A critical assessment of clustering algorithms to improve cell clustering and identification in single-cell transcriptome study.

Cell clustering is typically the initial step in single-cell RNA sequencing (scRNA-seq) analyses. The performance of clustering considerably impacts the validity and reproducibility of cell identification. A variety of clustering algorithms have been developed for scRNA-seq data. These algorithms generate cell label sets that assign each cell to a cluster. However, different algorithms usually yield different label sets, which can introduce variations in cell-type identification based on the generated label sets. Currently, the performance of these algorithms has not been systematically evaluated in single-cell transcriptome studies. Herein, we performed a critical assessment of seven state-of-the-art clustering algorithms including four deep learning-based clustering algorithms and commonly used methods Seurat, Cosine-based Tanimoto similarity-refined graph for community detection using Leiden's algorithm (CosTaL) and Single-cell consensus clustering (SC3). We used diverse evaluation indices based on 10 different scRNA-seq benchmarks to systematically evaluate their clustering performance. Our results show that CosTaL, Seurat, Deep Embedding for Single-cell Clustering (DESC) and SC3 consistently outperformed Single-Cell Clustering Assessment Framework and scDeepCluster based on nine effectiveness scores. Notably, CosTaL and DESC demonstrated superior performance in clustering specific cell types. The performance of the single-cell Variational Inference tools varied across different datasets, suggesting its sensitivity to certain dataset characteristics. Notably, DESC exhibited promising results for cell subtype identification and capturing cellular heterogeneity. In addition, SC3 requires more memory and exhibits slower computation speed compared to other algorithms for the same dataset. In sum, this study provides useful guidance for selecting appropriate clustering methods in scRNA-seq data analysis.

High Performance Nacre Fibers by Engineering Interfacial Entanglement.

Biological materials exhibit fascinating mechanical properties for intricate interactions at multiple interfaces to combine superb toughness with wondrous strength and stiffness. Recently, strong interlayer entanglement has emerged to replicate the powerful dissipation of natural proteins and alleviate the conflict between strength and toughness. However, designing intricate interactions in a strong entanglement network needs to be further explored. Here, we modulate interlayer entanglement by introducing multiple interactions, including hydrogen and ionic bonding, and achieve ultrahigh mechanical performance of graphene-based nacre fibers. Two essential modulating trends are directed. One is modulating dynamic hydrogen bonding to improve the strength and toughness up to 1.58 GPa and 52 MJ/m3, simultaneously. The other is tailoring ionic coordinating bonding to raise the strength and stiffness, reaching 2.3 and 253 GPa. Modulating various interactions within robust entanglement provides an effective approach to extend performance limits of bioinspired nacre and optimize multiscale interfaces in diverse composites.

Identification of the hub genes in polycystic ovary syndrome based on disease-associated molecule network.

Revealing the key genes involved in polycystic ovary syndrome (PCOS) and elucidating its pathogenic mechanism is of extreme importance for the development of targeted clinical therapy for PCOS. Investigating disease by integrating several associated and interacting molecules in biological systems will make it possible to discover new pathogenic genes. In this study, an integrative disease-associated molecule network, combining protein-protein interactions and protein-metabolites interactions (PPMI) network was constructed based on the PCOS-associated genes and metabolites systematically collected. This new PPMI strategy identified several potential PCOS-associated genes, which have unreported in previous publications. Moreover, the systematic analysis of five benchmarks data sets indicated the DERL1 was identified as downregulated in PCOS granulosa cell and has good classification performance between PCOS patients and healthy controls. CCR2 and DVL3 were upregulated in PCOS adipose tissues and have good classification performance. The expression of novel gene FXR2 identified in this study is significantly increased in ovarian granulosa cells of PCOS patients compared with controls via quantitative analysis. Our study uncovers substantial differences in the PCOS-specific tissue and provides a plethora of information on dysregulated genes and metabolites that are linked to PCOS. This knowledgebase could have the potential to benefit the scientific and clinical community. In sum, the identification of novel gene associated with PCOS provides valuable insights into the underlying molecular mechanisms of PCOS and could potentially lead to the development of new diagnostic and therapeutic strategies.

