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mtTB:一个用于肺结核筛查的基于网络的 R/Shiny 应用程序。

mtTB: A Web-Based R/Shiny App for Pulmonary Tuberculosis Screening.

机构信息

Department of Pulmonary and Critical Care Medicine, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, China.

出版信息

Front Cell Infect Microbiol. 2022 Mar 18;12:850279. doi: 10.3389/fcimb.2022.850279. eCollection 2022.

Abstract

Pulmonary tuberculosis caused by Mycobacterium tuberculosis remains a global issue. However, the diagnosis of active pulmonary tuberculosis (TB) remains a challenge in the clinic. Small non-coding RNAs are potential diagnostic biomarkers for pulmonary tuberculosis. However, the current normalization methods are not stable and usually fail to reliably detect differentially expressed sncRNAs. To identify reliable biomarkers for pulmonary tuberculosis screening, we utilized the ratio-based method on the newly discovered mitochondria-derived small RNAs in human peripheral blood mononuclear cells. The prediction model of seven mtRNA biomarkers noteworthily enables the discrimination between pulmonary tuberculosis patients and controls in discovery (AUC = 0.906, 23 patients) and independent validation cohort (AUC = 0.968, 20 patients). Moreover, we present mtTB (https://tuberculosis.shinyapps.io/mtTB/), a novel R Graphical User Interface (GUI) that provides reliable biomarkers for the feasibility of blood-based screening, and produce a more accurate tool for pulmonary tuberculosis diagnosis in real clinical practice.

摘要

由结核分枝杆菌引起的肺结核仍然是一个全球性问题。然而,活动性肺结核(TB)的诊断在临床上仍然是一个挑战。小非编码 RNA 是肺结核的潜在诊断生物标志物。然而,目前的标准化方法并不稳定,通常无法可靠地检测差异表达的 sncRNA。为了确定用于肺结核筛查的可靠生物标志物,我们利用基于比率的方法对人外周血单个核细胞中新发现的线粒体衍生小 RNA 进行分析。七个 mtRNA 标志物的预测模型显著区分了发现队列(AUC=0.906,23 名患者)和独立验证队列(AUC=0.968,20 名患者)中的肺结核患者和对照者。此外,我们还展示了 mtTB(https://tuberculosis.shinyapps.io/mtTB/),这是一个新的 R 图形用户界面(GUI),它提供了用于血液筛查可行性的可靠生物标志物,并为实际临床实践中的肺结核诊断提供了更准确的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a09b/8982078/84fddb1faf27/fcimb-12-850279-g001.jpg

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