Neurocalcin-delta: a potential memory-related factor in hippocampus of obese rats induced by high-fat diet.

Introduction: Aberrant protein expression within the hippocampus has recently been implicated in the pathogenesis of obesity- induced memory impairment.Objectives: The objective of the current study was to search for specific memory-related factors in the hippocampus in obese rats.Methods: Sprague-Dawley (SD) rats were fed either a high-fat (HF) diet or normal-fat (NF) diet for 10 weeks to obtain the control (CON), diet-induced obese rats (DIO) and diet-resistant (DR) rats. D-galactose was injected subcutaneously for 10 weeks to establish model (MOD) rats with learning and memory impairment. After the hippocampus of the rats sampling, the proteome analysis was conducted using two-dimensional get electrophoresis (2-DE) combined with peptide mass fingerprinting (PMF).Results: We found 15 differential proteins that expressed in the hippocampus in rats induced by HF diet from the 2-DE map. In addition, Neurocalcin-delta (NCALD) was nearly down-regulated in the DR rats compared with CON rats and MOD rats, which was further confirmed by Western blot, real-time PCR and ELISA results.Conclusion: Our data demonstrates that the differential memory-related proteins were a reflection of the HF diet, but not potential factors in obesity proneness or obesity resistance. Furthermore, NCALD is proved to be a potential hippocampus-memory related factor related to obesity.Keywords: Diet-induced obesity; diet-resistant; high fat diet; neurocalcin-delta; proteom

Artificial Intelligent Diagnosis and Monitoring in Manufacturing

The manufacturing sector is heavily influenced by artificial intelligence-based technologies with the extraordinary increases in computational power and data volumes. It has been reported that 35% of US manufacturers are currently collecting data from sensors for manufacturing processes enhancement. Nevertheless, many are still struggling to achieve the 'Industry 4.0', which aims to achieve nearly 50% reduction in maintenance cost and total machine downtime by proper health management. For increasing productivity and reducing operating costs, a central challenge lies in the detection of faults or wearing parts in machining operations. Here we propose a data-driven, end-to-end framework for monitoring of manufacturing systems. This framework, derived from deep learning techniques, evaluates fused sensory measurements to detect and even predict faults and wearing conditions. This work exploits the predictive power of deep learning to extract hidden degradation features from noisy data. We demonstrate the proposed framework on several representative experimental manufacturing datasets drawn from a wide variety of applications, ranging from mechanical to electrical systems. Results reveal that the framework performs well in all benchmark applications examined and can be applied in diverse contexts, indicating its potential for use as a critical corner stone in smart manufacturing

MM-Diffusion: Learning Multi-Modal Diffusion Models for Joint Audio and Video Generation

We propose the first joint audio-video generation framework that brings engaging watching and listening experiences simultaneously, towards high-quality realistic videos. To generate joint audio-video pairs, we propose a novel Multi-Modal Diffusion model (i.e., MM-Diffusion), with two-coupled denoising autoencoders. In contrast to existing single-modal diffusion models, MM-Diffusion consists of a sequential multi-modal U-Net for a joint denoising process by design. Two subnets for audio and video learn to gradually generate aligned audio-video pairs from Gaussian noises. To ensure semantic consistency across modalities, we propose a novel random-shift based attention block bridging over the two subnets, which enables efficient cross-modal alignment, and thus reinforces the audio-video fidelity for each other. Extensive experiments show superior results in unconditional audio-video generation, and zero-shot conditional tasks (e.g., video-to-audio). In particular, we achieve the best FVD and FAD on Landscape and AIST++ dancing datasets. Turing tests of 10k votes further demonstrate dominant preferences for our model. The code and pre-trained models can be downloaded at https://github.com/researchmm/MM-Diffusion.Comment: Accepted by CVPR 202