Design, synthesis, and antiviral activity of 1-aryl-4-arylmethylpiperazine derivatives as Zika virus inhibitors with broad antiviral spectrum.

Zika virus (ZIKV) disease has been given attention due to the risk of congenital microcephaly and neurodevelopmental disorders after ZIKV infection in pregnancy, but no vaccine or antiviral drug is available. Based on a previously reported ZIKV inhibitor ZK22, a series of novel 1-aryl-4-arylmethylpiperazine derivatives was designed, synthesized, and investigated for antiviral activity by quantify cellular ZIKV RNA amount using RT-qPCR method in ZIKV-infected human venous endothelial cells (HUVECs) assay. Structure-activity relationship (SAR) analysis demonstrated that anti-ZIKV activity of 1-aryl-4-arylmethylpiperazine derivatives is not correlated with molecular hydrophobicity, multiple new derivatives with pyridine group to replace the benzonitrile moiety of ZK22 showed stronger antiviral activity, higher ligand lipophilicity efficiency as well as lower cytotoxicity. Two active compounds 13 and 33 were further identified as novel ZIKV entry inhibitors with the potential of oral available. Moreover, both ZK22 and newly active derivatives also possess of obvious inhibition on the viral replication of coronavirus and influenza A virus at low micromolar level. In summary, this work provided better candidates of ZIKV inhibitor for preclinical study and revealed the promise of 1-aryl-4-arylmethylpiperazine chemotype in the development of broad-spectrum antiviral agents.

Global Trends and Frontier in Research on Pancreatic Alpha Cells: A Bibliometric Analysis from 2013 to 2023.

PURPOSE: Over the past 20 years, much of the research on diabetes has focused on pancreatic beta cells. In the last 10 years, interest in the important role of pancreatic alpha cells in the pathogenesis of diabetes, which had previously received little attention, has grown. We aimed to summarize and visualize the hotspot and development trends of pancreatic alpha cells through bibliometric analysis and to provide research direction and future ideas for the treatment of diabetes and other islet-related diseases. METHODS: We used two scientometric software packages (CiteSpace 6.1.R6 and VOSviewer1.6.18) to visualize the information and connection of countries, institutions, authors, and keywords in this field. RESULTS: A total of 532 publications, published in 752 institutions in 46 countries and regions, were included in this analysis. The United States showed the highest output, accounting for 39.3% of the total number of published papers. The most active institution was Vanderbilt University, and the authors with highest productivity came from Ulster University. In recent years, research hotspots have concentrated on transdifferentiation, gene expression, and GLP-1 regulatory function. Visualization analysis shows that research hotspots mainly focus on clinical diseases as well as physiological and pathological mechanisms and related biochemical indicators. CONCLUSIONS: This study provides a review and summary of the literature on pancreatic alpha cells through bibliometric and visual methods and shows research hotspot and development trends, which can guide future directions for research.

Superior Strong and Tough Nacre-Inspired Materials by Interlayer Entanglement.

Natural materials teach that mechanical dissipative interactions relieve the conflict between strength and toughness and enable fabrication of strong yet tough artificial materials. Replicating natural nacre structure has yielded rich biomimetic materials; however, stronger interlayer dissipation still waits to be exploited to extend the performance limits of artificial nacre materials. Here, we introduce strong entanglement as a new artificial interlayer dissipative mechanism and fabricate entangled nacre materials with superior strength and toughness, across molecular to nanoscale nacre structures. The entangled graphene nacre fibers achieved high strength of 1.2 GPa and toughness of 47 MJ/m3, and films reached 1.5 GPa and 25 MJ/m3. Experiments and simulations reveal that strong entanglement can effectively dissipate interlayer energy to relieve the conflict between strength and toughness, acting as natural folded proteins. The strong interlayer entanglement opens up a new path for designing stronger and tougher artificial materials to mimic but surpass natural materials.

Multimorbidity, cognitive phenotypes, and Alzheimer's disease plasma biomarkers in older adults: A population-based study.

