22, 2021 12:00 AM.
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Nature Reviews Neuroscience, Published online: 22 February 2021; doi:10.1038/s41583-021-00442-y
Stressful experience increases erroneous choices in a reward-based learning task by weakening excitatory synapses in the lateral habenula via a reduction in AMPA-receptor-mediated synaptic transmission.in Nature Reviews on February 22, 2021 12:00 AM.
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Nature Communications, Published online: 22 February 2021; doi:10.1038/s41467-021-21706-2
Author Correction: Simulating the ghost: quantum dynamics of the solvated electronin Nature Communications on February 22, 2021 12:00 AM.
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Nature Communications, Published online: 22 February 2021; doi:10.1038/s41467-021-21471-2
Learning-activated engram neurons play a critical role in memory recall but the role of these neurons in offline memory consolidation is unclear. The authors show that sleep-associated reactivation of learning-activated sensory neurons is necessary for memory consolidation.in Nature Communications on February 22, 2021 12:00 AM.
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Nature Communications, Published online: 22 February 2021; doi:10.1038/s41467-021-21455-2
The unprecedented cost of the 2018 eruption in Hawai’i reflects an intersection of disparate physical and social phenomena: widely spaced, highly destructive eruptions, and atypically high population growth. These were linked and the former indirectly drove the latter with unavoidable consequences.in Nature Communications on February 22, 2021 12:00 AM.
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Nature Communications, Published online: 22 February 2021; doi:10.1038/s41467-021-21443-6
The mechanism by which RING E3-anchored ubiquitin chains are formed is not well understood. Here, the authors solve a crystal structure of the RING E3 enzyme TRIM21 trapped in the process of self-anchored chain elongation and provide biochemical and cellular insights into the mechanism of ubiquitin conjugation.in Nature Communications on February 22, 2021 12:00 AM.
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Nature Communications, Published online: 22 February 2021; doi:10.1038/s41467-021-21440-9
Here, the authors report an active all-dielectric metasurface platform based on phase change materials, combining phase tuning in the full 2π range, and demonstrate aberration-free and multi-depth imaging with a non-mechanical tunable metalens.in Nature Communications on February 22, 2021 12:00 AM.
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Nature Communications, Published online: 22 February 2021; doi:10.1038/s41467-021-21410-1
Programmed death-ligand 1 (PD-L1) is involved in the inhibition of antigen specific T cells via ligation of programmed death 1 (PD-1). Here, the authors show checkpoint inhibition by use of small molecule inhibition of PD-L1 which in a humanised mouse model was shown to restore T cell responses and reduced tumour burden.in Nature Communications on February 22, 2021 12:00 AM.
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Nature Communications, Published online: 22 February 2021; doi:10.1038/s41467-021-21400-3
The N cycle involves complex, microbially-mediated shuttling between ammonium, nitrite and nitrate, with climatically important greenhouse gas byproducts. Here the authors use isotope labeling experiments in river sediments and find a cryptic new step in the N cycle between nitrification and the removal of fixed N through N2 gas production.in Nature Communications on February 22, 2021 12:00 AM.
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Nature Communications, Published online: 22 February 2021; doi:10.1038/s41467-021-21254-9
The Genomic Data Commons repository contains genomic, epigenomic, proteomic and clinical data from the TCGA and TARGET datasets. Here, the authors describe the analysis methods for how these divergent datasets were integrated together.in Nature Communications on February 22, 2021 12:00 AM.
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Nature Communications, Published online: 22 February 2021; doi:10.1038/s41467-021-21216-1
Reply to ‘Oxic methanogenesis is only a minor source of lake-wide diffusive CH4 emissions from lakes’in Nature Communications on February 22, 2021 12:00 AM.
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Connective Field (CF) modeling estimates the local spatial integration between signals in distinct cortical visual field areas. As we have shown previously using 7T data, CF can reveal the visuotopic organization of visual cortical areas even when applied to BOLD activity recorded in the absence of external stimulation. This indicates that CF modeling can be used to evaluate cortical processing in participants in which the visual input may be compromised. Furthermore, by using Bayesian CF modeling it is possible to estimate the co-variability of the parameter estimates and therefore, apply CF modeling to single cases. However, no previous studies evaluated the (Bayesian) CF model using 3T resting-state fMRI data. This is important since 3T scanners are much more abundant and more often used in clinical research compared to 7T scanners. Therefore in this study, we investigate whether it is possible to obtain meaningful CF estimates from 3T resting state (RS) fMRI data. To do so, we applied the standard and Bayesian CF modeling approaches on two RS scans, which were separated by the acquisition of visual field mapping data in 12 healthy participants. Our results show good agreement between RS- and visual field (VF)- based maps using either the standard or Bayesian CF approach. In addition to quantify the uncertainty associated with each estimate in both RS and VF data, we applied our Bayesian CF framework to provide the underlying marginal distribution of the CF parameters. Finally, we show how an additional CF parameter, beta, can be used as a data-driven threshold on the RS data to further improve CF estimates. We conclude that Bayesian CF modeling can characterize local functional connectivity between visual cortical areas from RS data at 3T. Moreover, observations obtained using 3T scanners were qualitatively similar to those reported for 7T. In particular, we expect the ability to assess parameter uncertainty in individual participants will be important for future clinical studies.
in Frontiers in Neuroscience: Brain Imaging Methods on February 22, 2021 12:00 AM.
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Alpha-neurofeedback (α-NFB) is a novel therapy which trains individuals to volitionally increase their alpha power to improve pain. Learning during NFB is commonly measured using static parameters such as mean alpha power. Considering the biphasic nature of alpha rhythm (high and low alpha), dynamic parameters describing the time spent by individuals in high alpha state and the pattern of transitioning between states might be more useful. Here, we quantify the changes during α-NFB for chronic pain in terms of dynamic changes in alpha states.
MethodsFour chronic pain and four healthy participants received five NFB sessions designed to increase frontal alpha power. Changes in pain resilience were measured using visual analogue scale (VAS) during repeated cold-pressor tests (CPT). Changes in alpha state static and dynamic parameters such as fractional occupancy (time in high alpha state), dwell time (length of high alpha state) and transition probability (probability of moving from low to high alpha state) were analyzed using Friedman’s Test and correlated with changes in pain scores using Pearson’s correlation.
ResultsThere was no significant change in mean frontal alpha power during NFB. There was a trend of an increase in fractional occupancy, mean dwell duration and transition probability of high alpha state over the five sessions in chronic pain patients only. Significant correlations were observed between change in pain scores and fractional occupancy (r = −0.45, p = 0.03), mean dwell time (r = -0.48, p = 0.04) and transition probability from a low to high state (r = -0.47, p = 0.03) in chronic pain patients but not in healthy participants.
ConclusionThere is a differential effect between patients and healthy participants in terms of correlation between change in pain scores and alpha state parameters. Parameters providing a more precise description of the alpha power dynamics than the mean may help understand the therapeutic effect of neurofeedback on chronic pain.
in Frontiers in Neuroscience: Neural Technology on February 22, 2021 12:00 AM.
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In general, only one diffusion model would be applied to whole field-of-view voxels in the intravoxel incoherent motion-magnetic resonance imaging (IVIM-MRI) study. However, the choice of the applied diffusion model can significantly influence the estimated diffusion parameters. The quality of the diffusion analysis can influence the reliability of the perfusion analysis. This study proposed an optimal model mapping method to improve the reliability of the perfusion parameter estimation in the IVIM study. Six healthy volunteers (five males and one female; average age of 38.3 ± 7.5 years). Volunteers were examined using a 3.0 Tesla scanner. IVIM-MRI of the brain was applied at 17 b-values ranging from 0 to 2,500 s/mm2. The Gaussian model, the Kurtosis model, and the Gamma model were found to be optimal for the CSF, white matter (WM), and gray matter (GM), respectively. In the mean perfusion fraction (fp) analysis, the GM/WM ratios were 1.16 (Gaussian model), 1.80 (Kurtosis model), 1.94 (Gamma model), and 1.54 (Optimal model mapping); in the mean pseudo diffusion coefficient (D*) analysis, the GM/WM ratios were 1.18 (Gaussian model), 1.19 (Kurtosis model), 1.56 (Gamma model), and 1.24 (Optimal model mapping). With the optimal model mapping method, the estimated fp and D* were reliable compared with the conventional methods. In addition, the optimal model maps, the associated products of this method, may provide additional information for clinical diagnosis.
in Frontiers in Human Neuroscience on February 22, 2021 12:00 AM.
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Background: Cognitive impairment is one of the core symptoms of schizophrenia, which is considered to be significantly correlated to prognosis. In recent years, many studies have suggested that metabolic disorders could be related to a higher risk of cognitive defects in a general setting. However, there has been limited evidence on the association between metabolism and cognitive function in patients with early-stage schizophrenia.
Methods: In this study, we recruited 172 patients with early-stage schizophrenia. Relevant metabolic parameters were examined and cognitive function was evaluated by using the MATRICS Consensus Cognitive Battery (MCCB) to investigate the relationship between metabolic disorder and cognitive impairment.
Results: Generally, the prevalence of cognitive impairment among patients in our study was 84.7% (144/170), which was much higher than that in the general population. Compared with the general Chinese setting, the study population presented a higher proportion of metabolic disturbance. Patients who had metabolic disturbance showed no significant differences on cognitive function compared with the other patients. Correlation analysis showed that metabolic status was significantly correlated with cognitive function as assessed by the cognitive domain scores (p < 0.05), while such association was not found in further multiple regression analysis.
Conclusions: Therefore, there may be no association between metabolic disorder and cognitive impairment in patients with early-stage schizophrenia.
Trial Registration: Clinicaltrials.gov, NCT03451734. Registered March 2, 2018 (retrospectively registered).
in Frontiers in Human Neuroscience on February 22, 2021 12:00 AM.
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Human not only can effortlessly recognize objects, but also characterize object categories into semantic concepts with a nested hierarchical structure. One dominant view is that top-down conceptual guidance is necessary to form such hierarchy. Here we challenged this idea by examining whether deep convolutional neural networks (DCNNs) could learn relations among objects purely based on bottom-up perceptual experience of objects through training for object categorization. Specifically, we explored representational similarity among objects in a typical DCNN (e.g., AlexNet), and found that representations of object categories were organized in a hierarchical fashion, suggesting that the relatedness among objects emerged automatically when learning to recognize them. Critically, the emerged relatedness of objects in the DCNN was highly similar to the WordNet in human, implying that top-down conceptual guidance may not be a prerequisite for human learning the relatedness among objects. In addition, the developmental trajectory of the relatedness among objects during training revealed that the hierarchical structure was constructed in a coarse-to-fine fashion, and evolved into maturity before the establishment of object recognition ability. Finally, the fineness of the relatedness was greatly shaped by the demand of tasks that the DCNN performed, as the higher superordinate level of object classification was, the coarser the hierarchical structure of the relatedness emerged. Taken together, our study provides the first empirical evidence that semantic relatedness of objects emerged as a by-product of object recognition in DCNNs, implying that human may acquire semantic knowledge on objects without explicit top-down conceptual guidance.
in Frontiers in Computational Neuroscience on February 22, 2021 12:00 AM.
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The transient receptor potential vanilloid 1 (TRPV1) is a non-selective ligand-gated cation channel involved in synaptic transmission, plasticity, and brain pathology. In the hippocampal dentate gyrus, TRPV1 localizes to dendritic spines and dendrites postsynaptic to excitatory synapses in the molecular layer (ML). At these same synapses, the cannabinoid CB1 receptor (CB1R) activated by exogenous and endogenous cannabinoids localizes to the presynaptic terminals. Hence, as both receptors are activated by endogenous anandamide, co-localize, and mediate long-term depression of the excitatory synaptic transmission at the medial perforant path (MPP) excitatory synapses though by different mechanisms, it is plausible that they might be exerting a reciprocal influence from their opposite synaptic sites. In this anatomical scenario, we tested whether the absence of TRPV1 affects the endocannabinoid system. The results obtained using biochemical techniques and immunoelectron microscopy in a mouse with the genetic deletion of TRPV1 show that the expression and localization of components of the endocannabinoid system, included CB1R, change upon the constitutive absence of TRPV1. Thus, the expression of fatty acid amide hydrolase (FAAH) and monoacylglycerol lipase (MAGL) drastically increased in TRPV1−/− whole homogenates. Furthermore, CB1R and MAGL decreased and the cannabinoid receptor interacting protein 1a (CRIP1a) increased in TRPV1−/− synaptosomes. Also, CB1R positive excitatory terminals increased, the number of excitatory terminals decreased, and CB1R particles dropped significantly in inhibitory terminals in the dentate ML of TRPV1−/− mice. In the outer 2/3 ML of the TRPV1−/− mutants, the proportion of CB1R particles decreased in dendrites, and increased in excitatory terminals and astrocytes. In the inner 1/3 ML, the proportion of labeling increased in excitatory terminals, neuronal mitochondria, and dendrites. Altogether, these observations indicate the existence of compensatory changes in the endocannabinoid system upon TRPV1 removal, and endorse the importance of the potential functional adaptations derived from the lack of TRPV1 in the mouse brain.
in Frontiers in Neuroanatomy on February 22, 2021 12:00 AM.
