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Biomedical subjects

Yubo Wang

Publications and source records attributed to Yubo Wang.

2 recordsLinked to original sources

Effects of exercise snacking on neuromuscular performance in insufficiently active adults: A systematic review and meta-analysis.

OBJECTIVE: To examine the effects of exercise snacking (ES) on neuromuscular performance in insufficiently active adults. METHODS: Six databases were searched from inception to July 17, 2026. Randomized controlled trials and non-randomized studies of interventions involving insufficiently active adults undertaking ES interventions were included. Outcomes were functional performance, muscular strength, and muscular power. A three-level random-effects meta-analysis was performed. Risk of bias was assessed with RoB 2 or ROBINS-I, and certainty of evidence was evaluated using GRADE. RESULTS: Nine studies (13 reports) involving 313 participants were included. In the primary three-level model, ES showed a small positive overall effect on neuromuscular performance (g = 0.37, 95% CI 0.16-0.58, p = 0.001), which remained supported under trial-clustered robust inference with small-sample adjustment. Domain-specific estimates for muscular power/velocity, functional performance, and muscular strength were positive but imprecise and were not statistically supported after small-sample robust adjustment. Robust moderator tests provided no evidence of between-subgroup differences, and the certainty of evidence was low for all outcomes. CONCLUSION: Current low-certainty evidence suggests that ES may produce a small improvement in overall neuromuscular performance. However, domain-specific effects remain uncertain because of the limited number of independent trials, and the overall prediction interval crossed zero, indicating uncertainty across future populations and settings. Larger, preregistered randomized controlled trials are needed to confirm these preliminary findings.

Adult

Machine learning algorithm-based biomarker exploration and validation of mitochondria-related diagnostic genes in osteoarthritis.

The role of mitochondria in the pathogenesis of osteoarthritis (OA) is significant. In this study, we aimed to identify diagnostic signature genes associated with OA from a set of mitochondria-related genes (MRGs). First, the gene expression profiles of OA cartilage GSE114007 and GSE57218 were obtained from the Gene Expression Omnibus. And the limma method was used to detect differentially expressed genes (DEGs). Second, the biological functions of the DEGs in OA were investigated using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Wayne plots were employed to visualize the differentially expressed mitochondrial genes (MDEGs) in OA. Subsequently, the LASSO and SVM-RFE algorithms were employed to elucidate potential OA signature genes within the set of MDEGs. As a result, GRPEL and MTFP1 were identified as signature genes. Notably, GRPEL1 exhibited low expression levels in OA samples from both experimental and test group datasets, demonstrating high diagnostic efficacy. Furthermore, RT-qPCR analysis confirmed the reduced expression of Grpel1 in an in vitro OA model. Lastly, ssGSEA analysis revealed alterations in the infiltration abundance of several immune cells in OA cartilage tissue, which exhibited correlation with GRPEL1 expression. Altogether, this study has revealed that GRPEL1 functions as a novel and significant diagnostic indicator for OA by employing two machine learning methodologies. Furthermore, these findings provide fresh perspectives on potential targeted therapeutic interventions in the future.

Humans