INTRODUCTION: To examine the burden and clusters of multimorbidity in association with mild cognitive impairment (MCI), dementia, and Alzheimer's disease (AD)-related plasma biomarkers among older adults. METHODS: This population-based study included 5432 participants (age ≥60 years); of these, plasma amyloid beta (Aß), total tau, and neurofilament light chain (NfL) were measured in a subsample (n = 1412). We used hierarchical clustering to generate five multimorbidity clusters from 23 chronic diseases. We diagnosed dementia and MCI following international criteria. Data were analyzed using logistic and linear regression models. RESULTS: The number of chronic diseases was associated with dementia (multivariable-adjusted odds ratio = 1.22; 95% confidence interval [CI] = 1.11 to 1.33), AD (1.13; 1.01 to 1.26), vascular dementia (VaD) (1.44; 1.25 to 1.64), and non-amnestic MCI (1.25; 1.13 to 1.37). Metabolic cluster was associated with VaD and non-amnestic MCI, whereas degenerative ocular cluster was associated with AD (p < 0.05). The number of chronic diseases was associated with increased plasma Aß and NfL (p < 0.05). DISCUSSION: Multimorbidity burden and clusters are differentially associated with subtypes of dementia and MCI and AD-related plasma biomarkers in older adults. HIGHLIGHTS: We used hierarchical clustering to generate five clusters of multimorbidity. The presence and load of multimorbidity were associated with dementia and mild cognitive impairment. Multimorbidity clusters were differentially associated with subtypes of dementia and Alzheimer's disease plasma biomarkers.

Falling-Leaves Stacking Aggregation of Two-Dimensional Macromolecular Graphene Oxide in Solution.

Understanding the dynamical behaviors of two-dimensional (2D) macromolecules is of fundamental importance for the precise modulation of their assembled structures and material performances. However, considerably less is known about how discrete macromolecular sheets aggregate into extended macroscopic assemblies in solutions. The absence of a quantitative description of the assembly process limits the precise structural control of assemblies. Here, we investigated the aggregation thermodynamic transition and kinetic behavior of 2D macromolecules in the model of single layer graphene oxide (GO). Combining Flory-Huggins theory with experimental observations, we unveiled the critical thermodynamic transition of GO to correlate with the solvent property. We proposed a theoretical falling-leaf model to quantitatively describe the kinetic aggregation process of 2D GO sheets. Experimental analysis validated the theoretical prediction that the thickness of GO aggregates has a power law relation with the poor solvent content. Our work provides a fundamental understanding of phase separation of 2D macromolecules and offers an insight into modulating the aggregated structures of their assembled materials.

Cost-Effectiveness of Low-Dose Compared to Standard-Dose Alteplase for Acute Ischemic Stroke in China: A Within-Trial Economic Evaluation of the ENCHANTED Study.

INTRODUCTION: The Enhanced Control of Hypertension and Thrombolysis Stroke Study (ENCHANTED) showed that a low-dose alteplase was safe but not clearly non-inferior to standard-dose alteplase in acute ischemic stroke (AIS). Given the significant cost of this medicine, we undertook a cost-effectiveness analysis to determine the probability that low-dose is cost-effective relative to standard-dose alteplase in China. METHODS: For ENCHANTED participants in China with available health cost data, cost-effectiveness and cost-utility analyses were undertaken in which death or disability (modified Rankin scale scores 2-6) at 90 days and quality-adjusted life-years (QALYs) were used as outcome measures, respectively. There was adherence to standard guidelines for health economic evaluations alongside non-inferiority trials and according to a health-care payer's perspective. The equivalence margin for cost and effectiveness was set at USD 691 and -0.025 QALYs, respectively, for the base-case analysis. Probabilistic sensitivity analyses were used to evaluate the probability of low-dose alteplase being non-inferior. RESULTS: While the mean cost of alteplase was lower in the low-dose group (USD 1,569 vs. USD 2,154 in the standard-dose group), the total cost was USD 56 (95% confidence interval [CI]: -1,000-1,113) higher compared to the standard-dose group due to higher hospitalization costs in the low-dose group. There were 462 (95% CI: 415-509) and 410 (95% CI: 363-457) patients with death or disability per 1,000 patients in the low-dose and standard-dose groups, respectively. The low-dose group had marginally lower (0.008, 95% CI: -0.016-0.001) QALYs compared to their standard-dose counterparts. The low-dose group was found to have an 88% probability of being non-inferior based on cost-effectiveness versus the standard-dose group. CONCLUSIONS: This health economic evaluation alongside the ENCHANTED indicates that the use of low-dose alteplase does not save overall healthcare costs nor lead to a gain in QALYs in the management of Chinese patients with AIS compared to the use of standard dose. There is little justification on economic grounds to shift from standard-of-care thrombolysis in AIS.