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Bacopa monnieri (BM) is a herbal supplement that increases signaling molecules implicated in synaptogenesis. Combined with cognitive stimulation, it may be a viable supplement to enhance long-term potentiation (LTP) and improve cognitive health in older adults. This randomized, double-blind, placebo-controlled trial asked 28 healthy adults aged over 55 years to complete cognitive training (CT) 3 hours weekly for 12 weeks. Fifteen consumed a standardized extract of BM and 13 consumed a placebo daily. Cognitive tasks, life-satisfaction, memory complaints and mood were assessed, and bloods analyzed for serum brain-derived neurotrophic factor (BDNF) before and after 12-weeks of the intervention. Diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) in gray (GM) and white matter (WM) were also analyzed. Results demonstrated slower reaction time in an image discrimination task in the BM group and faster reaction time in a spatial working memory task (SWM-O RT) in the placebo group. Mean accuracy was higher in the BM group for these tasks, suggesting a change in the speed accuracy trade-off. Exploratory neuroimaging analysis showed increased WM mean diffusivity (MD) and GM dispersion of neurites (orientation dispersion index, ODI) and decreased WM fractional anisotropy (FA) and GM neurite density (ND) in the BM group. No other outcomes reached statistical significance. An increase in ODI with a decrease in MD and ND in the BM group may indicate an increase in network complexity (through higher dendritic branching) accompanied by dendritic pruning to enhance network efficiency. These neuroimaging outcomes conflict with the behavioral results, which showed poorer reaction time in the BM group. Given the exploratory outcomes and inconsistent findings between the behavioral and neuroimaging data, a larger study is needed to confirm the synaptogenic mechanisms of BM.
in Frontiers in Ageing Neuroscience on February 22, 2021 12:00 AM.
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Introduction: Functional imaging studies have demonstrated the recruitment of additional neural resources as a possible mechanism to compensate for age and Alzheimer’s disease (AD)-related cerebral pathology, the efficacy of which is potentially modulated by underlying structural network connectivity. Additionally, structural network efficiency (SNE) is associated with intelligence across the lifespan, which is a known factor for resilience to cognitive decline. We hypothesized that SNE may be a surrogate of the physiological basis of resilience to cognitive decline in elderly persons without dementia and with age- and AD-related cerebral pathology.Methods: We included 85 cognitively normal elderly subjects or mild cognitive impairment (MCI) patients submitted to baseline diffusion imaging, liquor specimens, amyloid-PET and longitudinal cognitive assessments. SNE was calculated from baseline MRI scans using fiber tractography and graph theory. Mixed linear effects models were estimated to investigate the association of higher resilience to cognitive decline with higher SNE and the modulation of this association by increased cerebral amyloid, liquor tau or WMHV. Results: For the majority of cognitive outcome measures, higher SNE was associated with higher resilience to cognitive decline (p-values: 0.011–0.039). Additionally, subjects with higher SNE showed more resilience to cognitive decline at higher cerebral amyloid burden (p-values: <0.001–0.036) and lower tau levels (p-values: 0.002–0.015).Conclusion: These results suggest that SNE to some extent may quantify the physiological basis of resilience to cognitive decline most effective at the earliest stages of AD, namely at increased amyloid burden and before increased tauopathy.
in Frontiers in Ageing Neuroscience on February 22, 2021 12:00 AM.
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Resilience, the ability to overcome adversity and face stressful demands and experiences, has been strongly associated with successful aging, a low risk of diseases and high mental and physical functioning. This relationship could be based on adaptive coping behaviors, but more research is needed to gain knowledge about the strategies employed to confront social stress. Thus, we aimed to investigate the role of the use of active or passive coping strategies by resilient people in dealing with stressful situations. For this purpose, we measured resilience, coping strategies, and perceived stress in 66 healthy older adults (31 men and 35 women) between 56 and 75 years old who were exposed to stress (Trier Social Stress Test, TSST) or a control situation. The stress response was analyzed at endocrine (cortisol) and psychological (anxiety) levels. In the stress condition, moderated mediation analysis showed a conditional indirect effect of resilience on cortisol reactivity through active coping. However, passive coping strategies did not mediate the resilience-cortisol relationship. In addition, neither active nor passive coping mediated the relationship between resilience and the anxiety response. These results suggest that resilience is associated with active coping strategies, which in turn could explain, at least in part, individual differences in the cortisol response to a psychosocial laboratory stressor. These factors may prevent the development of stress-related pathologies associated with aging and facilitate healthy and satisfactory aging.
in Frontiers in Ageing Neuroscience on February 22, 2021 12:00 AM.
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Objective: To investigate variation in the characteristics of regional cerebral blood flow (rCBF), brain activity, and intrinsic functional connectivity (FC) across the Alzheimer's disease spectrum (ADS).
Methods: The study recruited 20 individuals in each of the following categories: Alzheimer's disease (AD), mild cognitive impairment (MCI), subjective cognitive decline (SCD), and healthy control (HC). All participants completed the 3.0T resting-state functional MRI (rs-fMRI) and arterial spin labeling scans in addition to neuropsychological tests. Additionally, the normalized CBF, regional homogeneity (ReHo), and amplitude of low-frequency fluctuation (ALFF) of individual subjects were compared in the ADS. Moreover, the changes in intrinsic FC were investigated across the ADS using the abnormal rCBF regions as seeds and behavioral correlations. Finally, a support-vector classifier model of machine learning was used to distinguish individuals with ADS from HC.
Results: Compared to the HC subjects, patients with AD showed the poorest level of rCBF in the left precuneus (LPCUN) and right middle frontal gyrus (RMFG) among all participants. In addition, there was a significant decrease in the ALFF in the bilateral posterior cingulate cortex (PCC) and ReHo in the right PCC. Moreover, RMFG- and LPCUN-based FC analysis revealed that the altered FCs were primarily located in the posterior brain regions. Finally, a combination of altered rCBF, ALFF, and ReHo in posterior cingulate cortex/precuneus (PCC/PCUN) showed a better ability to differentiate ADS from HC, AD from SCD and MCI, but not MCI from SCD.
Conclusions: The study demonstrated the significance of an altered rCBF and brain activity in the early stages of ADS. These findings, therefore, present a potential diagnostic neuroimaging-based biomarker in ADS. Additionally, the study provides a better understanding of the pathophysiology of AD.
in Frontiers in Ageing Neuroscience on February 22, 2021 12:00 AM.
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Alzheimer's disease (AD) is the most common form of dementia, characterized by a complex etiology that makes therapeutic strategies still not effective. A true understanding of key pathological mechanisms and new biomarkers are needed, to identify alternative disease-modifying therapies counteracting the disease progression. Iron is an essential element for brain metabolism and its imbalance is implicated in neurodegeneration, due to its potential neurotoxic effect. However, the role of iron in different stages of dementia is not clearly established. This study aimed to investigate the potential impact of iron both in cerebrospinal fluid (CSF) and in serum to improve early diagnosis and the related therapeutic possibility. In addition to standard clinical method to detect iron in serum, a precise quantification of total iron in CSF was performed using graphite-furnace atomic absorption spectrometry in patients affected by AD, mild cognitive impairment, frontotemporal dementia, and non-demented neurological controls. The application of machine learning techniques, such as clustering analysis and multiclassification algorithms, showed a new potential stratification of patients exploiting iron-related data. The results support the involvement of iron dysregulation and its potential interaction with biomarkers (Tau protein and Amyloid-beta) in the pathophysiology and progression of dementia.
in Frontiers in Ageing Neuroscience on February 22, 2021 12:00 AM.
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in eLife on February 22, 2021 12:00 AM.
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in eLife on February 22, 2021 12:00 AM.
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Publication date: Available online 21 February 2021
Source: Neural Networks
Author(s): Alex Bihlo
in Neural Networks on February 21, 2021 07:00 PM.
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in Journal of Neuroscience Research on February 21, 2021 03:24 AM.
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in Journal of Neuroscience Research on February 21, 2021 03:18 AM.
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in Behavioural and Brain Functions on February 21, 2021 12:00 AM.
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in Journal of Neuroscience Research on February 20, 2021 09:41 AM.
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in Journal of Neuroscience Research on February 20, 2021 08:57 AM.
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in Journal of Neuroscience Research on February 20, 2021 08:57 AM.
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in Journal of Neuroscience Research on February 20, 2021 08:57 AM.
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in Journal of Neuroscience Research on February 20, 2021 08:57 AM.
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in Journal of Neuroscience Research on February 20, 2021 08:57 AM.
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in Journal of Neuroscience Research on February 20, 2021 08:57 AM.
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in Journal of Neuroscience Research on February 20, 2021 08:57 AM.
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in Journal of Neuroscience Research on February 20, 2021 08:57 AM.
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in Journal of Neuroscience Research on February 20, 2021 08:57 AM.
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in Journal of Neuroscience Research on February 20, 2021 08:57 AM.
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in Journal of Neuroscience Research on February 20, 2021 08:57 AM.
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in Journal of Neuroscience Research on February 20, 2021 08:57 AM.
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in Journal of Neuroscience Research on February 20, 2021 08:57 AM.
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in Journal of Neuroscience Research on February 20, 2021 08:57 AM.
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in Journal of Comparative Neurology on February 20, 2021 08:50 AM.
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in Hippocampus on February 19, 2021 03:15 PM.
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in Journal of Neuroscience Research on February 19, 2021 03:07 PM.
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in Journal of Neuroscience Research on February 19, 2021 02:45 PM.
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by Sitong Wang, Ting Ye, Guansheng Li, Xuejiao Zhang, Huixin Shi
In tumor metastasis, the margination and adhesion of tumor cells are two critical and closely related steps, which may determine the destination where the tumor cells extravasate to. We performed a direct three-dimensional simulation on the behaviors of the tumor cells in a real microvascular network, by a hybrid method of the smoothed dissipative particle dynamics and immersed boundary method (SDPD-IBM). The tumor cells are found to adhere at the microvascular bifurcations more frequently, and there is a positive correlation between the adhesion of the tumor cells and the wall-directed force from the surrounding red blood cells (RBCs). The larger the wall-directed force is, the closer the tumor cells are marginated towards the wall, and the higher the probability of adhesion behavior happen is. A relatively low or high hematocrit can help to prevent the adhesion of tumor cells, and similarly, increasing the shear rate of blood flow can serve the same purpose. These results suggest that the tumor cells may be more likely to extravasate at the microvascular bifurcations if the blood flow is slow and the hematocrit is moderate.in PLoS Computational Biology on February 19, 2021 02:00 PM.
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by Qixin He, Mercedes Pascual
In malaria and several other important infectious diseases, high prevalence occurs concomitantly with incomplete immunity. This apparent paradox poses major challenges to malaria elimination in highly endemic regions, where asymptomatic Plasmodium falciparum infections are present across all age classes creating a large reservoir that maintains transmission. This reservoir is in turn enabled by extreme antigenic diversity of the parasite and turnover of new variants. We present here the concept of a threshold in local pathogen diversification that defines a sharp transition in transmission intensity below which new antigen-encoding genes generated by either recombination or migration cannot establish. Transmission still occurs below this threshold, but diversity of these genes can neither accumulate nor recover from interventions that further reduce it. An analytical expectation for this threshold is derived and compared to numerical results from a stochastic individual-based model of malaria transmission that incorporates the major antigen-encoding multigene family known as var. This threshold corresponds to an “innovation” number we call Rdiv; it is different from, and complementary to, the one defined by the classic basic reproductive number of infectious diseases, R0, which does not easily apply under large and dynamic strain diversity. This new threshold concept can be exploited for effective malaria control and applied more broadly to other pathogens with large multilocus antigenic diversity.in PLoS Computational Biology on February 19, 2021 02:00 PM.
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by Hana Susak, Laura Serra-Saurina, German Demidov, Raquel Rabionet, Laura Domènech, Mattia Bosio, Francesc Muyas, Xavier Estivill, Geòrgia Escaramís, Stephan Ossowski
Rare variants are thought to play an important role in the etiology of complex diseases and may explain a significant fraction of the missing heritability in genetic disease studies. Next-generation sequencing facilitates the association of rare variants in coding or regulatory regions with complex diseases in large cohorts at genome-wide scale. However, rare variant association studies (RVAS) still lack power when cohorts are small to medium-sized and if genetic variation explains a small fraction of phenotypic variance. Here we present a novel Bayesian rare variant Association Test using Integrated Nested Laplace Approximation (BATI). Unlike existing RVAS tests, BATI allows integration of individual or variant-specific features as covariates, while efficiently performing inference based on full model estimation. We demonstrate that BATI outperforms established RVAS methods on realistic, semi-synthetic whole-exome sequencing cohorts, especially when using meaningful biological context, such as functional annotation. We show that BATI achieves power above 70% in scenarios in which competing tests fail to identify risk genes, e.g. when risk variants in sum explain less than 0.5% of phenotypic variance. We have integrated BATI, together with five existing RVAS tests in the ‘Rare Variant Genome Wide Association Study’ (rvGWAS) framework for data analyzed by whole-exome or whole genome sequencing. rvGWAS supports rare variant association for genes or any other biological unit such as promoters, while allowing the analysis of essential functionalities like quality control or filtering. Applying rvGWAS to a Chronic Lymphocytic Leukemia study we identified eight candidate predisposition genes, including EHMT2 and COPS7A.in PLoS Computational Biology on February 19, 2021 02:00 PM.
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by Katharine Z. Coyte, Chitong Rao, Seth Rakoff-Nahoum, Kevin R. Foster
Humans and many other hosts establish a diverse community of beneficial microbes anew each generation. The order and identity of incoming symbionts is critical for health, but what determines the success of the assembly process remains poorly understood. Here we develop ecological theory to identify factors important for microbial community assembly. Our method maps out all feasible pathways for the assembly of a given microbiome—with analogies to the mutational maps underlying fitness landscapes in evolutionary biology. Building these “assembly maps” reveals a tradeoff at the heart of the assembly process. Ecological dependencies between members of the microbiota make assembly predictable—and can provide metabolic benefits to the host—but these dependencies may also create barriers to assembly. This effect occurs because interdependent species can fail to establish when each relies on the other to colonize first. We support our predictions with published data from the assembly of the preterm infant microbiota, where we find that ecological dependence is associated with a predictable order of arrival. Our models also suggest that hosts can overcome barriers to assembly via mechanisms that either promote the uptake of multiple symbiont species in one step or feed early colonizers. This predicted importance of host feeding is supported by published data on the impacts of breast milk in the assembly of the human microbiome. We conclude that both microbe–microbe and host–microbe interactions are important for the trajectory of microbiome assembly.in PLoS Biology on February 19, 2021 02:00 PM.
