Genome Composition and Divergence of the Novel Coronavirus (2019-nCoV) Originating in China.

An in-depth annotation of the newly discovered coronavirus (2019-nCoV) genome has revealed differences between 2019-nCoV and severe acute respiratory syndrome (SARS) or SARS-like coronaviruses. A systematic comparison identified 380 amino acid substitutions between these coronaviruses, which may have caused functional and pathogenic divergence of 2019-nCoV

Analysis of the Composition of Fatty Acids and the Effect of Storage Time on the Fatty Fcids in Edible Cassava Flour

The composition and content of fatty acids in edible cassava flour not only affect its shelf life but also serve as important indicators for evaluating the nutritional quality of cassava flour. In this experiment, edible cassava flour was used as the sample. By optimizing the fatty acid methyl esterification method and gas chromatography conditions, a qualitative and quantitative detection method for fatty acids in edible cassava flour was established. The fatty acid composition in edible cassava flour of different varieties (strains) and different storage times was analyzed and detected. The results showed that gas chromatography could accurately analyze and quantify various fatty acids in edible cassava flour. There was a good linear relationship between the concentrations of palmitic acid, stearic acid, oleic acid, linoleic acid, and linolenic acid in the ranges of 20.0~1000.0, 4.0~400.0, 30.0~1500.0, 10.0~500.0 and 2.0~100.0 μg/mL, respectively, with coefficient of determination (R2) ranging from 0.9992 to 0.9999. The relative standard deviations (RSDs) of sample repeatability ranged from 0.5% to 3.2%. The RSDs of concentration changes after 24 hours of storage at room temperature ranged from 0.7% to 1.1%. The average recovery rates of the five fatty acids in the samples ranged from 88.0% to 105.4%, with average recovery rate RSD ranging from 3.4% to 10.4%, indicating good sample stability, method repeatability, and accuracy. The cassava flour prepared from different edible cassava varieties mainly contained palmitic acid, stearic acid, oleic acid, linoleic acid, and linolenic acid. There were significant differences in fatty acid content among different varieties, and the proportions of the five cassava flour fatty acids (SFA/MUFA/PUFA) were 1:(0.91~1.35):(0.12~0.39). Among them, the content of palmitic acid, oleic acid, linoleic acid, and linolenic acid in 'Huanan 9' cassava flour was significantly higher than other varieties (P<0.05). The content reached 0.7818, 1.088, 0.2967 and 0.0398 mg/g, respectively. However, the content of stearic acid in this variety was the lowest, only 0.0868 mg/g. Ambient temperature storage experiments showed a negative correlation between the content of the five fatty acids and storage time, with oleic acid, linoleic acid, and linolenic acid showing a highly significant negative correlation (P<0.01). The content of five fatty acids reached its lowest level after 12 weeks of storage, and the changes tended to be gradual in the later storage stages. The research results provide a basis for evaluating the composition of fatty acids in edible cassava flour of different varieties (strains) and the changes in fatty acids during the storage process

BASP1 is a prognostic biomarker associated with immunotherapeutic response in head and neck squamous cell carcinoma

BackgroundsImmunotherapy is effective in a subset of head and neck squamous cell carcinoma (HNSCC). However, the unfavorable response rate and inadequate biomarkers for stratifying patients have primarily limited its clinical application. Considering transcriptional factors (TFs) play essential roles in regulating immune activity during HNSCC progression, we comprehensively analyzed the expression alterations of TFs and their prognostic values.MethodsGene expression datasets and clinical information of HNSCC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repository. Then, Brain abundant membrane attached signal protein 1 (BASP1) was screened out of differentially expressed TFs by univariate and multivariate survival analysis. Tumor immune dysfunction and exclusion (TIDE) was applied to analyze the response to immunotherapy of BASP1high/low patients. Meanwhile, GO, KEGG and GSEA analyses were used to enrich the pathways between the BASP1high and BASP1low groups. Single-sample gene set enrichment analysis (ssGSEA), CIBERSORT, EPIC and quanTiseq algorithms were applied to explore immune infiltrations. Also, immune cycle analysis was conducted by ssGSEA. Additionally, lipid peroxidation, glutathione and reactive oxygen species were performed to detect the ferroptosis alternations.ResultsBASP1 was upregulated and associated with poor survival in HNSCC patients. BASP1high patients exhibited better response rates to anti-PD-1 immunotherapy and higher expressions of immune checkpoint inhibitors. GO, KEGG and GSEA analyses indicated that the expression of BASP1 was related to several immune-related pathways and immunogenic ferroptosis signature. The infiltration of activated CD8+ T cells was authenticated to be decreased in BASP1high patients. Furthermore, BASP1 was identified to be positively correlated with T cell dysfunction and immune escape. Moreover, silencing BASP1 triggered ferroptosis in HNSCC cells, representing as increased LDH, lipid peroxidation and ROS levels, and reduced glutathione synthesisConclusionsWe demonstrated that BASP1 suppressed immunogenic ferroptosis to induce immunosuppressive tumor microenvironment. BASP1 plays a critical role in immune response, and might be a promising classifier for selecting HNSCC patients who benefit from current immunotherapy