Identification of an N-phenylsulfonyl-2-(piperazin-1-yl)methyl-benzonitrile derivative as Zika virus entry inhibitor.

Zika virus (ZIKV) infection could cause severe neurological complications such as neonatal microcephaly, Guillain-Barré syndrome, and myelitis in adults. No vaccine or therapeutic drug is available for prevention and control of ZIKV infection yet. Based on previously reported anti-ZIKV hit compound 1, a series of novel N-benzoyl or phenylsulfonyl substituted 2-(piperazin-1-yl)methyl-benzonitrile (PMBN) derivatives was designed, synthesized, and investigated for the antiviral activity against ZIKV replication in different cell-based phenotypic assays. The results indicated that N-phenylsulfonyl-PMBN derivative 24 displayed the comparable antiviral activity and higher oral availability than hit compound 1. Meanwhile, mechanism of action study confirmed that compound 24 acts on the early entry stage of ZIKV life cycle. The identification of this new ZIKV entry inhibitor chemotype provided a promising lead for further optimization to develop new drug for ZIKV infection.

GIMICA: host genetic and immune factors shaping human microbiota.

Besides the environmental factors having tremendous impacts on the composition of microbial community, the host factors have recently gained extensive attentions on their roles in shaping human microbiota. There are two major types of host factors: host genetic factors (HGFs) and host immune factors (HIFs). These factors of each type are essential for defining the chemical and physical landscapes inhabited by microbiota, and the collective consideration of both types have great implication to serve comprehensive health management. However, no database was available to provide the comprehensive factors of both types. Herein, a database entitled 'Host Genetic and Immune Factors Shaping Human Microbiota (GIMICA)' was constructed. Based on the 4257 microbes confirmed to inhabit nine sites of human body, 2851 HGFs (1368 single nucleotide polymorphisms (SNPs), 186 copy number variations (CNVs), and 1297 non-coding ribonucleic acids (RNAs)) modulating the expression of 370 microbes were collected, and 549 HIFs (126 lymphocytes and phagocytes, 387 immune proteins, and 36 immune pathways) regulating the abundance of 455 microbes were also provided. All in all, GIMICA enabled the collective consideration not only between different types of host factor but also between the host and environmental ones, which is freely accessible without login requirement at: https://idrblab.org/gimica/.

A double-cycle echo state network topology for time series prediction.

Echo state network (ESN) has gained wide acceptance in the field of time series prediction, relying on sufficiently complex reservoir connections to remember the historical features of the data and using these features to obtain the outputs by a simple linear readout. However, the randomness of its input and reservoir connections pose negative impacts on the prediction performance and performance stability of the models, the complexity of reservoir connections brings high time consumption during network computing, and the presence of randomness and complexity makes the hardware implementation of the ESN difficult. In response, we propose a double-cycle ESN (DCESN) based on the Li-ESN model, which has fixed weights to improve prediction performance and performance stability and simpler reservoir connections compared to the classical ESN to reduce the time consumption. The existence of both greatly reduces the difficulty of hardware implementation of the ESN and provides many conveniences for the future application of the ESN. Experimental results on many widely used time series datasets show that the DCESN has comparable or even better prediction performance than the ESN and good robustness against noise and parameter fluctuations.

Mild cognitive impairment among rural-dwelling older adults in China: A community-based study.