Profile of immunoglobulin G N-glycome in COVID-19 patients: A case-control study

Coronavirus disease 2019 (COVID-19) remains a major health challenge globally. Previous studies have suggested that changes in the glycosylation of IgG are closely associated with the severity of COVID-19. This study aimed to compare the profiles of IgG N-glycome between COVID-19 patients and healthy controls. A case-control study was conducted, in which 104 COVID-19 patients and 104 age- and sex-matched healthy individuals were recruited. Serum IgG N-glycome composition was analyzed by hydrophilic interaction liquid chromatography with the ultra-high-performance liquid chromatography (HILIC-UPLC) approach. COVID-19 patients have a decreased level of IgG fucosylation, which upregulates antibody-dependent cell cytotoxicity (ADCC) in acute immune responses. In severe cases, a low level of IgG sialylation contributes to the ADCC-regulated enhancement of inflammatory cytokines. The decreases in sialylation and galactosylation play a role in COVID-19 pathogenesis via the activation of the lectin-initiated alternative complement pathway. IgG N-glycosylation underlines the complex clinical phenotypes of SARS-CoV-2 infection

Transcription Profiling of a Revealed the Potential Molecular Mechanism of Governor Vessel Electroacupuncture for Spinal Cord Injury in Rats

Objective This study aimed to identify differentially expressed genes (DEGs) by transcriptome analysis to elucidate a potential mechanism by which governor vessel electroacupuncture (GV-EA) promotes neuronal survival, axonal regeneration, and functional recovery after complete transection spinal cord injury (SCI). Methods Sham, control, or GV-EA group adult female Sprague Dawley rats underwent a complete transection SCI protocol. SCI area RNA-seq investigated the DEGs of coding and noncoding RNAs 7 days post-SCI. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses were used to classify DEGs functions, to explain a possible molecular mechanism. Immunofluorescence and BBB (Basso, Beattie, and Bresnahan) score were used to verify a GV-EA treatment effect following SCI. Results GV-EA treatment could regulate the expression of 173 mRNA, 260 lncRNA, and 153 circRNA genes among these DEGs resulted by SCI. GO enrichment analysis showed that the DEGs were most enriched in membrane, actin binding, and regulation of Toll-like receptor signaling pathway. KEGG pathway analysis showed enriched pathways (e.g. , Toll-like receptors, MAPK, Hippo signaling). According to the ceRNA network, miR-144-3p played a regulatory role by interacting with lncRNA and circRNA. GV-EA also promoted the injured spinal cord neuron survival, axonal regeneration, and functional improvement of hind limb locomotion. Conclusion Results of our RNA-seq suggest that post-SCI GV-EA may regulate characteristic changes in transcriptome gene expression, potential critical genes, and signaling pathways, providing clear directions for further investigation into the mechanism of GV-EA in subacute SCI treatment. Moreover, we found that GV-EA promotes neuronal survival, nerve fiber extension, and motor function recovery in subacute SCI

Survey and Visual Detection of Zaire ebolavirus in Clinical Samples Targeting the Nucleoprotein Gene in Sierra Leone

Ebola virus (EBOV) can lead to severe hemorrhagic fever with a high risk of death in humans and other primates. To guide treatment and prevent spread of the viral infection, a rapid and sensitive detection method is required for clinical samples. Here, we described and evaluated a reverse transcription loop-mediated isothermal amplification (RT-LAMP) method to detect Zaire ebolavirus using the nucleoprotein gene (NP) as a target sequence. Two different techniques were used, a calcein/Mn2+ complex chromogenic method and real-time turbidity monitoring. The RT-LAMP assay detected the NP target sequence with a limit of 4.56 copies/μL within 45 min under 61°C, a similar even or increase in sensitivity than that of real-time reverse transcription-polymerase chain reaction (RT-PCR). Additionally, all pseudoviral particles or non- Zaire EBOV genomes were negative for LAMP detection, indicating that the assay was highly specific for EBOV. To appraise the availability of the RT-LAMP method for use in clinical diagnosis of EBOV, of 417 blood or swab samples collected from patients with clinically suspected infections in Sierra Leone, 307 were identified for RT-LAMP-based surveillance of EBOV. Therefore, the highly specific and sensitive RT-LAMP method allows the rapid detection of EBOV, and is a suitable tool for clinical screening, diagnosis, and primary quarantine purposes

Spatial and temporal clustering analysis of tuberculosis in the mainland of China at the prefecture level, 2005-2015