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in Journal of Neuroscience Research on February 19, 2021 10:26 AM.
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Author(s): Luis Abrego, Susanna Gordleeva, Oleg Kanakov, Mikhail Krivonosov, and Alexey Zaikin
There is growing evidence that suggests the importance of astrocytes as elements for neural information processing through the modulation of synaptic transmission. A key aspect of this problem is understanding the impact of astrocytes in the information carried by compound events in neurons across t...
[Phys. Rev. E 103, 022410] Published Fri Feb 19, 2021
in Physical Review E: Biological physics on February 19, 2021 10:00 AM.
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Author(s): Hongwei Yin, Shuqin Liu, and Xiaoqing Wen
Gene expression is a complex biochemical process involving multiple reaction steps, creating molecular memory because the probability of waiting time between consecutive reaction steps no longer follows exponential distributions. What effect the molecular memory has on metastable states in gene expr...
[Phys. Rev. E 103, 022409] Published Fri Feb 19, 2021
in Physical Review E: Biological physics on February 19, 2021 10:00 AM.
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in Journal of Neuroscience Research on February 19, 2021 05:03 AM.
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in Annals of Neurology on February 19, 2021 02:33 AM.
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Nature Reviews Neuroscience, Published online: 19 February 2021; doi:10.1038/s41583-021-00432-0
Inactivation of the gene encoding fragile X mental retardation protein (FMRP) drives the impairments in brain development and function that underlie fragile X syndrome. Richter and Zhao illustrate how innovative genetic and molecular biology tools have enhanced our understanding of both FMRP’s function and the causes of fragile X syndrome pathophysiology.in Nature Reviews on February 19, 2021 12:00 AM.
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Nature Photonics, Published online: 19 February 2021; doi:10.1038/s41566-021-00768-0
Radiation pressure exerted by light was a lifelong passion for Arthur Ashkin. He foresaw that light pressure could do useful work and invented the optical tweezers that can trap microscopic objects, from small ‘living things’ down to individual atoms.in Nature Photomics on February 19, 2021 12:00 AM.
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in The Journal of Mathematical Neuroscience on February 19, 2021 12:00 AM.
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Auxiliary α2δ subunits of voltage-gated calcium channels modulate channel trafficking, current properties, and synapse formation. Three of the four isoforms (α2δ-1, α2δ-2, and α2δ-3) are abundantly expressed in the brain; however, of the available knockout models, only α2δ-2 knockout or mutant mice display an obvious abnormal neurological phenotype. Thus, we hypothesize that the neuronal α2δ isoforms may have partially specific as well as redundant functions. To address this, we generated three distinct α2δ double knockout mouse models by crossbreeding single knockout (α2δ-1 and -3) or mutant (α2δ-2/ducky) mice. Here, we provide a first phenotypic description and brain structure analysis. We found that genotypic distribution of neonatal litters in distinct α2δ-1/-2, α2δ-1/-3, and α2δ-2/-3 breeding combinations did not conform to Mendel’s law, suggesting premature lethality of single and double knockout mice. Notably, high occurrences of infant mortality correlated with the absence of specific α2δ isoforms (α2Δ-2 > α2δ-1 > α2δ-3), and was particularly observed in cages with behaviorally abnormal parenting animals of α2δ-2/-3 cross-breedings. Juvenile α2δ-1/-2 and α2δ-2/-3 double knockout mice displayed a waddling gate similar to ducky mice. However, in contrast to ducky and α2δ-1/-3 double knockout animals, α2δ-1/-2 and α2δ-2/-3 double knockout mice showed a more severe disease progression and highly impaired development. The observed phenotypes within the individual mouse lines may be linked to differences in the volume of specific brain regions. Reduced cortical volume in ducky mice, for example, was associated with a progressively decreased space between neurons, suggesting a reduction of total synaptic connections. Taken together, our findings show that α2δ subunits differentially regulate premature survival, postnatal growth, brain development, and behavior, suggesting specific neuronal functions in health and disease.
in Frontiers in Synaptic Neuroscience on February 19, 2021 12:00 AM.
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For human protection, the internal electric field is used as a dosimetric quantity for electromagnetic fields lower than 5–10 MHz. According to international standards, in this frequency range, electrostimulation is the main adverse effect against which protection is needed. One of the topics to be investigated is the quantification of the internal electric field threshold levels of perception and pain. Pain has been reported as a side effect during transcranial magnetic stimulation (TMS), especially during stimulation of the Broca’s (speech) area of the brain. In this study, we designed an experiment to conduct a dosimetry analysis to quantify the internal electric field corresponding to perception and pain thresholds when targeting the Broca’s and M1 areas from magnetic stimulator exposure. Dosimetry analysis was conducted using a multi-scale analysis in an individualized head model to investigate electrostimulation in an axonal model. The main finding is that the stimulation on the primary motor cortex has higher perception and pain thresholds when compared to Broca’s area. Also, TMS-induced electric field applied to Broca’s area exhibited dependence on the coil orientation at lower electric field threshold which was found to be related to the location and thickness of pain fibers. The derived dosimetry quantities provide a scientific rationale for the development of human protection guidelines and the estimation of possible side effects of magnetic stimulation in clinical applications.
in Frontiers in Neuroscience: Neural Technology on February 19, 2021 12:00 AM.
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The frequently discovered incidental findings (IFs) from imaging observations are increasing. The IFs show the potential clues of structural abnormalities underlying cognitive decline in elders. Detecting brain IFs and their relationship with cognitive and behavioral functions helps provide the information for clinical strategies.
MethodsFive hundred and seventy-nine participants were recruited in the Shanghai Changfeng Study. All participants performed the demographic, biochemical, and cognitive functions and gait speed assessment and underwent the high-resolution multimodal magnetic resonance imaging scans. We calculated the detection rate of brain IFs. The association between cardiovascular risk factors and IFs and the associations between IFs and cognitive and motor functions were assessed using regression models. The relationships among gray matter volume, cognitive function, and gait speed were assessed with/without adjusting the IFs to evaluate the effects of potential IFs confounders.
ResultsIFs were found in a total of 578 subjects with a detection rate of 99.8%. Age and blood pressure were the most significant cardiovascular risk factors correlated with IFs. IFs were found to be negatively associated with Montreal Cognitive Assessment, Mini-Mental State Examination, and gait speed. The gray matter volume was found to be positively correlated with the cognitive function without adjusting the white matter hyperintensity but not if adjusted.
ConclusionIFs are commonly found in the elderly population and related to brain functions. The adequate intervention of IFs related cardiovascular risk factors that may slow down the progression of brain function decline. We also suggest that IFs should be considered as confounding factors that may affect cognitive issues on the structural neuroimaging researches in aging or diseases.
in Frontiers in Neuroscience: Neurodegeneration on February 19, 2021 12:00 AM.
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A common task in brain image analysis includes diagnosis of a certain medical condition wherein groups of healthy controls and diseased subjects are analyzed and compared. On the other hand, for two groups of healthy participants with different proficiency in a certain skill, a distinctive analysis of the brain function remains a challenging problem. In this study, we develop new computational tools to explore the functional and anatomical differences that could exist between the brain of healthy individuals identified on the basis of different levels of task experience/proficiency. Toward this end, we look at a dataset of amateur and professional chess players, where we utilize resting-state functional magnetic resonance images to generate functional connectivity (FC) information. In addition, we utilize T1-weighted magnetic resonance imaging to estimate morphometric connectivity (MC) information. We combine functional and anatomical features into a new connectivity matrix, which we term as the functional morphometric similarity connectome (FMSC). Since, both the FC and MC information is susceptible to redundancy, the size of this information is reduced using statistical feature selection. We employ off-the-shelf machine learning classifier, support vector machine, for both single- and multi-modality classifications. From our experiments, we establish that the saliency and ventral attention network of the brain is functionally and anatomically different between two groups of healthy subjects (chess players). We argue that, since chess involves many aspects of higher order cognition such as systematic thinking and spatial reasoning and the identified network is task-positive to cognition tasks requiring a response, our results are valid and supporting the feasibility of the proposed computational pipeline. Moreover, we quantitatively validate an existing neuroscience hypothesis that learning a certain skill could cause a change in the brain (functional connectivity and anatomy) and this can be tested via our novel FMSC algorithm.
in Frontiers in Neuroscience: Brain Imaging Methods on February 19, 2021 12:00 AM.
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An efficient method to identify whether mild cognitive impairment (MCI) has progressed to Alzheimer’s disease (AD) will be beneficial to patient care. Previous studies have shown that magnetic resonance imaging (MRI) has enabled the assessment of AD progression based on imaging findings. The present work aimed to establish an algorithm based on three features, namely, volume, surface area, and surface curvature within the hippocampal subfields, to model variations, including atrophy and structural changes to the cortical surface. In this study, a new biomarker, the ratio of principal curvatures (RPC), was proposed to characterize the folding patterns of the cortical gyrus and sulcus. Along with volumes and surface areas, these morphological features associated with the hippocampal subfields were assessed in terms of their sensitivity to the changes in cognitive capacity by two different feature selection methods. Either the extracted features were statistically significantly different, or the features were selected through a random forest model. The identified subfields and their structural indices that are sensitive to the changes characteristic of the progression from MCI to AD were further assessed with a multilayer perceptron classifier to help facilitate the diagnosis. The accuracy of the classification based on the proposed method to distinguish whether a MCI patient enters the AD stage amounted to 79.95%, solely using the information from the features selected by a logical feature selection method.
in Frontiers in Neuroscience: Brain Imaging Methods on February 19, 2021 12:00 AM.
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Many articles have used voice analysis to detect Parkinson's disease (PD), but few have focused on the early stages of the disease and the gender effect. In this article, we have adapted the latest speaker recognition system, called x-vectors, in order to detect PD at an early stage using voice analysis. X-vectors are embeddings extracted from Deep Neural Networks (DNNs), which provide robust speaker representations and improve speaker recognition when large amounts of training data are used. Our goal was to assess whether, in the context of early PD detection, this technique would outperform the more standard classifier MFCC-GMM (Mel-Frequency Cepstral Coefficients—Gaussian Mixture Model) and, if so, under which conditions. We recorded 221 French speakers (recently diagnosed PD subjects and healthy controls) with a high-quality microphone and via the telephone network. Men and women were analyzed separately in order to have more precise models and to assess a possible gender effect. Several experimental and methodological aspects were tested in order to analyze their impacts on classification performance. We assessed the impact of the audio segment durations, data augmentation, type of dataset used for the neural network training, kind of speech tasks, and back-end analyses. X-vectors technique provided better classification performances than MFCC-GMM for the text-independent tasks, and seemed to be particularly suited for the early detection of PD in women (7–15% improvement). This result was observed for both recording types (high-quality microphone and telephone).
in Frontiers in Neuroinformatics on February 19, 2021 12:00 AM.
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Emotion recognition plays an important role in intelligent human–computer interaction, but the related research still faces the problems of low accuracy and subject dependence. In this paper, an open-source software toolbox called MindLink-Eumpy is developed to recognize emotions by integrating electroencephalogram (EEG) and facial expression information. MindLink-Eumpy first applies a series of tools to automatically obtain physiological data from subjects and then analyzes the obtained facial expression data and EEG data, respectively, and finally fuses the two different signals at a decision level. In the detection of facial expressions, the algorithm used by MindLink-Eumpy is a multitask convolutional neural network (CNN) based on transfer learning technique. In the detection of EEG, MindLink-Eumpy provides two algorithms, including a subject-dependent model based on support vector machine (SVM) and a subject-independent model based on long short-term memory network (LSTM). In the decision-level fusion, weight enumerator and AdaBoost technique are applied to combine the predictions of SVM and CNN. We conducted two offline experiments on the Database for Emotion Analysis Using Physiological Signals (DEAP) dataset and the Multimodal Database for Affect Recognition and Implicit Tagging (MAHNOB-HCI) dataset, respectively, and conducted an online experiment on 15 healthy subjects. The results show that multimodal methods outperform single-modal methods in both offline and online experiments. In the subject-dependent condition, the multimodal method achieved an accuracy of 71.00% in the valence dimension and an accuracy of 72.14% in the arousal dimension. In the subject-independent condition, the LSTM-based method achieved an accuracy of 78.56% in the valence dimension and an accuracy of 77.22% in the arousal dimension. The feasibility and efficiency of MindLink-Eumpy for emotion recognition is thus demonstrated.
in Frontiers in Human Neuroscience on February 19, 2021 12:00 AM.
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Focal cortical dysplasia (FCD) is a type of malformations of cortical development and one of the leading causes of drug-resistant epilepsy. Postoperative results improve the diagnosis of lesions on structural MRIs. Advances in quantitative algorithms have increased the identification of FCD lesions. However, due to significant differences in size, shape, and location of the lesion in different patients and a big deal of time for the objective diagnosis of lesion as well as the dependence of individual interpretation, sensitive approaches are required to address the challenge of lesion diagnosis. In this research, a FCD computer-aided diagnostic system to improve existing methods is presented.
MethodsMagnetic resonance imaging (MRI) data were collected from 58 participants (30 with histologically confirmed FCD type II and 28 without a record of any neurological prognosis). Morphological and intensity-based features were calculated for each cortical surface and inserted into an artificial neural network. Statistical examinations evaluated classifier efficiency.
ResultsNeural network evaluation metrics—sensitivity, specificity, and accuracy—were 96.7, 100, and 98.6%, respectively. Furthermore, the accuracy of the classifier for the detection of the lobe and hemisphere of the brain, where the FCD lesion is located, was 84.2 and 77.3%, respectively.