BACKGROUND: Epidemiological studies of mild cognitive impairment (MCI) and subtypes of MCI have rarely focused on rural residents in China. METHODS: This population-based study included 5068 participants (age ≥60 years) who were living in rural communities. We defined MCI, amnestic MCI (aMCI), and non-amnestic MCI (naMCI) following the Petersen's criteria that integrated neuropsychological assessments with in-person clinical evaluations. RESULTS: The overall prevalence of MCI, aMCI, and naMCI was 26.48%, 22.30%, and 4.18%, respectively. The prevalence of MCI increased with age. The adjusted odds ratio (OR) of MCI was 0.71 (95% confidence interval [CI] 0.61 to 0.82) for primary school (vs. illiteracy), 0.30 (0.24 to 0.39) for middle school or above, 1.35 (1.09 to 1.67) for being farmers, 0.65 (0.54 to 0.78) for alcohol consumption, 1.43 (1.20 to 1.70) for stroke history, and 1.14 (0.95 to 1.36) for any apolipoprotein E (APOE) ε4 allele (vs ε3/ε3). CONCLUSIONS: MCI affects over one-fourth of rural older adults in China. Overall MCI was associated with demographic factors, non-alcohol consumption, and stroke, but not with APOE genotype and cardiometabolic factors.

Diagnosis of Potomac horse fever (syn. equine neorickettsiosis) in 2 foals in southwestern Ontario.

Potomac horse fever (PHF) is characterized by fever, depression, anorexia, ileus, diarrhea, and occasionally, laminitis. The disease is caused by infection with Neorickettsia risticii and/or N. findlayensis. Equids of all ages may be affected; however, the condition has not been well-characterized in foals. This report describes clinical signs, laboratory findings, and treatment of 2 foals diagnosed with PHF in southwestern Ontario. Feces submitted for an equine PCR panel tested positive for Neorickettsia spp. and were subsequently confirmed to be N. risticii (Case 1) and N. findlayensis (Case 2). Both foals recovered following hospitalization and intensive care. Key clinical message: The purpose of this report is to make veterinarians aware that foals may develop PHF. During summer (July to September), when encountering foals in endemic areas with clinical signs compatible with PHF, veterinarians should consider PHF as a diagnostic rule-out. For confirmation of the diagnosis, blood and feces should be submitted for PCR testing for Neorickettsia spp.

Diagnostic de la fièvre équine du Potomac (syn. néorickettsiose équine) chez 2 poulains dans le sud-ouest de l'Ontario. La fièvre équine du Potomac (PHF) se caractérise par de la fièvre, une dépression, de l'anorexie, un iléus, de la diarrhée et, occasionnellement, une fourbure. La maladie est causée par une infection par Neorickettsia risticii et/ou N. findlayensis. Les équidés de tous âges peuvent être atteints; cependant, cette pathologie n'a pas été bien caractérisée chez les poulains. Ce rapport décrit les signes cliniques, les résultats de laboratoire et le traitement de 2 poulains diagnostiqués avec PHF dans le sud-ouest de l'Ontario. Les matières fécales soumises à un panel PCR équin se sont révélées positives pour Neorickettsia spp. et ont ensuite été confirmées comme étant positives pour N. risticii (cas 1) et N. findlayensis (cas 2). Les deux poulains se sont rétablis après une hospitalisation et des soins intensifs.Message clinique clé :Le but de ce rapport est de sensibiliser les vétérinaires au fait que les poulains peuvent développer une PHF. Pendant l'été (juillet à septembre), lorsqu'ils rencontrent des poulains dans des zones d'endémie présentant des signes cliniques compatibles avec le PHF, les vétérinaires doivent considérer le PHF comme une exclusion diagnostique. Pour confirmer le diagnostic, du sang et des selles doivent être soumis à un test PCR pour Neorickettsia spp.(Traduit par Dr Serge Messier).

A novel conservative system with hidden flows evolved from the simplest memristive circuit.

Over the past few decades, the research of dissipative chaotic systems has yielded many achievements in both theory and application. However, attractors in dissipative systems are easily reconstructed by the attacker, which leads to information security problems. Compared with dissipative systems, conservative ones can effectively avoid these reconstructing attacks due to the absence of attractors. Therefore, conservative systems have advantages in chaos-based applications. Currently, there are still relatively few studies on conservative systems. For this purpose, based on the simplest memristor circuit in this paper, a non-Hamiltonian 3D conservative system without equilibria is proposed. The phase volume conservatism is analyzed by calculating the divergence of the system. Furthermore, a Kolmogorov-type transformation suggests that the Hamiltonian energy is not conservative. The most prominent property in the conservative system is that it exhibits quasi-periodic 3D tori with heterogeneous coexisting and different amplitude rescaling trajectories triggered by initial values. In addition, the results of Spectral Entropy analysis and NIST test show that the system can produce pseudo-random numbers with high randomness. To the best of our knowledge, there is no 3D conservative system with such complex dynamics, especially in a memristive conservative system. Finally, the analog circuit of the system is designed and implemented to test its feasibility as well.

