ABSTRACT
MOTIVATION: High-throughput sequencing technologies have greatly facilitated microbiome research and have generated a large volume of microbiome data with the potential to answer key questions regarding microbiome assembly, structure and function. Cluster analysis aims to group features that behave similarly across treatments, and such grouping helps to highlight the functional relationships among features and may provide biological insights into microbiome networks. However, clustering microbiome data are challenging due to the sparsity and high dimensionality. RESULTS: We propose a model-based clustering method based on Poisson hurdle models for sparse microbiome count data. We describe an expectation-maximization algorithm and a modified version using simulated annealing to conduct the cluster analysis. Moreover, we provide algorithms for initialization and choosing the number of clusters. Simulation results demonstrate that our proposed methods provide better clustering results than alternative methods under a variety of settings. We also apply the proposed method to a sorghum rhizosphere microbiome dataset that results in interesting biological findings. AVAILABILITY AND IMPLEMENTATION: R package is freely available for download at https://cran.r-project.org/package=PHclust. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Subject(s)
Algorithms , Microbiota , Computer Simulation , Cluster Analysis , High-Throughput Nucleotide Sequencing/methods , SoftwareABSTRACT
BACKGROUND: This study will assess the efficacy and safety of Shenmai injection (SMI) for the treatment of chronic heart failure (CHF). METHODS: The following electronic bibliographic databases will be searched from inception to the March 25, 2020 without language and publication time limitations: MEDLINE, PUBMED, Cochrane Library, Web of Science, Scopus, WANGFANG, Chinese Biomedical Literature Database, and China National Knowledge Infrastructure. All randomized controlled trials related to the SMI for patients with CHF will be included. All study selection, data extraction, and study quality will be carried out by 2 reviewers. Any disagreements will be solved by a third reviewer through discussion. RevMan 5.3 software will be used for data synthesis and data analysis. RESULTS: This study will summarize the present evidence of SMI for the treatment of patients with CHF. CONCLUSION: The findings of this study will determine whether SMI is effective and safety for the treatment of CHF or not. STUDY REGISTRATION NUMBER: INPLASY202050029.
Subject(s)
Drugs, Chinese Herbal/therapeutic use , Heart Failure/drug therapy , Chronic Disease/drug therapy , Chronic Disease/mortality , Drug Combinations , Heart Failure/mortality , Humans , Injections , Research Design , Sodium/blood , Systematic Reviews as Topic , UrineABSTRACT
BACKGROUND: This study will assess the effect of Xingnaojing injection (XNJI) for the treatment of acute alcoholism (AAH). METHODS: The bibliographic literature sources will be systematically searched in MEDLINE, EMBASE, Cochrane Library, China National Knowledge Infrastructure Database, Wan fang Database, and VIP Science Technology Periodical Database. All above electronic databases will be sought from inception to the April 1, 2020. We will not apply any limitations to language and publication time. In addition, we will also search other literature sources. Two reviewers will carry out study selection, data extraction, and methodological quality evaluation, respectively. Any divergences will be resolved by a third reviewer through discussion. We will use RevMan 5.3 software to analyze data analysis. RESULTS: This study will summarize present evidence to assess the effect of XNJI for the treatment of AAH. CONCLUSION: This study will investigate whether XNJI is effective and safety for AAH. SYSTEMATIC REVIEW REGISTRATION: INPLASY202040197.
Subject(s)
Alcoholic Intoxication/drug therapy , Drugs, Chinese Herbal/pharmacology , Humans , Injections , Meta-Analysis as Topic , Research Design , Systematic Reviews as Topic , Treatment OutcomeABSTRACT
The aim of this study was to explore how atrial natriuretic polypeptide (ANP) affects the properties and function of endothelial cells. Gene expression data GSE56976 generated at 0, 1, and 6 hours after ANP incubation in human umbilical vein endothelial cells (HUVEC) was used. Microarray data were preprocessed for differentially expressed genes (DEGs) in each time-dependent group. Next, gene ontology (GO), pathway analysis, and transcriptional regulation were performed. Co-expression clustering analysis of DEGs and functional enrichment analysis of co-expression modules were processed. RT-PCR analysis was performed to validate gene expression. DEGs were obtained and their counts were increased from 0 hours to 6 hours. No overlapping DEGs were obtained among the 3 groups. The DEGs of ANP_6hours, including TGFB2 (transforming growth factor, beta 2), LTF (lactotransferrin/lactoferrin), and ETV7 (Ets variant 7) were mainly related with cell apoptosis and immune responses. The DEGs in the network of ANP_0hour were mainly associated with epithelial ion transport processes. In addition, 3 co-expressed modules were detected. CSF2 (colony stimulating factor 2) and PF4 (platelet factor 4) of the blue module were related with cytolysis, while FXYD1 (FXYD domain containing ion transport regulator 1) and TGFB2 of the yellow module were mainly enriched in ion transport and the ovulation cycle. The expression of TGFB2 obtained by microarray analysis was consistent with that of RT-PCR. Ion transport could be affected promptly after ANP treatment, and subsequently, the cytolysis of vein endothelial cells may be promoted and endothelial permeability would be enhanced, followed by activated immune responses.