ConclusionAnalyzing surface-based features by automated machine learning can give a quantitative and objective diagnosis of FCD lesions in presurgical assessment and improve postsurgical outcomes.
in Frontiers in Human Neuroscience on February 19, 2021 12:00 AM.
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The convolutional neural networks (CNNs) are a powerful tool of image classification that has been widely adopted in applications of automated scene segmentation and identification. However, the mechanisms underlying CNN image classification remain to be elucidated. In this study, we developed a new approach to address this issue by investigating transfer of learning in representative CNNs (AlexNet, VGG, ResNet-101, and Inception-ResNet-v2) on classifying geometric shapes based on local/global features or invariants. While the local features are based on simple components, such as orientation of line segment or whether two lines are parallel, the global features are based on the whole object such as whether an object has a hole or whether an object is inside of another object. Six experiments were conducted to test two hypotheses on CNN shape classification. The first hypothesis is that transfer of learning based on local features is higher than transfer of learning based on global features. The second hypothesis is that the CNNs with more layers and advanced architectures have higher transfer of learning based global features. The first two experiments examined how the CNNs transferred learning of discriminating local features (square, rectangle, trapezoid, and parallelogram). The other four experiments examined how the CNNs transferred learning of discriminating global features (presence of a hole, connectivity, and inside/outside relationship). While the CNNs exhibited robust learning on classifying shapes, transfer of learning varied from task to task, and model to model. The results rejected both hypotheses. First, some CNNs exhibited lower transfer of learning based on local features than that based on global features. Second the advanced CNNs exhibited lower transfer of learning on global features than that of the earlier models. Among the tested geometric features, we found that learning of discriminating inside/outside relationship was the most difficult to be transferred, indicating an effective benchmark to develop future CNNs. In contrast to the “ImageNet” approach that employs natural images to train and analyze the CNNs, the results show proof of concept for the “ShapeNet” approach that employs well-defined geometric shapes to elucidate the strengths and limitations of the computation in CNN image classification. This “ShapeNet” approach will also provide insights into understanding visual information processing the primate visual systems.
in Frontiers in Computational Neuroscience on February 19, 2021 12:00 AM.
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Background: Musculoskeletal pain disorders are among the leading causes of years lived with disability worldwide representing a significant burden to society. Studies investigating a “nociceptive-fusimotor” relationship using experimentally-induced pain/noxious stimuli and muscle spindle afferent (MSA) response have been published over several decades. The purpose of this scoping review was to systematically identify and summarize research findings related to the impact of experimentally-induced pain or noxious stimulation on direct MSA discharge/response.
Methods: PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane and Embase were searched from database inception to August 2020. Eligible studies were: (a) published in English; (b) clinical or pre-clinical studies; (c) original data studies; (d) included the investigation of MSA response to experimentally-induced pain or noxious stimulation; (e) included quantification of at least one direct physiological measure associated with MSA activity/response. Two-phase screening procedures were conducted by a pair of independent reviewers and data extracted from eligible studies.
Results: The literature search resulted in 195 articles of which 23 met inclusion criteria. Six studies (26%) were classified as clinical and 17 (74%) as pre-clinical. Two clinical studies investigated the effects of sacral dermatome pin-pricking on MSA response, while the remaining 4 studies investigated the effects of tonic muscle and/or skin pain induced by injection/infusion of hypertonic saline into the tibialis anterior muscle or subdermal tissues. In pre-clinical studies, muscle pain was induced by injection of noxious substances or the surgical removal of the meniscus at the knee joint.
Conclusion: Clinical studies in awake humans reported that experimentally-induced pain did not affect, or else slightly decreased MSA spontaneous discharge and/or response during weak dorsiflexor muscle contraction, thus failing to support an excitatory nociceptive-fusimotor relationship. However, a majority of pre-clinical studies indicated that ipsilateral and contralateral muscle injection of noxious substances altered MSA resting discharge and/or response to stretch predominately through static fusimotor reflex mechanisms. Methodological differences (use of anesthesia, stretch methodology, etc.) may ultimately be responsible for the discrepancies between clinical and pre-clinical findings. Additional investigative efforts are needed to reconcile these discrepancies and to clearly establish or refute the existence of nociceptive-fusimotor relationship in muscular pain.
in Frontiers in Cellular Neuroscience on February 19, 2021 12:00 AM.
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Exposure to the repeated low-level blast overpressure (BOP) periodically experienced by military personnel in operational and training environments can lead to deficits in behavior and cognition. While these low-intensity blasts do not cause overt changes acutely, repeated exposures may lead to cumulative effects in the brain that include acute inflammation, vascular disruption, and other molecular changes, which may eventually contribute to neurodegenerative processes. To identify these acute changes in the brain following repeated BOP, an advanced blast simulator was used to expose rats to 8.5 or 10 psi BOP once per day for 14 days. At 24 h after the final BOP, brain tissue was collected and analyzed for inflammatory markers, astrogliosis (GFAP), tight junction proteins (claudin-5 and occludin), and neurodegeneration-related proteins (Aβ40/42, pTau, TDP-43). After repeated exposure to 8.5 psi BOP, the change in cytokine profile was relatively modest compared to the changes observed following 10 psi BOP, which included a significant reduction in several inflammatory markers. Reduction in the tight junction protein occludin was observed in both groups when compared to controls, suggesting cerebrovascular disruption. While repeated exposure to 8.5 psi BOP led to a reduction in the Alzheimer’s disease (AD)-related proteins amyloid-β (Aβ)40 and Aβ42, these changes were not observed in the 10 psi group, which had a significant reduction in phosphorylated tau. Finally, repeated 10 psi BOP exposures led to an increase in GFAP, indicating alterations in astrocytes, and an increase in the mechanosensitive ion channel receptor protein, Piezo2, which may increase brain sensitivity to injury from pressure changes from BOP exposure. Overall, cumulative effects of repeated low-level BOP may increase the vulnerability to injury of the brain by disrupting neurovascular architecture, which may lead to downstream deleterious effects on behavior and cognition.
in Frontiers in Cellular Neuroscience on February 19, 2021 12:00 AM.
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Serotonin (5-HT) is member of a family of indolamine molecules that participate in a wide variety of biological processes. Despite its important role in the regulation of local blood systems, little is known about the physiological function of 5-HT in reproductive organs, its functional implications, and its role in the reproduction of mammals. In the present work, we evaluated the localization and distribution of 5-HT (using histochemical analysis of indolamines) and different components of the serotoninergic system in rat testes. We detected local synthesis and degradation through immunofluorescence and western blot analyses against the TPH1, MAOA, 5-HTT, and VMAT1 serotonin transporters. We also identified the localization and distribution of the 5-HT1B, 5-HT2A, and 5-HT3A receptors. RT-PCR results showed the presence of the Tph1, Maoa, Slc6a4, and Htr3a genes in testes and in the brain stem (Tph1 was used as a negative control). High-performance liquid chromatography was used to determine the presence of 5-HT and the activity of tryptophan hydroxylase in testes homogenates in vitro. Our observations suggest that TPH1 activity and local 5-HT synthesis befall in rat testes. We propose that 5-HT could participate in the regulation of testosterone synthesis and in the spermatogenesis process via local serotoninergic system. However, more studies are needed before concluding that rat testes, or those of other mammals, contain an active form of tryptophan hydroxylase and produce 5-HT.
in Frontiers in Neuroanatomy on February 19, 2021 12:00 AM.
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Plasma neurofilaments light chain (pNfL) is a marker of axonal injury. The purpose of this study was to examine the role of pNfL as a predictive biomarker for post-stroke cognitive impairment (PSCI).
MethodsA prospective single-center observational cohort study was conducted at the General Hospital of Western Theater Command between July 1, 2017 and December 31, 2019. Consecutive patients ≥18 years with first-ever acute ischemic stroke (AIS) of anterior circulation within 24 h of symptom onset were included. PSCI was defined by the Montreal Cognitive Assessment (MOCA) (MOCA < 26) at 90 days after stroke onset.
ResultsA total of 1,694 patients [male, 893 (52.70%); median age, 64 (16) years] were enrolled in the cohort analysis, and 1,029 (60.70%) were diagnosed with PSCI. Patients with PSCI had significantly higher pNfL [median (IQR), 55.96 (36.13) vs. 35.73 (17.57) pg/ml; P < 0.001] than Non-PSCI. pNfL was valuable for the prediction of PSCI (OR 1.044, 95% CI 1.038–1.049, P < 0.001) after a logistic regression analysis, even after adjusting for conventional risk factors including age, sex, education level, NIHSS, TOAST classification, and infarction volume (OR 1.041, 95% CI 1.034–1.047, P < 0.001). The optimal cutoff value of the pNfL concentration was 46.12 pg/ml, which yielded a sensitivity of 71.0% and a specificity of 81.5%, with the area under the curve (AUC) at 0.785 (95% CI 0.762–0.808, P < 0.001).
ConclusionThis prospective cohort study showed that the pNfL concentration within 48 h of onset was an independent risk factor for PSCI 90 days after an anterior circulation stroke, even after being adjusted for potential influencing factors regarded as clinically relevant.
Clinical Trial Registrationwww.chictr.org.cn, identifier ChiCTR1800020330.
in Frontiers in Ageing Neuroscience on February 19, 2021 12:00 AM.
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Background: Uncertainty exists over the long-term prognostic significance of cerebral small vessel disease (CSVD) in primary intracerebral hemorrhage (ICH).
Methods: We performed a longitudinal analysis of CSVD and clinical outcomes in consecutive patients with primary ICH who had MRI. Baseline CSVD load (including white matter hyperintensities [WMH], cerebral microbleeds [CMBs], lacunes, and enlarged perivascular spaces [EPVS]) was evaluated. The cumulative CSVD score was calculated by combining the presence of each CSVD marker (range 0–4). We followed participants for poor functional outcome [modified Rankin scale [mRS] ≥ 4], stroke recurrence, and time-varying survival during a median follow-up of 4.9 [interquartile range [IQR] 3.1–6.0] years. Parsimonious and fuller multivariable logistic regression analysis and Cox-regression analysis were performed to estimate the association of CSVD markers, individually and collectively, with each outcome.
Results: A total of 153 patients were included in the analyses. CMBs ≥ 10 [adjusted OR [adOR] 3.252, 95% CI 1.181–8.956, p = 0.023] and periventricular WMH (PWMH) (adOR 2.053, 95% CI 1.220–3.456, p = 0.007) were significantly associated with poor functional outcome. PWMH (adOR 2.908, 95% CI 1.230–6.878, p = 0.015) and lobar CMB severity (adOR 1.811, 95% CI 1.039–3.157, p = 0.036) were associated with stroke recurrence. The cumulative CSVD score was associated with poor functional outcome (adOR 1.460, 95% CI 1.017–2.096) and stroke recurrence (adOR 2.258, 95% CI 1.080–4.723). Death occurred in 36.1% (13/36) of patients with CMBs ≥ 10 compared with 18.8% (22/117) in those with CMB < 10 (adjusted HR 2.669, 95% CI 1.248–5.707, p = 0.011). In addition, the cumulative CSVD score ≥ 2 was associated with a decreased survival rate (adjusted HR 3.140, 95% CI 1.066–9.250, p = 0.038).
Conclusions: Severe PWMH, CMB, or cumulative CSVD burden exert important influences on the long-term outcome of ICH.
in Frontiers in Ageing Neuroscience on February 19, 2021 12:00 AM.
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Working memory is a core cognitive function and its deficits is one of the most common cognitive impairments. Reduced working memory capacity manifests as reduced accuracy in memory recall and prolonged speed of memory retrieval in older adults. Currently, the relationship between healthy older individuals’ age-related changes in resting brain oscillations and their working memory capacity is not clear. Eyes-closed resting electroencephalogram (rEEG) is gaining momentum as a potential neuromarker of mild cognitive impairments. Wearable and wireless EEG headset measuring key electrophysiological brain signals during rest and a working memory task was utilized. This research’s central hypothesis is that rEEG (e.g., eyes closed for 90 s) frequency and network features are surrogate markers for working memory capacity in healthy older adults. Forty-three older adults’ memory performance (accuracy and reaction times), brain oscillations during rest, and inter-channel magnitude-squared coherence during rest were analyzed. We report that individuals with a lower memory retrieval accuracy showed significantly increased alpha and beta oscillations over the right parietal site. Yet, faster working memory retrieval was significantly correlated with increased delta and theta band powers over the left parietal sites. In addition, significantly increased coherence between the left parietal site and the right frontal area is correlated with the faster speed in memory retrieval. The frontal and parietal dynamics of resting EEG is associated with the “accuracy and speed trade-off” during working memory in healthy older adults. Our results suggest that rEEG brain oscillations at local and distant neural circuits are surrogates of working memory retrieval’s accuracy and processing speed. Our current findings further indicate that rEEG frequency and coherence features recorded by wearable headsets and a brief resting and task protocol are potential biomarkers for working memory capacity. Additionally, wearable headsets are useful for fast screening of cognitive impairment risk.
in Frontiers in Ageing Neuroscience on February 19, 2021 12:00 AM.