Comprehensive Molecular Characterization of the Mitochondrial Genome of the Takin Lungworm Varestrongylus eleguneniensis (Strongylida: Protostrongylidae).

The takin lungworm Varestrongylus eleguneniensis (Strongylida: Protostrongylidae) causes lethal bronchopneumonia and represents severe threats to captive and wild populations. However, until now there has been very limited information available concerning the molecular epidemiology and evolutionary biology of V. eleguneniensis. Mitochondrial genomes (mtDNAs) can provide resources for investigations in these areas and, therefore, can assist with the surveillance and control of this lungworm. Herein, the complete mtDNA of V. eleguneniensis was sequenced and characterized with Illumina pipeline analyses. This circular genome (13,625 bp) encoded twelve protein-coding genes (PCGs), two rRNAs, and twenty-two tRNAs, with notable levels of AT and GC skews. Comparative genomics revealed a purifying selection among PCGs, with cox1 and nad6 having the lowest and the highest evolutionary rate, respectively. Genome-wide phylogenies showed a close relationship between V. eleguneniensis and Protostrongylus rufescens in Strongylida. Single gene (PCGs or rRNAs)-based phylogenies indicated that cox1 and nad5 genes shared the same family-level topology with that inferred from genomic datasets, suggesting that both genes could be suitable genetic markers for evolutionary and phylogenetic studies of Strongylida species. This was the first mtDNA of any member of the genus Varestrongylus, and its comprehensive molecular characterization represents a new resource for systematic, population genetic and evolutionary biological studies of Varestrongylus lungworms in wildlife.

Efficacy and safety of liraglutide in type 2 diabetes mellitus patients complicated with coronary artery disease: A systematic review and meta-analysis of randomized controlled trials.

To evaluate the efficacy and safety of liraglutide in patients with Type 2 Diabetes Mellitus (T2DM) complicated with Coronary Artery Disease (CAD), we searched PubMed, Cochrane Library, Embase, China National Knowledge Infrastructure (CNKI), Chinese VIP Information (VIP), Wanfang Database and Chinese Biomedical Literature database (CBM) for relevant randomized controlled trials (RCTs) from inception to 7 October 2020. A total of 18 RCTs including 1557 patients with T2DM complicated with CAD were included. Meta-analysis revealed liraglutide reduced hemoglobin A1c (HbA1c) (WMD = -0.67; 95% CI[-0.94 to -0.39]; P < 0.00001), fasting plasma glucose (FPG) (WMD = -0.80; 95% CI[-1.06 to -0.54]; P < 0.00001) and 2 h plasma glucose (2hPG) (WMD = -1.64; 95% CI[-2.12 to -1.16]; P＜0.00001); improved left ventricular ejection fraction(LVEF) (WMD = 4.79; 95% CI[4.08-5.51]; P < 0.00001), left ventricular end-diastolic diameter (LVEDD) (WMD = -5.70; 95% CI[-6.67 to -4.72]; P＜0.00001), E/A (WMD = 0.13; 95% CI[0.11-0.14]; P < 0.00001) and left ventricular posterior wall thickness (LVPWT) (WMD = -1.86; 95% CI[-2.16 to -1.55]; P < 0.00001); reduced total cholesterol (TC) (WMD = -0.48; 95% CI[-0.56 to -0.39]; P < 0.00001), triglycerides (TG) (WMD = -0.42; 95% CI[-0.59 to -0.26]; P < 0.00001), low-density lipoprotein cholesterol (LDL-C) (WMD = -0.41; 95% CI[-0.55 to -0.26]; P < 0.00001), and increased high-density lipoprotein cholesterol (HDL-C) (WMD = -0.19; 95% CI[0.13-0.24]; P = 0.0005). As for safety assessment, liraglutide did not increase the incidence of hypoglycemia (OR = 0.75, 95% CI[0.32-1.77], P = 0.51) and gastrointestinal (OR = 1.15, 95% CI[0.72-1.85], P = 0.55) events. Consequently, liraglutide had favorable effects on blood glucose, cardiac function, lipid profile and an acceptable safety profile.