BACKGROUND: Tuberculosis (TB) is still one of the most serious infectious diseases in the mainland of China. So it was urgent for the formulation of more effective measures to prevent and control it. METHODS: The data of reported TB cases in 340 prefectures from the mainland of China were extracted from the China Information System for Disease Control and Prevention (CISDCP) during January 2005 to December 2015. The Kulldorff\u27s retrospective space-time scan statistics was used to identify the temporal, spatial and spatio-temporal clusters of reported TB in the mainland of China by using the discrete Poisson probability model. Spatio-temporal clusters of sputum smear-positive (SS+) reported TB and sputum smear-negative (SS-) reported TB were also detected at the prefecture level. RESULTS: A total of 10 200 528 reported TB cases were collected from 2005 to 2015 in 340 prefectures, including 5 283 983 SS- TB cases and 4 631 734 SS + TB cases with specific sputum smear results, 284 811 cases without sputum smear test. Significantly TB clustering patterns in spatial, temporal and spatio-temporal were observed in this research. Results of the Kulldorff\u27s scan found twelve significant space-time clusters of reported TB. The most likely spatio-temporal cluster (RR = 3.27, P \u3c  0.001) was mainly located in Xinjiang Uygur Autonomous Region of western China, covering five prefectures and clustering in the time frame from September 2012 to November 2015. The spatio-temporal clustering results of SS+ TB and SS- TB also showed the most likely clusters distributed in the western China. However, the clustering time of SS+ TB was concentrated before 2010 while SS- TB was mainly concentrated after 2010. CONCLUSIONS: This study identified the time and region of TB, SS+ TB and SS- TB clustered easily in 340 prefectures in the mainland of China, which is helpful in prioritizing resource assignment in high-risk periods and high-risk areas, and to formulate powerful strategy to prevention and control TB

Agromyces chromiiresistens sp. nov., Novosphingobium album sp. nov., Sphingobium arseniciresistens sp. nov., Sphingomonas pollutisoli sp. nov., and Salinibacterium metalliresistens sp. nov.: five new members of Microbacteriaceae and Sphingomonadaceae from polluted soil

There are many unidentified microbes in polluted soil needing to be explored and nominated to benefit the study of microbial ecology. In this study, a taxonomic research was carried out on five bacterial strains which were isolated and cultivated from polycyclic aromatic hydrocarbons, and heavy metals polluted soil of an abandoned coking plant. Phylogenetical analysis showed that they belonged to the phyla Proteobacteria and Actinobacteria, and their 16S rRNA gene sequence identities were lower than 98.5% to any known and validly nominated bacterial species, suggesting that they were potentially representing new species. Using polyphasic taxonomic approaches, the five strains were classified as new species of the families Microbacteriaceae and Sphingomonadaceae. Genome sizes of the five strains ranged from 3.07 to 6.60 Mb, with overall DNA G+C contents of 63.57–71.22 mol%. The five strains had average nucleotide identity of 72.38–87.38% and digital DNA-DNA hybridization of 14.0–34.2% comparing with their closely related type strains, which were all below the thresholds for species delineation, supporting these five strains as novel species. Based on the phylogenetic, phylogenomic, and phenotypic characterizations, the five novel species are proposed as Agromyces chromiiresistens (type strain H3Y2-19aT = CGMCC 1.61332T), Salinibacterium metalliresistens (type strain H3M29-4T = CGMCC 1.61335T), Novosphingobium album (type strain H3SJ31-1T = CGMCC 1.61329T), Sphingomonas pollutisoli (type strain H39-1-10T = CGMCC 1.61325T), and Sphingobium arseniciresistens (type strain H39-3-25T = CGMCC 1.61326T). Comparative genome analysis revealed that the species of the family Sphingomonadaceae represented by H39-1-10T, H39-3-25T, and H3SJ31-1T possessed more functional protein-coding genes for the degradation of aromatic pollutants than the species of the family Microbacteriaceae represented by H3Y2-19aT and H3M29-4T. Furthermore, their capacities of resisting heavy metals and metabolizing aromatic compounds were investigated. The results indicated that strains H3Y2-19aT and H39-3-25T were robustly resistant to chromate (VI) and/or arsenite (III). Strains H39-1-10T and H39-3-25T grew on aromatic compounds, including naphthalene, as carbon sources even in the presence of chromate (VI) and arsenite (III). These features reflected their adaptation to the polluted soil environment