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Astrocytes are specialized glial cells that are essential components of the neurovascular unit (NVU) and are involved in neurodevelopment, brain maintenance and repair, and neurodegeneration. Astrocytes mediate these processes by releasing cellular mediators such as extracellular vesicles (EVs). EVs are vehicles of cell-cell communication and have been proposed as mediators of damage in AD. However, the transcellular mechanism by which Alzheimer disease (AD) astrocytes impair the function of NVU components is poorly understood. Therefore, we evaluated the effects of adult PS1-KI and 3xTg-AD astrocyte conditioned media (CM) and EVs on NVU components (neuroglia and endothelium) in vitro. Additionally, SAD and FAD astrocyte-derived EVs (A-EVs) were characterized, and we evaluated their effects on NVU in cocultured cells in vitro and on intrahippocampal CA1 cells in vivo. Surprisingly, cultured 3xTg-AD astrocytes showed increased glial fibrillary acidic protein (GFAP) reactivity compared to PS1-KI astrocytes, which denotes astrocytic hyperreactivity. CM from adult mice 3xTg-AD astrocytes increased cell-cell gaps between endothelial cells, filopodia-like dendritic protrusions in neurons and neuronal and endothelial cell death. 3xTg-AD A-EVs induced neurotoxicity and increased astrocyte GFAP reactivity. Cultured human postmortem astrocytes from AD patients also increased GFAP reactivity and EVs release. No differences in the size or number of A-EVs were detected between AD and control samples; however, both SAD and FAD A-EVs showed increased expression of the surface marker aquaporin 4. A-EVs induced cytotoxicity and astrocyte hyperactivation: specifically, FAD A-EVs induced neuroglial cytotoxicity and increased gaps between the endothelium, while SAD A-EVs mainly altered the endothelium. Similarly, both AD A-EVs increased astrocyte GS reactivity and vascular deterioration in vivo. We associated this finding with perivascular reactive astrocytes and vascular deterioration in the human AD brain. In summary, these results suggest that AD A-EVs impair neuroglial and vascular components.
in Frontiers in Ageing Neuroscience on February 19, 2021 12:00 AM.
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in eLife on February 19, 2021 12:00 AM.
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Publication date: Available online 17 February 2021
Source: Neural Networks
Author(s): Mei Liu, Li He, Bin Hu, Shuai Li
in Neural Networks on February 18, 2021 07:00 PM.
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in Hippocampus on February 18, 2021 04:13 PM.
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by Zutan Li, Hangjin Jiang, Lingpeng Kong, Yuanyuan Chen, Kun Lang, Xiaodan Fan, Liangyun Zhang, Cong Pian
N6-methyladenine (6mA) is an important DNA modification form associated with a wide range of biological processes. Identifying accurately 6mA sites on a genomic scale is crucial for under-standing of 6mA’s biological functions. However, the existing experimental techniques for detecting 6mA sites are cost-ineffective, which implies the great need of developing new computational methods for this problem. In this paper, we developed, without requiring any prior knowledge of 6mA and manually crafted sequence features, a deep learning framework named Deep6mA to identify DNA 6mA sites, and its performance is superior to other DNA 6mA prediction tools. Specifically, the 5-fold cross-validation on a benchmark dataset of rice gives the sensitivity and specificity of Deep6mA as 92.96% and 95.06%, respectively, and the overall prediction accuracy is 94%. Importantly, we find that the sequences with 6mA sites share similar patterns across different species. The model trained with rice data predicts well the 6mA sites of other three species: Arabidopsis thaliana, Fragaria vesca and Rosa chinensis with a prediction accuracy over 90%. In addition, we find that (1) 6mA tends to occur at GAGG motifs, which means the sequence near the 6mA site may be conservative; (2) 6mA is enriched in the TATA box of the promoter, which may be the main source of its regulating downstream gene expression.in PLoS Computational Biology on February 18, 2021 02:00 PM.
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by Carlos Coronel-Oliveros, Rodrigo Cofré, Patricio Orio
Segregation and integration are two fundamental principles of brain structural and functional organization. Neuroimaging studies have shown that the brain transits between different functionally segregated and integrated states, and neuromodulatory systems have been proposed as key to facilitate these transitions. Although whole-brain computational models have reproduced this neuromodulatory effect, the role of local inhibitory circuits and their cholinergic modulation has not been studied. In this article, we consider a Jansen & Rit whole-brain model in a network interconnected using a human connectome, and study the influence of the cholinergic and noradrenergic neuromodulatory systems on the segregation/integration balance. In our model, we introduce a local inhibitory feedback as a plausible biophysical mechanism that enables the integration of whole-brain activity, and that interacts with the other neuromodulatory influences to facilitate the transition between different functional segregation/integration regimes in the brain.in PLoS Computational Biology on February 18, 2021 02:00 PM.
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by Yaron Goldberg, Jonathan Friedman
Positive interactions, including intraspecies cooperation and interspecies mutualisms, play crucial roles in shaping the structure and function of many ecosystems, ranging from plant communities to the human microbiome. While the evolutionary forces that form and maintain positive interactions have been investigated extensively, the influence of positive interactions on the ability of species to adapt to new environments is still poorly understood. Here, we use numerical simulations and theoretical analyses to study how positive interactions impact the likelihood that populations survive after an environment deteriorates, such that survival in the new environment requires quick adaptation via the rise of new mutants—a scenario known as evolutionary rescue. We find that the probability of evolutionary rescue in populations engaged in positive interactions is reduced significantly. In cooperating populations, this reduction is largely due to the fact that survival may require at least a minimal number of individuals, meaning that adapted mutants must arise and spread before the population declines below this threshold. In mutualistic populations, the rescue probability is decreased further due to two additional effects—the need for both mutualistic partners to adapt to the new environment, and competition between the two species. Finally, we show that the presence of cheaters reduces the likelihood of evolutionary rescue even further, making it extremely unlikely. These results indicate that while positive interactions may be beneficial in stable environments, they can hinder adaptation to changing environments and thereby elevate the risk of population collapse. Furthermore, these results may hint at the selective pressures that drove co-dependent unicellular species to form more adaptable organisms able to differentiate into multiple phenotypes, including multicellular life.in PLoS Computational Biology on February 18, 2021 02:00 PM.
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by Tzu-Hao Lin, Tomonari Akamatsu, Yu Tsao
Remote acquisition of information on ecosystem dynamics is essential for conservation management, especially for the deep ocean. Soundscape offers unique opportunities to study the behavior of soniferous marine animals and their interactions with various noise-generating activities at a fine temporal resolution. However, the retrieval of soundscape information remains challenging owing to limitations in audio analysis techniques that are effective in the face of highly variable interfering sources. This study investigated the application of a seafloor acoustic observatory as a long-term platform for observing marine ecosystem dynamics through audio source separation. A source separation model based on the assumption of source-specific periodicity was used to factorize time-frequency representations of long-duration underwater recordings. With minimal supervision, the model learned to discriminate source-specific spectral features and prove to be effective in the separation of sounds made by cetaceans, soniferous fish, and abiotic sources from the deep-water soundscapes off northeastern Taiwan. Results revealed phenological differences among the sound sources and identified diurnal and seasonal interactions between cetaceans and soniferous fish. The application of clustering to source separation results generated a database featuring the diversity of soundscapes and revealed a compositional shift in clusters of cetacean vocalizations and fish choruses during diurnal and seasonal cycles. The source separation model enables the transformation of single-channel audio into multiple channels encoding the dynamics of biophony, geophony, and anthropophony, which are essential for characterizing the community of soniferous animals, quality of acoustic habitat, and their interactions. Our results demonstrated the application of source separation could facilitate acoustic diversity assessment, which is a crucial task in soundscape-based ecosystem monitoring. Future implementation of soundscape information retrieval in long-term marine observation networks will lead to the use of soundscapes as a new tool for conservation management in an increasingly noisy ocean.in PLoS Computational Biology on February 18, 2021 02:00 PM.
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by Parice A. Brandies, Carolyn J. Hogg
in PLoS Computational Biology on February 18, 2021 02:00 PM.
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by Micaela S. Parker, Arlyn E. Burgess, Philip E. Bourne
in PLoS Computational Biology on February 18, 2021 02:00 PM.
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by Johannes Werner, Debora Jeske
in PLoS Computational Biology on February 18, 2021 02:00 PM.
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by Alexandre Pitti, Mathias Quoy, Sofiane Boucenna, Catherine Lavandier
We propose a developmental model inspired by the cortico-basal system (CX-BG) for vocal learning in babies and for solving the correspondence mismatch problem they face when they hear unfamiliar voices, with different tones and pitches. This model is based on the neural architecture INFERNO standing for Iterative Free-Energy Optimization of Recurrent Neural Networks. Free-energy minimization is used for rapidly exploring, selecting and learning the optimal choices of actions to perform (eg sound production) in order to reproduce and control as accurately as possible the spike trains representing desired perceptions (eg sound categories). We detail in this paper the CX-BG system responsible for linking causally the sound and motor primitives at the order of a few milliseconds. Two experiments performed with a small and a large audio database show the capabilities of exploration, generalization and robustness to noise of our neural architecture in retrieving audio primitives during vocal learning and during acoustic matching with unheared voices (different genders and tones).in PLoS Computational Biology on February 18, 2021 02:00 PM.
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by Sabrina Islam, Christine A. Wells
in PLoS Computational Biology on February 18, 2021 02:00 PM.
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by George G. Vega Yon, Duncan C. Thomas, John Morrison, Huaiyu Mi, Paul D. Thomas, Paul Marjoram
Gene function annotation is important for a variety of downstream analyses of genetic data. But experimental characterization of function remains costly and slow, making computational prediction an important endeavor. Phylogenetic approaches to prediction have been developed, but implementation of a practical Bayesian framework for parameter estimation remains an outstanding challenge. We have developed a computationally efficient model of evolution of gene annotations using phylogenies based on a Bayesian framework using Markov Chain Monte Carlo for parameter estimation. Unlike previous approaches, our method is able to estimate parameters over many different phylogenetic trees and functions. The resulting parameters agree with biological intuition, such as the increased probability of function change following gene duplication. The method performs well on leave-one-out cross-validation, and we further validated some of the predictions in the experimental scientific literature.in PLoS Computational Biology on February 18, 2021 02:00 PM.
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by Ricardo A. R. Machado, Vanitha Theepan, Christelle A. M. Robert, Tobias Züst, Lingfei Hu, Qi Su, Bernardus C. J. Schimmel, Matthias Erb
Plants produce complex mixtures of primary and secondary metabolites. Herbivores use these metabolites as behavioral cues to increase their fitness. However, how herbivores combine and integrate different metabolite classes into fitness-relevant foraging decisions in planta is poorly understood. We developed a molecular manipulative approach to modulate the availability of sugars and benzoxazinoid secondary metabolites as foraging cues for a specialist maize herbivore, the western corn rootworm. By disrupting sugar perception in the western corn rootworm and benzoxazinoid production in maize, we show that sugars and benzoxazinoids act as distinct and dynamically combined mediators of short-distance host finding and acceptance. While sugars improve the capacity of rootworm larvae to find a host plant and to distinguish postembryonic from less nutritious embryonic roots, benzoxazinoids are specifically required for the latter. Host acceptance in the form of root damage is increased by benzoxazinoids and sugars in an additive manner. This pattern is driven by increasing damage to postembryonic roots in the presence of benzoxazinoids and sugars. Benzoxazinoid- and sugar-mediated foraging directly improves western corn rootworm growth and survival. Interestingly, western corn rootworm larvae retain a substantial fraction of their capacity to feed and survive on maize plants even when both classes of chemical cues are almost completely absent. This study unravels fine-grained differentiation and combination of primary and secondary metabolites into herbivore foraging and documents how the capacity to compensate for the lack of important chemical cues enables a specialist herbivore to survive within unpredictable metabolic landscapes.in PLoS Biology on February 18, 2021 02:00 PM.
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Author(s): Tomas Barta and Lubomir Kostal
Strong inhibitory input to neurons, which occurs in balanced states of neural networks, increases synaptic current fluctuations. This has led to the assumption that inhibition contributes to the high spike-firing irregularity observed in vivo. We used single compartment neuronal models with time-cor...
[Phys. Rev. E 103, 022408] Published Thu Feb 18, 2021
in Physical Review E: Biological physics on February 18, 2021 10:00 AM.
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in Journal of Comparative Neurology on February 18, 2021 09:07 AM.
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in Annals of Neurology on February 18, 2021 07:15 AM.
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Nature Neuroscience, Published online: 18 February 2021; doi:10.1038/s41593-021-00817-5
Publisher Correction: Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortexin Nature Neuroscience on February 18, 2021 12:00 AM.
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Nature Neuroscience, Published online: 18 February 2021; doi:10.1038/s41593-021-00804-w
Gava et al. explore the organization of neuronal co-activity in hippocampus from a graph theoretical perspective to report how new associative memories integrate into the network and restructure the neural patterns representing prior memories.in Nature Neuroscience on February 18, 2021 12:00 AM.
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Nature Neuroscience, Published online: 18 February 2021; doi:10.1038/s41593-021-00801-z
Oxidized phosphatidylcholines found in MS lesions are not just markers of oxidative stress but are also promoters of demyelination and axon injury. Microglia suppress oxidized-phosphatidylcholine-mediated neurodegeneration by phagocytosis through TREM2.in Nature Neuroscience on February 18, 2021 12:00 AM.
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Nature Neuroscience, Published online: 18 February 2021; doi:10.1038/s41593-020-00793-2
Vast networks of capillaries feed the brain. Hartmann et al. show that pericyte contractility is critical for maintenance of enduring capillary tone, which sets an optimized rate and distribution of blood flow through brain capillary networks.in Nature Neuroscience on February 18, 2021 12:00 AM.
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Nature Neuroscience, Published online: 18 February 2021; doi:10.1038/s41593-020-00792-3
Bonapersona and colleagues describe how historical control data can be used to improve statistical power while reducing the number of animals required in experiments. They present an open-source tool, RePAIR, that can be used to apply this approach.in Nature Neuroscience on February 18, 2021 12:00 AM.
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Nature Physics, Published online: 18 February 2021; doi:10.1038/s41567-021-01172-9
A structure of monolayer and bilayer graphene with a small twist between them shows correlated insulating states that can be tuned by changing the twist angle or applying an electric field.in Nature Physics on February 18, 2021 12:00 AM.
