The asymmetric expression of plasma membrane H+-ATPase family genes in response to pulvinus-driven leaf phototropism movement in Vitis vinifera.

Phototropism movement is crucial for plants to adapt to various environmental changes. Plant P-type H+-ATPase (HA) plays diverse roles in signal transduction during cell expansion, regulation of cellular osmotic potential and stomatal opening, and circadian movement. Despite numerous studies on the genome-wide analysis of Vitis vinifera, no research has been done on the P-type H+-ATPase family genes, especially concerning pulvinus-driven leaf movement. In this study, 55 VvHAs were identified and classified into nine distinct subgroups (1 to 9). Gene members within the same subgroups exhibit similar features in motif, intron/exon, and protein tertiary structures. Furthermore, four pairs of genes were derived by segmental duplication in grapes. Cis-acting element analysis identified numerous light/circadian-related elements in the promoters of VvHAs. qRT-PCR analysis showed that several genes of subgroup 7 were highly expressed in leaves and pulvinus during leaf movement, especially VvHA14, VvHA15, VvHA16, VvHA19, VvHA51, VvHA52, and VvHA54. Additionally, we also found that the VvHAs genes were asymmetrically expressed on both sides of the extensor and flexor cell of the motor organ, the pulvinus. The expression of VvHAs family genes in extensor cells was significantly higher than that in flexor cells. Overall, this study serves as a foundation for further investigations into the functions of VvHAs and contributes to the complex mechanisms underlying grapevine pulvinus growth and development.

Financial distress prediction using integrated Z-score and multilayer perceptron neural networks.

The COVID-19 pandemic led to a great deal of financial uncertainty in the stock market. An initial drop in March 2020 was followed by unexpected rapid growth over 2021. Therefore, financial risk forecasting continues to be a central issue in financial planning, dealing with new types of uncertainty. This paper presents a stock market forecasting model combining a multi-layer perceptron artificial neural network (MLP-ANN) with the traditional Altman Z-Score model. The contribution of the paper is presentation of a new hybrid enterprise crisis warning model combining Z-score and MLP-ANN models. The new hybrid default prediction model is demonstrated using Chinese data. The results of empirical analysis show that the average correct classification rate of thew hybrid neural network model (99.40%) is higher than that of the Altman Z-score model (86.54%) and of the pure neural network method (98.26%). Our model can provide early warning signals of a company's deteriorating financial situation to managers and other related personnel, investors and creditors, government regulators, financial institutions and analysts and others so that they can take timely measures to avoid losses.

Identification of biomarkers related to angiogenesis in myocardial ischemia-reperfusion injury and prediction of potential drugs.

Myocardial ischemia-reperfusion injury (MIRI) refers to the secondary damage to myocardial tissue that occurs when blood perfusion is rapidly restored following myocardial ischemia. This process often exacerbates the injury to myocardial fiber structure and function. The activation mechanism of angiogenesis is closely related to MIRI and plays a significant role in the occurrence and progression of ischemic injury. In this study, we utilized sequencing data from the GEO database and employed WGCNA, Mfuzz cluster analysis, and protein interaction network to identify Stat3, Rela, and Ubb as hub genes involved in MIRI-angiogenesis. Additionally, the GO and KEGG analysis of differentially expressed genes highlighted their broad participation in inflammatory responses and associated signaling pathways. Moreover, the analysis of sequencing data and hub genes revealed a notable increase in the infiltration ratio of monocytes and activated mast cells. By establishing key cell ROC curves, using independent datasets, and validating the expression of hub genes, we demonstrated their high diagnostic value. Moreover, by scrutinizing single-cell sequencing data alongside trajectory analysis, it has come to light that Stat3 and Rela exhibit predominant expression within Dendritic cells. In contrast, Ubb demonstrates expression across multiple cell types, with all three genes being expressed at distinct stages of cellular development. Lastly, leveraging the CMap database, we predicted potential small molecule compounds for the identified hub genes and validated their binding activity through molecular docking. Ultimately, our research provides valuable evidence and references for the early diagnosis and treatment of MIRI from the perspective of angiogenesis.

Integrating machine learning and single-cell transcriptomic analysis to identify potential biomarkers and analyze immune features of ischemic stroke.