Silent Synapse Unsilencing in Hippocampal CA1 Neurons for Associative Fear Memory Storage.

Clarifying learning-induced synaptic plasticity in hippocampal circuits is critical for understanding hippocampal mechanisms of memory acquisition and storage. Many in vitro studies have demonstrated learning-associated plasticity at hippocampal synapses. However, as a neural basis of memory encoding, the nature of synaptic plasticity underlying hippocampal neuronal responses to memorized stimulation remains elusive. Using in vivo whole-cell recording in anaesthetized adult rats and mice, we investigated synaptic activity of hippocampal CA1 pyramidal cells (PCs) in response to a flash of visual stimulation as the conditioned stimulus (CS) in associative fear conditioning. We found that shortly (<3 days) after conditioning, excitatory synaptic responses and spiking responses to the flash CS emerged in a large number (~70%) of CA1 PCs, a neuronal population previously unresponsive to the flash before conditioning. The learning-induced CA1 excitatory responsiveness was further indicated to result from postsynaptic unsilencing at flash-associated silent synapses, with NMDA receptor-gated responses we recently reported in naive animals. Our findings suggest that associative fear learning can induce excitatory responsiveness to the memorized CS in a large population of CA1 neurons, via a process of postsynaptic unsilencing at CA1 silent synapses, which may be critical for hippocampal acquisition and storage of associative memory.

Convolution Kernel Operations on a Two-Dimensional Spin Memristor Cross Array.

In recent years, convolution operations often consume a lot of time and energy in deep learning algorithms, and convolution is usually used to remove noise or extract the edges of an image. However, under data-intensive conditions, frequent operations of the above algorithms will cause a significant memory/communication burden to the computing system. This paper proposes a circuit based on spin memristor cross array to solve the problems mentioned above. First, a logic switch based on spin memristors is proposed, which realizes the control of the memristor cross array. Secondly, a new type of spin memristor cross array and peripheral circuits is proposed, which realizes the multiplication and addition operation in the convolution operation and significantly alleviates the computational memory bottleneck. At last, the color image filtering and edge extraction simulation are carried out. By calculating the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) of the image result, the processing effects of different operators are compared, and the correctness of the circuit is verified.

Salmonella spv locus affects type I interferon response and the chemotaxis of neutrophils via suppressing autophagy.

Salmonella is a facultative intracellular pathogen that can cause significant morbidity and mortality in humans and animals. Salmonella plasmid virulence (spv) gene sequence is a highly conserved 6.8 kb region which exists in the plasmid of most pathogenic Salmonella. Autophagy is a degradation process of unnecessary and dysfunctional cytoplasm components to maintain cellular homeostasis, which could affect host inflammatory responses, such as type I interferon response. Type I interferon response can promote the antibacterial activity of macrophage as well as the secretion of cytokines and neutrophil chemokines. We previously reported that spv locus could suppress autophagy and the aggregation of neutrophils in zebrafish larvae. To explore the influence of spv locus on Salmonella escaping from the innate immune responses and the underlying mechanism, the models of Salmonella enterica serovar Typhimurium infected macrophages in vitro and zebrafish larvae in vivo were used in this study. The interactions among spv locus, autophagy, type I interferon response and the chemotaxis of neutrophils were investigated. Western blot was used to detect the expression levels of autophagy related proteins and RT-qPCR was used to measure the mRNA levels of type I interferon response and the neutrophil chemokines. The chemotaxis of neutrophils were observed by Laser Scanning confocal microscopy. Autophagy agonist Torin 1 was also involved to interfere the autophagy influx. Results showed that spv locus could restrain type I interferon response and the chemotaxis of neutrophils via suppressing autophagy, which provided substantial foundation to study the mechanism of Salmonella escaping the innate immunity.