Biomedical subjects

Jin Xiong

Publications and source records attributed to Jin Xiong.

2 recordsLinked to original sources

PubMed2026

A Network Pharmacology and Molecular Docking Study of TongBi Formula for Osteoarthritis.

This study applied network pharmacology combined with molecular docking to predict the potential therapeutic targets and molecular mechanisms of TongBi Formula (TBF) in osteoarthritis (OA). Active components and corresponding targets of TBF were retrieved from the traditional Chinese medicine Systems Pharmacology Database and Analysis Platform, while OA-related targets were collected from Online Mendelian Inheritance in Man, GeneCards, DrugBank, and Therapeutic Target Database. A network visualization and analysis software was used to construct compound-target and protein-protein interaction (PPI) networks. Gene Ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery platform. Molecular docking analysis was conducted using a molecular docking software to evaluate the predicted binding affinity between key active compounds and core target proteins. A total of 47 overlapping targets between TBF and OA were identified. PPI network analysis highlighted JUN, RELA, IL6, MAPK1, and IL10 as potential hub targets. Enrichment analysis suggested that TBF may regulate inflammation, lipid metabolism, and multiple intracellular signaling pathways associated with OA progression. Molecular docking results demonstrated favorable predicted binding affinities between core active compounds and key OA-related protein targets. These findings provide a computational framework for understanding the potential mechanisms of TBF against OA and support further experimental validation.

Molecular Docking Simulation↗

PubMed2025

Whole-Genome Conservation Analysis for the Specific and Accurate Detection of Influenza A and B Viruses and Respiratory Syncytial Virus by Quadruplex RT-qPCR.

Influenza virus (Flu) and respiratory syncytial virus (RSV) are the primary pathogens responsible for acute respiratory infections. Both viruses are prone to mutations due to the seasonal epidemic, leading to an increasing rate of false-negative results. In this study, comprehensive meta-analyses of the genomes focusing on most conserved fragments have been performed for the four seasonal influenza viruses (two subtypes of Flu A: H1N1 and H3N2; two subtypes of Flu B: Yamagata and Victoria) and the two types of RSV: RSVA and RSVB), respectively. The most conserved sequences of 200 bp were identified as targets of the designed primer/probe sets for RT-qPCR were screened and optimized. Good sensitivities of the optimized primer/probe sets were obtained with the limits of detections of 2.95, 2.82, 1.57, 2.8, 1.19, and 2.12 copies/reaction for H1N1, H3N2, Yamagata, Victoria, RSVA and RSVB, respectively. Eventually, quadruplex qPCR using the four designed primer/probe sets can achieve simultaneous screening of the four viruses at a single tube. Furthermore, the assay's good performance in detecting target viruses from clinical throat swab samples demonstrated its potential for diagnosis of these viruses. The method, based on the identified conserved sequences and primer/probe sets, can effectively reduce false-negative results and rapidly respond to these viruses during respiratory disease outbreaks, or even before their widespread emergence, which aid in preventing outbreaks and guiding clinical treatment.

Humans↗