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Nature Physics, Published online: 18 February 2021; doi:10.1038/s41567-021-01170-x
The ability to perform multiple tasks simultaneously is a key characteristic of parallel architectures. Using methods from statistical physics, this study provides analytical results that quantify the limitations of processing capacity for different types of tasks in neural networks.in Nature Physics on February 18, 2021 12:00 AM.
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Nature Physics, Published online: 18 February 2021; doi:10.1038/s41567-020-01150-7
Laser spectroscopy can resolve vibrational transitions of molecular hydrogen ions without Doppler broadening when these are trapped within a cluster of laser-cooled atomic ions.in Nature Physics on February 18, 2021 12:00 AM.
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in Frontiers in Synaptic Neuroscience on February 18, 2021 12:00 AM.
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in Frontiers in Integrative Neuroscience on February 18, 2021 12:00 AM.
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Repetitive peripheral magnetic stimulation (rPMS) may improve motor function following central nervous system lesions, but the optimal parameters of rPMS to induce neural plasticity and mechanisms underlying its action remain unclear. We examined the effects of rPMS over wrist extensor muscles on neural plasticity and motor performance in 26 healthy volunteers. In separate experiments, the effects of rPMS on motor evoked potentials (MEPs), short-interval intracortical inhibition (SICI), intracortical facilitation (ICF), direct motor response (M-wave), Hoffmann-reflex, and ballistic wrist extension movements were assessed before and after rPMS. First, to examine the effects of stimulus frequency, rPMS was applied at 50, 25, and 10 Hz by setting a fixed total number of stimuli. A significant increase in MEPs of wrist extensors was observed following 50 and 25 Hz rPMS, but not 10 Hz rPMS. Next, we examined the time required to induce plasticity by increasing the number of stimuli, and found that at least 15 min of 50 and 25 Hz rPMS was required. Based on these parameters, lasting effects were evaluated following 15 min of 50 or 25 Hz rPMS. A significant increase in MEP was observed up to 60 min following 50 and 25 Hz rPMS; similarly, an attenuation of SICI and enhancement of ICF were also observed. The maximal M-wave and Hoffmann-reflex did not change, suggesting that the increase in MEP was due to plastic changes at the motor cortex. This was accompanied by increasing force and electromyograms during wrist ballistic extension movements following 50 and 25 Hz rPMS. These findings suggest that 15 min of rPMS with 25 Hz or more induces an increase in cortical excitability of the relevant area rather than altering the excitability of spinal circuits, and has the potential to improve motor output.
in Frontiers in Neuroscience: Neural Technology on February 18, 2021 12:00 AM.
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Iron has been increasingly implicated in the pathology of neurodegenerative diseases. In the past decade, development of the new magnetic resonance imaging technique, quantitative susceptibility mapping (QSM), has enabled for the more comprehensive investigation of iron distribution in the brain. The aim of this systematic review was to provide a synthesis of the findings from existing QSM studies in neurodegenerative diseases. We identified 80 records by searching MEDLINE, Embase, Scopus, and PsycInfo databases. The disorders investigated in these studies included Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Wilson's disease, Huntington's disease, Friedreich's ataxia, spinocerebellar ataxia, Fabry disease, myotonic dystrophy, pantothenate-kinase-associated neurodegeneration, and mitochondrial membrane protein-associated neurodegeneration. As a general pattern, QSM revealed increased magnetic susceptibility (suggestive of increased iron content) in the brain regions associated with the pathology of each disorder, such as the amygdala and caudate nucleus in Alzheimer's disease, the substantia nigra in Parkinson's disease, motor cortex in amyotrophic lateral sclerosis, basal ganglia in Huntington's disease, and cerebellar dentate nucleus in Friedreich's ataxia. Furthermore, the increased magnetic susceptibility correlated with disease duration and severity of clinical features in some disorders. Although the number of studies is still limited in most of the neurodegenerative diseases, the existing evidence suggests that QSM can be a promising tool in the investigation of neurodegeneration.
in Frontiers in Neuroscience: Neurodegeneration on February 18, 2021 12:00 AM.
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In EEG studies, one of the most common ways to detect a weak periodic signal in the steady-state visual evoked potential (SSVEP) is spectral evaluation, a process that detects peaks of power present at notable temporal frequencies. However, the presence of noise decreases the signal-to-noise ratio (SNR), which in turn lowers the probability of successful detection of these spectral peaks. In this paper, using a single EEG channel, we compare the detection performance of four different metrics to analyse the SSVEP: two metrics that use spectral power density, and two other metrics that use phase coherency. We employ these metrics find weak signals with a known temporal frequency hidden in the SSVEP, using both simulation and real data from a stereoscopic apparent depth movement perception task. We demonstrate that out of these metrics, the phase coherency analysis is the most sensitive way to find weak signals in the SSVEP, provided that the phase information of the stimulus eliciting the SSVEP is preserved.
in Frontiers in Neuroscience: Brain Imaging Methods on February 18, 2021 12:00 AM.
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Wild-type human SOD1 forms a highly conserved intra-molecular disulfide bond between C57-C146, and in its native state is greatly stabilized by binding one copper and one zinc atom per monomer rendering the protein dimeric. Loss of copper extinguishes dismutase activity and destabilizes the protein, increasing accessibility of the disulfide with monomerization accompanying disulfide reduction. A further pair of free thiols exist at C6 and C111 distant from metal binding sites, raising the question of their function. Here we investigate their role in misfolding of SOD1 along a pathway that leads to formation of amyloid fibrils. We present the seeding reaction of a mutant SOD1 lacking free sulfhydryl groups (AS-SOD1) to exclude variables caused by these free cysteines. Completely reduced fibril seeds decreasing the kinetic barrier to cleave the highly conserved intramolecular disulfide bond, and accelerating SOD1 reduction and initiation of fibrillation. Presence or absence of the pair of free thiols affects kinetics of fibrillation. Previously, we showed full maturation with both Cu and Zn prevents this behavior while lack of Cu renders sensitivity to fibrillation, with presence of the native disulfide bond modulating this propensity much more strongly than presence of Zn or dimerization. Here we further investigate the role of reduction of the native C57-C146 disulfide bond in fibrillation of wild-type hSOD1, firstly through removal of free thiols by paired mutations C6A, C111S (AS-SOD1), and secondly in seeded fibrillation reactions modulated by reductant tris (2-carboxyethyl) phosphine (TCEP). Fibrillation of AS-SOD1 was dependent upon disulfide reduction and showed classic lag and exponential growth phases compared with wild-type hSOD1 whose fibrillation trajectories were typically somewhat perturbed. Electron microscopy showed that AS-SOD1 formed classic fibrils while wild-type fibrillation reactions showed the presence of smaller “sausage-like” oligomers in addition to fibrils, highlighting the potential for mixed disulfides involving C6/C111 to disrupt efficient fibrillation. Seeding by addition of sonicated fibrils lowered the TCEP concentration needed for fibrillation in both wild-type and AS-SOD1 providing evidence for template-driven structural disturbance that elevated susceptibility to reduction and thus propensity to fibrillate.
in Frontiers in Neuroscience: Neurodegeneration on February 18, 2021 12:00 AM.
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Studying brain function is a challenging task. In the past, we could only study brain anatomical structures post-mortem, or infer brain functions from clinical data of patients with a brain injury. Nowadays technology, such as functional magnetic resonance imaging (fMRI), enable non-invasive brain activity observation. Several approaches have been proposed to interpret brain activity data. The brain connectivity model is a graphical tool that represents the interaction between brain regions, during certain states. It depicts how a brain region cause changes to other parts of the brain, which can be implied as information flow. This model can be used to help interpret how the brain works. There are several mathematical frameworks that can be used to infer the connectivity model from brain activity signals. Granger causality is one such approach and is one of the first that has been applied to brain activity data. However, due to the concept of the framework, such as the use of pairwise correlation, combined with the limitation of brain activity data such as low temporal resolution in case of fMRI signal, makes the interpretation of the connectivity difficult. We therefore propose the application of the Tigramite causal discovery framework on fMRI data. The Tigramite framework uses measures such as causal effect to analyze causal relations in the system. This enables the framework to identify both direct and indirect pathways or connectivities. In this paper, we applied the framework to the Human Connectome Project motor task-fMRI dataset. We then present the results and discuss how the framework improves interpretability of the connectivity model. We hope that this framework will help us understand more complex brain functions such as memory, consciousness, or the resting-state of the brain, in the future.
in Frontiers in Neuroinformatics on February 18, 2021 12:00 AM.
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Pyramidal neurons are the most common neurons in the cerebral cortex. Understanding how they differ between species is a key challenge in neuroscience. We compared human temporal cortex and mouse visual cortex pyramidal neurons from the Allen Cell Types Database in terms of their electrophysiology and dendritic morphology. We found that, among other differences, human pyramidal neurons had a higher action potential threshold voltage, a lower input resistance, and larger dendritic arbors. We learned Gaussian Bayesian networks from the data in order to identify correlations and conditional independencies between the variables and compare them between the species. We found strong correlations between electrophysiological and morphological variables in both species. In human cells, electrophysiological variables were correlated even with morphological variables that are not directly related to dendritic arbor size or diameter, such as mean bifurcation angle and mean branch tortuosity. Cortical depth was correlated with both electrophysiological and morphological variables in both species, and its effect on electrophysiology could not be explained in terms of the morphological variables. For some variables, the effect of cortical depth was opposite in the two species. Overall, the correlations among the variables differed strikingly between human and mouse neurons. Besides identifying correlations and conditional independencies, the learned Bayesian networks might be useful for probabilistic reasoning regarding the morphology and electrophysiology of pyramidal neurons.
in Frontiers in Neuroinformatics on February 18, 2021 12:00 AM.
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To preserve postoperative brain function, it is important for neurosurgeons to fully understand the brain's structure, vasculature, and function. Intraoperative high-frequency electrical stimulation during awake craniotomy is the gold standard for mapping the function of the cortices and white matter; however, this method can only map the “focal” functions and cannot monitor large-scale cortical networks in real-time. Recently, an in vivo electrophysiological method using cortico-cortical evoked potentials (CCEPs) induced by single-pulse electrical cortical stimulation has been developed in an extraoperative setting. By using the CCEP connectivity pattern intraoperatively, mapping and real-time monitoring of the dorsal language pathway is available. This intraoperative CCEP method also allows for mapping of the frontal aslant tract, another language pathway, and detection of connectivity between the primary and supplementary motor areas in the frontal lobe network. Intraoperative CCEP mapping has also demonstrated connectivity between the frontal and temporal lobes, likely via the ventral language pathway. Establishing intraoperative electrophysiological monitoring is clinically useful for preserving brain function, even under general anesthesia. This CCEP technique demonstrates potential clinical applications for mapping and monitoring large-scale cortical networks.
in Frontiers in Human Neuroscience on February 18, 2021 12:00 AM.
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Research on cognitive control has sparked increasing interest in recent years, as it is an important prerequisite for goal oriented human behavior. The paced auditory serial addition task (PASAT) has been used to test and train cognitive control functions. This adaptive, challenging task includes continuous performance feedback. Therefore, additional cognitive control capacities are required to process this information along with the already high task-load. The underlying neural mechanisms, however, are still unclear. To explore the neural signatures of the PASAT and particularly the processing of distractive feedback information, feedback locked event-related potentials were derived from 24 healthy participants during an adaptive 2-back version of the PASAT. Larger neural activation after negative feedback was found for feedback related negativity (FRN), P300, and late positive potential (LPP). In early stages of feedback processing (i.e., FRN), a larger difference between positive and negative feedback responses was associated with poorer overall performance. This association was inverted in later stages (i.e., P300 and LPP). Together, our findings indicate stage-dependent associations between neural activation after negative information and cognitive functioning. Conceivably, increased early responses to negative feedback signify distraction, whereas higher activity at later stages reflects cognitive control processes to preserve ongoing performance.
in Frontiers in Human Neuroscience on February 18, 2021 12:00 AM.
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Functional near-infrared spectroscopy (fNIRS) is a neuroimaging technique that has undergone tremendous growth over the last decade due to methodological advantages over other measures of brain activation. The action-observation network (AON), a system of brain structures proposed to have “mirroring” abilities (e.g., active when an individual completes an action or when they observe another complete that action), has been studied in humans through neural measures such as fMRI and electroencephalogram (EEG); however, limitations of these methods are problematic for AON paradigms. For this reason, fNIRS is proposed as a solution to investigating the AON in humans. The present review article briefly summarizes previous neural findings in the AON and examines the state of AON research using fNIRS in adults. A total of 14 fNIRS articles are discussed, paying particular attention to methodological choices and considerations while summarizing the general findings to aid in developing better protocols to study the AON through fNIRS. Additionally, future directions of this work are discussed, specifically in relation to researching AON development and potential multimodal imaging applications.
in Frontiers in Human Neuroscience on February 18, 2021 12:00 AM.
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This study investigated the neuromodulatory effects of transspinal stimulation on soleus H-reflex excitability and electromyographic (EMG) activity during stepping in humans with and without spinal cord injury (SCI). Thirteen able-bodied adults and 5 individuals with SCI participated in the study. EMG activity from both legs was determined for steps without, during, and after a single-pulse or pulse train transspinal stimulation delivered during stepping randomly at different phases of the step cycle. The soleus H-reflex was recorded in both subject groups under control conditions and following single-pulse transspinal stimulation at an individualized exactly similar positive and negative conditioning-test interval. The EMG activity was decreased in both subject groups at the steps during transspinal stimulation, while intralimb and interlimb coordination were altered only in SCI subjects. At the steps immediately after transspinal stimulation, the physiological phase-dependent EMG modulation pattern remained unaffected in able-bodied subjects. The conditioned soleus H-reflex was depressed throughout the step cycle in both subject groups. Transspinal stimulation modulated depolarization of motoneurons over multiple segments, limb coordination, and soleus H-reflex excitability during assisted stepping. The soleus H-reflex depression may be the result of complex spinal inhibitory interneuronal circuits activated by transspinal stimulation and collision between orthodromic and antidromic volleys in the peripheral mixed nerve. The soleus H-reflex depression by transspinal stimulation suggests a potential application for normalization of spinal reflex excitability after SCI.
in Frontiers in Human Neuroscience on February 18, 2021 12:00 AM.