Molecular and clinical characteristics of ATP1A3-related diseases

ObjectiveWith detailed studies of ATP1A3-related diseases, the phenotypic spectrum of ATP1A3 has greatly expanded. This study aimed to potentially identify the mechanisms by which ATP1A3 caused neurological dysfunction by analyzing the clinical features and phenotypes of ATP1A3-related diseases, and exploring the distribution patterns of mutations in the subregions of the ATP1A3 protein, thus providing new and effective therapeutic approaches.MethodsDatabases of PubMed, Online Mendelian Inheritance in Man, and Human Gene Mutation Database, Wanfang Data, and Embase were searched for case reports of ATP1A3-related diseases. Following case screening, we collected clinical information and genetic testing results of patients, and analyzed the disease characteristics on the clinical phenotype spectrum associated with mutations, genetic characteristics of mutations, and effects of drug therapy.ResultsWe collected 902 clinical cases related to ATP1A3 gene. From the results of previous studies, we further clarified the clinical characteristics of ATP1A3-related diseases, such as alternating hemiplegia of childhood (AHC), rapid-onset dystonia-parkinsonism; cerebellar ataxia, areflexia, pes cavus, optic atrophy, and sensorineural hearing loss syndrome, and relapsing encephalopathy with cerebellar ataxia, frequency of mutations in different phenotypes and their distribution in gene and protein structures, and differences in mutations in different clinical phenotypes. Regarding the efficacy of drug treatment, 80 of the 124 patients with AHC were treated with flunarizine, with an effectiveness rate of ~64.5%.ConclusionsNervous system dysfunction due to mutations of ATP1A3 gene was characterized by a group of genotypic–phenotypic interrelated disease pedigrees with multiple clinical manifestations. The presented results might help guide the diagnosis and treatment of ATP1A3-related diseases and provided new ideas for further exploring the mechanisms of nervous system diseases due to ATP1A3 mutations

An Efficient and Adaptive Reconstructive Homogeneous Block-Based Local Tensor Robust PCA for Feature Extraction of Hyperspectral Images

Model-driven tensor robust principal component analysis (TRPCA) has been widely applied to feature extraction of hyperspectral images (HSIs) and successfully protected two-dimensional spectral contextual information. Nevertheless, the current TRPCA-based feature extraction methods still destroy the underlying spectral and spatial&#x2013;spectral joint contextual features. Moreover, these global iterative algorithms commonly ignore the heterogeneity of different real-world regions, increase the calculation burden, and improve practice operating time. To solve these issues, an efficient reconstructive homogeneous block-based local TRPCA is proposed for low-rank feature extraction, composed of a homogeneous block rebuilder and a local TRPCA low-rank feature extractor. The proposed local TRPCA is a novel data-model-driven algorithm depending on the data regulation. It remains the primary spatial and spectral contextual information and extracts the underlying homogeneity and heterogeneity characteristics of spatial, spectral, and spatial&#x2013;spectral joint variables, which provides more essential features for further research than other model-driven TRPCA models. Furthermore, our local TRPCA feature extractor is an elaborate divide-and-rule model that executes on each homogeneous data block to extract low-rank features adaptively, remarkably decreasing computing cost and time. Experimental results on six hyperspectral datasets demonstrate that the proposed local TRPCA is more adaptive to HSIs and outperforms other state-of-the-art TRPCA-based feature extraction algorithms