This study employs machine learning and single-cell transcriptome sequencing (scRNA-seq) analysis to unearth novel biomarkers and delineate the immune characteristics of ischemic stroke (IS), thereby contributing fresh insights into IS treatment strategies.Our research leverages gene expression data sourced from the GEO database. We undertake weighted gene co-expression network analysis (WGCNA) to filter pertinent genes and subsequently employ machine learning algorithms for the identification of feature genes. Concurrently, we rigorously execute quality control measures, dimensionality reduction techniques, and cell annotation on the scRNA-seq data to pinpoint differentially expressed genes (DEGs). The identification of core genes, denoted as Hub genes, among the feature genes and DEGs, is achieved through meticulous overlapping analysis. We illuminate the immune characteristics of these Hub genes using a suite of analytical tools, encompassing CIBERSORT, MCPcounter, and pseudotemporal analysis, all based on immune cell annotations and single-cell transcriptome data.Subsequently, we harness the CMap database to prognosticate potential therapeutic drugs and scrutinize their associations with the identified Hub genes. Our findings unveil robust linkages between three pivotal Hub genes-namely, RNF13, VASP, and CD163-and specific immune cell types such as T cells and neutrophils. These Hub genes predominantly manifest in macrophages and microglial cells within the scRNA-seq immune cell population, exhibiting variances across different stages of cellular differentiation. In conclusion, this study unearths highly pertinent biomarkers for IS diagnosis and elucidates IS-induced immune infiltration characteristics, thus providing a firm foundation for a comprehensive exploration of potential immune mechanisms and the identification of novel therapeutic targets for IS.

Effectiveness and safety of Tai Chi for anxiety disorder of COVID-19: A protocol of systematic review and meta-analysis.

BACKGROUND: Anxiety disorders pose a significant threat to the clinical rehabilitation of patients with coronavirus disease 2019 (COVID-19). Tai Chi is a therapeutic exercise that can be used to treat anxiety disorders. We aim to conduct a systematic review and meta-analysis to evaluate the effectiveness and safety of Tai Chi for treating patients with anxiety disorders caused by COVID-19. METHODS: The PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure, Chinese Biomedical Literature, Wan Fang, and Chinese Clinical Trial Registry databases will be searched for reports of randomized controlled trials on Tai Chi for the treatment of anxiety disorders caused by COVID-19, published from December 1, 2019, to August 22, 2022. Two researchers will screen the articles and extract the relevant information. RESULTS: The results will provide a systematic overview of the current evidence on the use of Tai Chi to treat anxiety disorders caused by COVID-19 among patients. CONCLUSION: The conclusions of this study will help clarify whether Tai Chi is effective and safe for treating anxiety disorders caused by COVID-19.

Molecular Phylogeny of Geographical Isolates of Bursaphelenchus xylophilus: Implications on the Origin and Spread of this Species in China and Worldwide.

The genetic diversity and phylogeny of 26 isolates of Bursaphelenchus xylophilus from China, Japan, Portugal and North America were investigated based on the D2/3 domain of 28S rDNA, nuclear ribosomal Internal Transcribed Spacer (ITS) sequences, and random amplified polymorphic DNA (RAPD) analysis. The genetic diversity analysis showed that the D2/3 domain of 28S rDNA of isolates of B. xylophilus from China, Portugal, Japan and the US were identical and differed at one to three nucleotides compared to those from Canada. ITS sequences of isolates from China and Portugal were the same; they differed at one or two nucleotides compared to those of Japanese isolates and at four and 23 nucleotides compared to those from the US and Canada, respectively. The phylogenetic analysis indicated that Chinese isolates share a common ancestor with one of the two Japanese clades and that the Canadian isolates form a sister group of the clade comprised of isolates from China, Portugal, Japan, and the US. The relationship between Japanese isolates and those from China was closer than with the American isolates. The Canadian isolates were the basal group of B. xylophilus. This suggests that B. xylophilus originated in North America and that the B. xylophilus that occurs in China could have been first introduced from Japan. Further analysis based on RAPD analysis revealed that the relationship among isolates from Guangdong, Zhejiang, Shandong, Anhui provinces and Nanjing was the closest, which suggests that pine wilt disease in these Chinese locales was probably dispersed from Nanjing, where this disease first occurred in China.

Nested case-control study on the risk factors of colorectal cancer.

AIM: To investigate the risk factors of colon cancer and rectal cancer. METHODS: A nested case-control study was conducted in a cohort of 64 693 subjects who participated in a colorectal cancer screening program from 1989 to 1998 in Jiashan county, Zhejiang, China. 196 cases of colorectal cancer were detected from 1990 to 1998 as the case group and 980 non-colorectal cancer subjects, matched with factors of age, gender, resident location, were randomly selected from the 64 693 cohort as controls. By using univariate analysis and multivariate conditional logistic regression analysis, the odds ratio (OR) and its 95 % confidence interval (95 %CI) were calculated between colorectal cancer and personal habits, dietary factors, as well as intestinal related symptoms. RESULTS: The multivariate analysis results showed that after matched with age, sex and resident location, mucous blood stool history and mixed sources of drinking water were closely associated with colon cancer and rectal cancer, OR values for the mucous blood stool history were 3.508 (95 %CI: 1.370-8.985) and 2.139 (95 %CI: 1.040-4.402) respectively; for the mixed drinking water sources, 2.387 (95 %CI: 1.243-4.587) and 1.951 (95 %CI: 1.086-3.506) respectively. All reached the significant level with a P-value less than 0.05. CONCLUSION: The study suggested that mucous blood stool history and mixed sources of drinking water were the risk factors of colon cancer and rectal cancer. There was no any significant association between dietary habits and the incidence of colorectal cancer.