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In vowel discrimination, commonly found discrimination patterns are directional asymmetries where discrimination is faster (or easier) if differing vowels are presented in a certain sequence compared to the reversed sequence. Different models of speech sound processing try to account for these asymmetries based on either phonetic or phonological properties. In this study, we tested and compared two of those often-discussed models, namely the Featurally Underspecified Lexicon (FUL) model (Lahiri and Reetz, 2002) and the Natural Referent Vowel (NRV) framework (Polka and Bohn, 2011). While most studies presented isolated vowels, we investigated a large stimulus set of German vowels in a more naturalistic setting within minimal pairs. We conducted an mismatch negativity (MMN) study in a passive and a reaction time study in an active oddball paradigm. In both data sets, we found directional asymmetries that can be explained by either phonological or phonetic theories. While behaviorally, the vowel discrimination was based on phonological properties, both tested models failed to explain the found neural patterns comprehensively. Therefore, we additionally examined the influence of a variety of articulatory, acoustical, and lexical factors (e.g., formant structure, intensity, duration, and frequency of occurrence) but also the influence of factors beyond the well-known (perceived loudness of vowels, degree of openness) in depth via multiple regression analyses. The analyses revealed that the perceptual factor of perceived loudness has a greater impact than considered in the literature and should be taken stronger into consideration when analyzing preattentive natural vowel processing.
in Frontiers in Human Neuroscience on February 18, 2021 12:00 AM.
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Multiple mechanisms contribute to the generation, propagation, and coordination of the rhythmic patterns necessary for locomotion in Caenorhabditis elegans. Current experiments have focused on two possibilities: pacemaker neurons and stretch-receptor feedback. Here, we focus on whether it is possible that a chain of multiple network rhythmic pattern generators in the ventral nerve cord also contribute to locomotion. We use a simulation model to search for parameters of the anatomically constrained ventral nerve cord circuit that, when embodied and situated, can drive forward locomotion on agar, in the absence of pacemaker neurons or stretch-receptor feedback. Systematic exploration of the space of possible solutions reveals that there are multiple configurations that result in locomotion that is consistent with certain aspects of the kinematics of worm locomotion on agar. Analysis of the best solutions reveals that gap junctions between different classes of motorneurons in the ventral nerve cord can play key roles in coordinating the multiple rhythmic pattern generators.
in Frontiers in Computational Neuroscience on February 18, 2021 12:00 AM.
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Systemic nicotine enhances neural processing in primary auditory cortex (A1) as determined using tone-evoked, current-source density (CSD) measurements. For example, nicotine enhances the characteristic frequency (CF)-evoked current sink in layer 4 of A1, increasing amplitude and decreasing latency. However, since presenting auditory stimuli within a stream of stimuli increases the complexity of response dynamics, we sought to determine the effects of nicotine on CSD responses to trains of CF stimuli (one-second trains at 2–40 Hz; each train repeated 25 times). CSD recordings were obtained using a 16-channel multiprobe inserted in A1 of urethane/xylazine-anesthetized mice, and analysis focused on two current sinks in the middle (layer 4) and deep (layers 5/6) layers. CF trains produced adaptation of the layer 4 response that was weak at 2 Hz, stronger at 5–10 Hz and complete at 20–40 Hz. In contrast, the layer 5/6 current sink exhibited less adaptation at 2–10 Hz, and simultaneously recorded auditory brainstem responses (ABRs) showed no adaptation even at 40 Hz. Systemic nicotine (2.1 mg/kg) enhanced layer 4 responses throughout the one-second stimulus train at rates ≤10 Hz. Nicotine enhanced both response amplitude within each train and the consistency of response timing across 25 trials. Nicotine did not alter the degree of adaptation over one-second trials, but its effect to increase amplitudes revealed a novel, slower form of adaptation that developed over multiple trials. Nicotine did not affect responses that were fully adapted (20–40 Hz trains), nor did nicotine affect any aspect of the layer 5/6 current sink or ABRs. The overall effect of nicotine in layer 4 was to enhance all responses within each train, to emphasize earlier trials across multiple trials, and to improve the consistency of timing across all trials. These effects may improve processing of complex acoustic streams, including speech, that contain information in the 2–10 Hz range.
in Frontiers in Neural Circuits on February 18, 2021 12:00 AM.
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Coronavirus disease 2019 (COVID-19) is marked by cardio-respiratory alterations, with increasing reports also indicating neurological and psychiatric symptoms in infected individuals. During COVID-19 pathology, the central nervous system (CNS) is possibly affected by direct severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) invasion, exaggerated systemic inflammatory responses, or hypoxia. Psychosocial stress imposed by the pandemic further affects the CNS of COVID-19 patients, but also the non-infected population, potentially contributing to the emergence or exacerbation of various neurological or mental health disorders. Microglia are central players of the CNS homeostasis maintenance and inflammatory response that exert their crucial functions in coordination with other CNS cells. During homeostatic challenges to the brain parenchyma, microglia modify their density, morphology, and molecular signature, resulting in the adjustment of their functions. In this review, we discuss how microglia may be involved in the neuroprotective and neurotoxic responses against CNS insults deriving from COVID-19. We examine how these responses may explain, at least partially, the neurological and psychiatric manifestations reported in COVID-19 patients and the general population. Furthermore, we consider how microglia might contribute to increased CNS vulnerability in certain groups, such as aged individuals and people with pre-existing conditions.
in Frontiers in Cellular Neuroscience on February 18, 2021 12:00 AM.
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Astrocytes are the most abundant cell type within the central nervous system (CNS) with various functions. Furthermore, astrocytes show a regional and developmental heterogeneity traceable with specific markers. In this study, the influence of the low-density lipoprotein receptor-related protein 1 (LRP1) on astrocytic maturation within the hippocampus was analyzed during development. Previous studies mostly focused on the involvement of LRP1 in the neuronal compartment, where the deletion caused hyperactivity and motor dysfunctions in knockout animals. However, the influence of LRP1 on glia cells is less intensively investigated. Therefore, we used a newly generated mouse model, where LRP1 is specifically deleted from GLAST-positive astrocytes co-localized with the expression of the reporter tdTomato to visualize recombination and knockout events in vivo. The influence of LRP1 on the maturation of hippocampal astrocytes was assessed with immunohistochemical stainings against stage-specific markers as well as on mRNA level with RT-PCR analysis. The examination revealed that the knockout induction caused a significantly decreased number of mature astrocytes at an early developmental timepoint compared to control animals. Additionally, the delayed maturation of astrocytes also caused a reduced activity of neurons within the hippocampus. As previous studies showed that the glial specification and maturation of astrocytes is dependent on the signaling cascades Ras/Raf/MEK/Erk and PI3K/Akt, the phosphorylation of the signaling molecules Erk1/2 and Akt was analyzed. The hippocampal tissue of LRP1-deficient animals at P21 showed a significantly decreased amount of activated Erk in comparison to control tissue leading to the conclusion that the activation of this signaling cascade is dependent on LRP1 in astrocytes, which in turn is necessary for proper maturation of astrocytes. Our results showed that the deletion of LRP1 at an early developmental timepoint caused a delayed maturation of astrocytes in the hippocampus based on an altered activation of the Ras/Raf/MEK/Erk signaling pathway. However, with ongoing development these effects were compensated and the number of mature astrocytes was comparable as well as the activity of neurons. Therefore, LRP1 acts as an early regulator of the differentiation and maturation of astrocytes within the hippocampus.
in Frontiers in Cellular Neuroscience on February 18, 2021 12:00 AM.
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Background: Indoleamine-2,3-dioxygenase 1 (IDO1) is the initial and rate-limiting enzyme in the metabolism of tryptophan (TRP) to kynurenine (KYN). IDO1-dependent neurotoxic KYN metabolism plays a crucial role in the pathogenesis of many neurodegenerative disorders. However, the function of IDO1 in epilepsy is still unclear.
Objective: In this study, we investigated whether IDO1 deficiency could affect epilepsy in a lithium-pilocarpine-induced model.
Methods: Patients with epilepsy and controls were enrolled. Male C57BL/6 mice and IDO1 knockout (KO, IDO1−/−) mice were subjected to intraperitoneal injection of lithium and pilocarpine to induce epilepsy. The levels of IDO1 and concentrations of TRP and KYN in patients with epilepsy and epileptic mice were evaluated by enzyme-linked immunosorbent assay (ELISA) and liquid chromatography-mass spectrometry (LC-MS), respectively. Then, behavioral phenotypes related to epileptic seizures and neuronal damage were compared between KO and wild-type (WT) mice with lithium-pilocarpine-induced epilepsy. To explore the underlying pathways involved in the effects of IDO1 deficiency, the concentrations of kynurenic acid (KYNA) and quinolinic acid (QUIN), glial cell activation, the levels of major pro-inflammatory cytokines, and antioxidant enzyme activity were measured by LC-MS, immunohistochemistry, and ELISA.
Results: In this study, IDO1 levels and the KYN/TRP ratio in the sera and cerebrospinal fluid (CSF) were increased in patients with epilepsy. Also, IDO1 levels, the KYN/TRP ratio, and the levels of pro-inflammatory cytokines in the sera and hippocampi were increased in mice during the acute phase and chronic phase after status epilepticus (SE). Furthermore, IDO1 was localized in microglial cells in epileptic mice. IDO1 deficiency delayed SE onset and attenuated the frequency, duration, and severity of spontaneous recurrent seizures (SRSs). Moreover, IDO1 deficiency improved neuronal survival. Additionally, IDO1−/− epileptic mice showed progressive declines in QUIN production, glial cell activation and pro-inflammatory cytokines levels, and enhanced antioxidant enzyme activity.
Conclusions: IDO1 deletion suppressed seizures and alleviated neuronal damage by reducing the IDO1-dependent production of neurotoxic metabolites, which finally inhibited glial cell activation and pro-inflammatory cytokine production and improved antioxidant enzyme activity. Our study demonstrates that IDO1 may be involved in the pathogenesis of epilepsy and has the potential to be a therapeutic target for epilepsy treatment.
in Frontiers in Cellular Neuroscience on February 18, 2021 12:00 AM.
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Brain microvascular endothelial cells (BMECs) are a major component of the blood-brain barrier that maintains brain homeostasis. Preserving and restoring the normal biological functions of BMECs can reverse or reduce brain injury. Endothelial progenitor cells (EPCs) may promote brain vascular remodeling and restore normal endothelial function. As a novel vehicle for cell-cell communication, microvesicles (MVs) have varied biological functions. The present study investigated the biological effects of EPC-derived MVs (EPC-MVs) on BMECs in vitro. We isolated MVs from the supernatant of EPCs in a serum-depleted medium. BMECs were cultured alone or in the presence of EPC-MVs. BMEC viability and proliferation were evaluated with the Cell Counting Kit-8 and by flow cytometry, and the proangiogenic effect of EPC-MVs on BMECs was assessed with the transwell migration, wound healing, and tube formation assays. Our results showed that EPC-derived MVs labeled with DiI were internalized by cultured BMECs; this enhanced BMEC viability and promoted their proliferation. EPC-MVs also stimulated migration and tube formation in BMECs. These results demonstrate that EPC-derived MVs exert a proangiogenic effect on BMECs, which has potential applications in cell-free therapy for brain injury.
in Frontiers in Cellular Neuroscience on February 18, 2021 12:00 AM.
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The most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) is a hexanucleotide expansion in the chromosome 9 open reading frame 72 gene (C9ORF72). This hexanucleotide expansion consists of GGGGCC (G4C2) repeats that have been implicated to lead to three main modes of disease pathology: loss of function of the C9ORF72 protein, the generation of RNA foci, and the production of dipeptide repeat proteins (DPRs) through repeat-associated non-AUG (RAN) translation. Five different DPRs are currently known to be formed: glycine–alanine (GA) and glycine–arginine (GR) from the sense strand, proline–alanine (PA), and proline–arginine (PR) from the antisense strand, and glycine–proline (GP) from both strands. The exact contribution of each DPR to disease pathology is currently under intense scrutiny and is still poorly understood. However, recent advances in both neuropathological and cellular studies have provided us with clues enabling us to better understand the effect of individual DPRs on disease pathogenesis. In this review, we compile the current knowledge of specific DPR involvement on disease development and highlight recent advances, such as the impact of arginine-rich DPRs on nucleolar protein quality control, the correlation of poly-GR with neurodegeneration, and the possible involvement of chimeric DPR species. Further, we discuss recent findings regarding the mechanisms of RAN translation, its modulators, and other promising therapeutic options.
in Frontiers in Cellular Neuroscience on February 18, 2021 12:00 AM.
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Spinal cord injury (SCI) is a devastating form of neurotrauma. Patients who carry one or two apolipoprotein E (ApoE)4 alleles show worse functional outcomes and longer hospital stays after SCI, but the cellular and molecular underpinnings for this genetic link remain poorly understood. Thus, there is a great need to generate animal models to accurately replicate the genetic determinants of outcomes after SCI to spur development of treatments that improve physical function. Here, we examined outcomes after a moderate contusion SCI of transgenic mice expressing human ApoE3 or ApoE4. ApoE4 mice have worse locomotor function and coordination after SCI. Histological examination revealed greater glial staining in ApoE4 mice after SCI associated with reduced levels of neuronal sprouting markers. Bulk RNA sequencing revealed that subcellular processes (SCPs), such as extracellular matrix organization and inflammatory responses, were highly ranked among upregulated genes at 7 days after SCI in ApoE4 variants. Conversely, SCPs related to neuronal action potential and neuron projection development were increased in ApoE3 mice at 21 days. In summary, our results reveal a clinically relevant SCI mouse model that recapitulates the influence of ApoE genotypes on post SCI function in individuals who carry these alleles and suggest that the mechanisms underlying worse recovery for ApoE4 animals involve glial activation and loss of sprouting and synaptic activity.
in Frontiers in Cellular Neuroscience on February 18, 2021 12:00 AM.
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In contrast to the prenatal topographic development of sensory cortices, striatal circuit organization is slow and requires the functional maturation of cortical and thalamic excitatory inputs throughout the first postnatal month. While mechanisms regulating synapse development and plasticity are quite well described at excitatory synapses of glutamatergic neurons in the neocortex, comparatively little is known of how this translates to glutamate synapses onto GABAergic neurons in the striatum. Here we investigate excitatory striatal synapse plasticity in an in vitro system, where glutamate can be studied in isolation from dopamine and other neuromodulators. We examined pre-and post-synaptic structural and functional plasticity in GABAergic striatal spiny projection neurons (SPNs), co-cultured with glutamatergic cortical neurons. After synapse formation, medium-term (24 h) TTX silencing increased the density of filopodia, and modestly decreased dendritic spine density, when assayed at 21 days in vitro (DIV). Spine reductions appeared to require residual spontaneous activation of ionotropic glutamate receptors. Conversely, chronic (14 days) TTX silencing markedly reduced spine density without any observed increase in filopodia density. Time-dependent, biphasic changes to the presynaptic marker Synapsin-1 were also observed, independent of residual spontaneous activity. Acute silencing (3 h) did not affect presynaptic markers or postsynaptic structures. To induce rapid, activity-dependent plasticity in striatal neurons, a chemical NMDA receptor-dependent “long-term potentiation (LTP)” paradigm was employed. Within 30 min, this increased spine and GluA1 cluster densities, and the percentage of spines containing GluA1 clusters, without altering the presynaptic signal. The results demonstrate that the growth and pruning of dendritic protrusions is an active process, requiring glutamate receptor activity in striatal projection neurons. Furthermore, NMDA receptor activation is sufficient to drive glutamatergic structural plasticity in SPNs, in the absence of dopamine or other neuromodulators.
in Frontiers in Cellular Neuroscience on February 18, 2021 12:00 AM.
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The cellular redox state, or balance between cellular oxidation and reduction reactions, serves as a vital antioxidant defence system that is linked to all important cellular activities. Redox regulation is therefore a fundamental cellular process for aerobic organisms. Whilst oxidative stress is well described in neurodegenerative disorders including amyotrophic lateral sclerosis (ALS), other aspects of redox dysfunction and their contributions to pathophysiology are only just emerging. ALS is a fatal neurodegenerative disease affecting motor neurons, with few useful treatments. Hence there is an urgent need to develop more effective therapeutics in the future. Here, we discuss the increasing evidence for redox dysregulation as an important and primary contributor to ALS pathogenesis, which is associated with multiple disease mechanisms. Understanding the connection between redox homeostasis, proteins that mediate redox regulation, and disease pathophysiology in ALS, may facilitate a better understanding of disease mechanisms, and lead to the design of better therapeutic strategies.
in Frontiers in Cellular Neuroscience on February 18, 2021 12:00 AM.
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Cytochrome oxidase (CO) histochemistry has been used to reveal the cytoarchitecture of the primate brain, including blobs/puffs/patches in the striate cortex (V1), and thick, thin and pale stripes in the middle layer of the secondary visual cortex (V2). It has been suggested that CO activity is coupled with the spiking activity of neurons, implying that neurons in these CO-rich subcompartments are more active than surrounding regions. However, we have discussed possibility that CO histochemistry represents the distribution of thalamo-cortical afferent terminals that generally use vesicular glutamate transporter 2 (VGLUT2) as their main glutamate transporter, and not the activity of cortical neurons. In this study, we systematically compared the labeling patterns observed between CO histochemistry and immunohistochemistry (IHC) for VGLUT2 from the system to microarchitecture levels in the visual cortex of squirrel monkeys. The two staining patterns bore striking similarities at all levels of the visual cortex, including the honeycomb structure of V1 layer 3Bβ (Brodmann's layer 4A), the patchy architecture in the deep layers of V1, the superficial blobs of V1, and the V2 stripes. The microarchitecture was more evident in VGLUT2 IHC, as expected. VGLUT2 protein expression that produced specific IHC labeling is thought to originate from the thalamus since the lateral geniculate nucleus (LGN) and the pulvinar complex both show high expression levels of VGLUT2 mRNA, but cortical neurons do not. These observations support our theory that the subcompartments revealed by CO histochemistry represent the distribution of thalamo-cortical afferent terminals in the primate visual cortex.
in Frontiers in Neuroanatomy on February 18, 2021 12:00 AM.
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Transient ischemic brain injury causes massive neuronal death in the hippocampus of both humans and animals. This was accompanied by progressive atrophy of the hippocampus, brain cortex, and white matter lesions. Furthermore, it has been noted that neurodegenerative processes after an episode of ischemia-reperfusion in the brain can continue well-beyond the acute stage. Rarefaction of white matter was significantly increased in animals at 2 years following ischemia. Some rats that survived 2 years after ischemia developed severe brain atrophy with dementia. The profile of post-ischemic brain neurodegeneration shares a commonality with neurodegeneration in Alzheimer's disease. Furthermore, post-ischemic brain injury is associated with the deposition of folding proteins, such as amyloid and tau protein, in the intracellular and extracellular space. Recent studies on post-ischemic brain neurodegeneration have revealed the dysregulation of Alzheimer's disease-associated genes such as amyloid protein precursor, α-secretase, β-secretase, presenilin 1, presenilin 2, and tau protein. The latest data demonstrate that Alzheimer's disease-related proteins and their genes play a key role in the development of post-ischemic brain neurodegeneration with full-blown dementia in disease types such as Alzheimer's. Ongoing interest in the study of brain ischemia has provided evidence showing that ischemia may be involved in the development of the genotype and phenotype of Alzheimer's disease, suggesting that brain ischemia can be considered as a useful model for understanding the mechanisms responsible for the initiation of Alzheimer's disease.
in Frontiers in Ageing Neuroscience on February 18, 2021 12:00 AM.
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Electroencephalogram (EEG) power reductions in the aging brain have been described by numerous previous studies. However, the underlying mechanism for the observed brain signal power reduction remains unclear. One possible cause for reduced EEG signals in elderly subjects might be the increased distance from the primary neural electrical currents on the cortex to the scalp electrodes as the result of cortical atrophies. While brain shrinkage itself reflects age-related neurological changes, the effects of changes in the distribution of electrical conductivity are often not distinguished from altered neural activity when interpreting EEG power reductions. To address this ambiguity, we employed EEG forward models to investigate whether brain shrinkage is a major factor for the signal attenuation in the aging brain. We simulated brain shrinkage in spherical and realistic brain models and found that changes in the conductor geometry cannot fully account for the EEG power reductions even when the brain was shrunk to unrealistic sizes. Our results quantify the extent of power reductions from brain shrinkage and pave the way for more accurate inferences about deficient neural activity and circuit integrity based on EEG power reductions in the aging population.
in Frontiers in Ageing Neuroscience on February 18, 2021 12:00 AM.
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Prior research has suggested that measurements of brain functioning and performance on dual tasks (tasks which require simultaneous performance) are promising candidate predictors of fall risk among older adults. However, no prior study has investigated whether brain function measurements during dual task performance could improve prediction of fall risks and whether the type of subtasks used in the dual task paradigm affects the strength of the association between fall characteristics and dual task performance. In this study, 31 cognitively normal, community-dwelling older adults provided a self-reported fall profile (number of falls and fear of falling), completed a gait dual task (spell a word backward while walking on a GaitRite mat), and completed a supine dual task (rhythmic finger tapping with one hand while completing the AX continuous performance task (AX-CPT) with the other hand) during functional magnetic resonance imaging (fMRI). Gait performance, AX-CPT reaction time and accuracy, finger tapping cadence, and brain functioning in finger-tapping-related and AX-CPT-related brain regions all showed declines in the dual task condition compared to the single task condition. Dual-task gait, AX-CPT and finger tapping performance, and brain functioning were all independent predictors of fall profile. No particular measurement domain stood out as being the most strongly associated measure with fall variables. Fall characteristics are determined by multiple factors; brain functioning, motor task, and cognitive task performance in challenging dual-task conditions all contribute to the risk of falling.
in Frontiers in Ageing Neuroscience on February 18, 2021 12:00 AM.
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Recent neuroimaging studies have shown the possibility of cognitive impairment after pontine stroke. In this study, we aimed to use voxel-mirrored homotopic connectivity (VMHC) to investigate changes in the cognitive function in chronic pontine stroke. Functional MRI (fMRI) and behavioral assessments of cognitive function were obtained from 56 patients with chronic pontine ischemic stroke [28 patients with left-sided pontine stroke (LP) and 28 patients with right-sided pontine stroke (RP)] and 35 matched healthy controls (HC). The one-way ANOVA test was performed for the three groups after the VMHC analysis. Results showed that there were significant decreases in the bilateral lingual gyrus (Lingual_L and Lingual_R) and the left precuneus (Precuneus_L) in patients with chronic pontine ischemic stroke compared to HCs. However, in a post-hoc multiple comparison test, this difference remained only between the HC and RP groups. Moreover, we explored the relationship between the decreased z-values in VMHC and the behavior-task scores using a Pearson's correlation test and found that both scores of short-term memory and long-term memory in the Rey Auditory Verbal Learning Test were positively correlated with z-values of the left lingual gyrus (Lingual_L), the right lingual gyrus (Lingual_R), and the left precuneus (Precuneus_L) in VMHC. Besides that, the z-values of Precuneus_L in VMHC were also negatively correlated with the reaction time for correct responses in the Flanker task and the spatial memory task. In conclusion, first, the lingual gyrus played an important role in verbal memory. Second, the precuneus influenced the working memory, both auditory-verbal memory and visual memory. Third, the right-sided stroke played a greater role in the results of this study. This study provides a basis for further elucidation of the characteristics and mechanisms of cognitive impairment after pontine stroke.
in Frontiers in Ageing Neuroscience on February 18, 2021 12:00 AM.
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Mitochondria play a pivotal role in bioenergetics and respiratory functions, which are essential for the numerous biochemical processes underpinning cell viability. Mitochondrial morphology changes rapidly in response to external insults and changes in metabolic status via fission and fusion processes (so-called mitochondrial dynamics) that maintain mitochondrial quality and homeostasis. Damaged mitochondria are removed by a process known as mitophagy, which involves their degradation by a specific autophagosomal pathway. Over the last few years, remarkable efforts have been made to investigate the impact on the pathogenesis of Alzheimer’s disease (AD) of various forms of mitochondrial dysfunction, such as excessive reactive oxygen species (ROS) production, mitochondrial Ca2+ dyshomeostasis, loss of ATP, and defects in mitochondrial dynamics and transport, and mitophagy. Recent research suggests that restoration of mitochondrial function by physical exercise, an antioxidant diet, or therapeutic approaches can delay the onset and slow the progression of AD. In this review, we focus on recent progress that highlights the crucial role of alterations in mitochondrial function and oxidative stress in the pathogenesis of AD, emphasizing a framework of existing and potential therapeutic approaches.
in Frontiers in Ageing Neuroscience on February 18, 2021 12:00 AM.
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Publication date: Available online 17 February 2021
Source: Neural Networks
Author(s): Jin-Woo Seo, Hong-Gyu Jung, Seong-Whan Lee
in Neural Networks on February 17, 2021 07:00 PM.
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Publication date: Available online 16 February 2021
Source: Neural Networks
Author(s): Luis Garcia, Giovanny Sanchez, Eduardo Vazquez, Gerardo Avalos, Esteban Anides, Mariko Nakano, Gabriel Sanchez, Hector Perez
in Neural Networks on February 17, 2021 07:00 PM.
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Publication date: Available online 16 February 2021
Source: Neural Networks
Author(s): Jiejie Chen, Boshan Chen, Zhigang Zeng
in Neural Networks on February 17, 2021 07:00 PM.
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in Hippocampus on February 17, 2021 04:02 PM.
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in Hippocampus on February 17, 2021 04:02 PM.
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in Hippocampus on February 17, 2021 04:02 PM.
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in Hippocampus on February 17, 2021 04:02 PM.
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in Hippocampus on February 17, 2021 04:02 PM.
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in Hippocampus on February 17, 2021 04:02 PM.
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in Hippocampus on February 17, 2021 04:02 PM.
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in Hippocampus on February 17, 2021 04:02 PM.
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in Hippocampus on February 17, 2021 04:02 PM.
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in Hippocampus on February 17, 2021 04:02 PM.
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in Hippocampus on February 17, 2021 04:02 PM.
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by Viktor Sip, Meysam Hashemi, Anirudh N. Vattikonda, Marmaduke M. Woodman, Huifang Wang, Julia Scholly, Samuel Medina Villalon, Maxime Guye, Fabrice Bartolomei, Viktor K. Jirsa
Surgical interventions in epileptic patients aimed at the removal of the epileptogenic zone have success rates at only 60-70%. This failure can be partly attributed to the insufficient spatial sampling by the implanted intracranial electrodes during the clinical evaluation, leading to an incomplete picture of spatio-temporal seizure organization in the regions that are not directly observed. Utilizing the partial observations of the seizure spreading through the brain network, complemented by the assumption that the epileptic seizures spread along the structural connections, we infer if and when are the unobserved regions recruited in the seizure. To this end we introduce a data-driven