Biomedical subjects

Hao Lin

Publications and source records attributed to Hao Lin.

5 recordsLinked to original sources

PubMed2026

Comparative Effectiveness of Exercise Interventions for Hamstring Injury Prevention in Football Players: A Systematic Review and Network Meta-analysis.

BACKGROUND: Hamstring strain injury is a leading time-loss injury in football, yet trials have evaluated diverse exercise-based prevention programs with limited direct head-to-head evidence. This systematic review and network meta-analysis aimed to compare the effectiveness of exercise-based interventions for preventing hamstring injuries in football players using exposure-adjusted incidence rate ratios. METHODS: We conducted a PRISMA-aligned systematic review and random-effects network meta-analysis of randomized controlled trials in football players comparing exercise-based interventions to prevent hamstring injuries. Searches covered PubMed, Cochrane Library, Embase and Web of Science from inception to January 5, 2026. Interventions were modeled as separate nodes (Nordic hamstring exercise [NHE], FIFA 11, FIFA 11 + , FIFA 11 + Kids, bounding exercise program [BEP], usual training). The primary effect measure was incidence rate ratio (IRR) versus usual training, with ranking by P-scores; exploratory subgroup analyses were conducted by sex-restricted male-only evidence and age group. RESULTS: Eleven randomized controlled trials involving 9,282 participants were included. The network was connected but largely star-shaped, with most evidence comparing active interventions against usual training and no direct active-active comparisons. FIFA 11 + showed the most consistent exposure-adjusted association with reduced hamstring injury incidence versus usual training (IRR = 0.55, 95% CI 0.31-0.98; P-score = 0.84). FIFA 11 + Kids showed a favorable but imprecise estimate, whereas NHE showed a modest non-significant reduction and FIFA 11 and BEP showed no clear benefit. Male-only findings were broadly consistent with the primary analysis. Age-stratified analyses suggested that the apparent hierarchy was not fully identical across age strata, but subgroup networks were sparse and exploratory. RoB 2 judged three studies as high risk and eight as having some concerns; no trial was judged as overall low risk. Between-study heterogeneity was substantial, and treatment rankings were, therefore, interpreted cautiously. CONCLUSIONS: In this IRR-based network meta-analysis, FIFA 11 + showed the most consistent exposure-adjusted association with reduced hamstring injury incidence compared with usual training. However, certainty across the primary comparisons ranged from low to very low because of clinical and methodological heterogeneity, sparse direct evidence for several nodes, reliance on indirect active-active comparisons, substantial between-study heterogeneity, and moderate-to-high risk of bias across the included studies. The treatment hierarchy should, therefore, be interpreted as a low-to-very-low-certainty, population-level summary rather than as a basis for firm recommendations. Further well-reported, age- and population-specific head-to-head trials with consistent exposure, injury-definition, adherence, and intervention-dose reporting are needed. Registration Systematic review registration PROSPERO (CRD420251243576).

FIFA 11 + ↗

PubMed2026

Essence: A benchmarking-validated transformer framework for early diagnosis of Parkinson's disease using cerebrospinal fluid protein biomarkers.

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by motor and non-motor symptoms. The lack of objective molecular biomarkers limits early diagnosis and personalized treatment. Here, we propose Essence, a benchmarking-validated framework integrating cerebrospinal fluid (CSF) proteomics with traditional and deep learning models to identify robust protein signatures for PD. Using data from two independent cohorts, 1266 high-confidence proteins are quantified, among which 178 exhibit differential abundance between PD and healthy controls (HC). Through systematic benchmarking of ten machine learning algorithms and four neural architectures, the Transformer model consistently outperforms alternatives across multiple feature selection strategies, achieving an area under the receiver operating characteristic curve (AUC) of 1.0000 with only 35 features. Functional analyses of the top-ranked 35 proteins reveal enrichment in neuroinflammatory, synaptic, and oxidative stress-related pathways. Importantly, spatial transcriptomic profiling based on the Allen Brain Atlas shows region-specific expression of these biomarkers in PD-relevant brain structures, including the striatum, subthalamic nucleus, hippocampus, and white matter tracts. This anatomical alignment supports the functional relevance of the identified markers and highlights their potential utility in early-stage diagnosis and mechanistic understanding of PD.

Benchmarking↗

PubMed2025

Colorectal Liver Metastasis Pathomics Model: Integrating Single-Cell and Spatial Transcriptome Analysis With Pathomics for Predicting Liver Metastasis in Colorectal Cancer.

The liver is the primary target organ for hematologic metastasis of colorectal cancer (CRC), and CRC liver metastasis (CRLM) often precludes radical resection, making it the leading cause of death in patients with CRC. To improve the identification and prediction of liver metastasis risk, we identified a cell type of liver metastasis--triggering malignant cells (LMTMCs) through integrating single-cell RNA sequencing and spatial transcriptome analysis. Multiomics cell communication analysis indicated that the interaction between fibroblasts and LMTMCs through the COL1A1-CD44/SDC4 and LAMA4-CD44 signaling axes could promote CRLM. By applying the one-class logistic regression algorithm, we developed a CRLM scoring system in the bulk RNA-sequencing data according to the abundance of LMTMCs in each individual. Using the grouping labels derived from the CRLM scoring system in the bulk data and the corresponding whole-slide images without any manual annotations at the region or pixel level, processed via slide-level weakly supervised learning, a deep-learning model based on the ResNet18 architecture, called Colorectal Liver Metastasis Pathomics Model, was developed to predict the risk of liver metastasis in patients with CRC. The Colorectal Liver Metastasis Pathomics Model achieved an area under the curve of 0.84 at the internal test set of The Cancer Genome Atlas-CRC histology images. In the external independent validation sets, namely the Affiliated Hospital of Southwest Medical University and the Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University cohorts, the areas under the curve were 0.89 and 0.72, respectively, indicating effective classification performances. This study provided new insights and tools for the early identification of CRLM and demonstrated the potential of combining multiomics with deep learning-based pathomics in cancer research.

Humans↗

PubMed2025

CCT8 drives colorectal cancer progression via the RPL4-MDM2-p53 axis and immune modulation.

PURPOSE: Colorectal cancer (CRC) ranks high in global mortality, emphasizing the need for effective interventions. The aim of the research is to elucidate the oncogenic role of CCT8 in CRC and its interaction with RPL4 in the RPL4-MDM2-p53 axis. METHODS: TIMER 2.0, TCGA, and GTEx databases were used to analyze CCT8 expression patterns in CRC. Immunohistochemistry was performed to examine CCT8 distribution in CRC tissues and adjacent non-tumor tissues. Functional assays, including CCK-8, transwell, wound-healing, and flow cytometry, were conducted using DLD-1 and HCT116 cell lines to assess the effects of CCT8 on cell proliferation, migration, invasion, and apoptosis. Gene set enrichment analysis, protein-protein interaction network analysis, and co-immunoprecipitation were performed to explore the interaction between CCT8 and RPL4 and their role in the RPL4-MDM2-p53 pathway. Additionally, gene set variation analysis was applied to investigate the relationship between CCT8/RPL4 expression and immune infiltration patterns in CRC. RESULTS: CCT8 was significantly upregulated in CRC and associated with tumor progression. Mechanistically, CCT8 potentially synergizes with RPL4 concluded from their positive correlation and similar immune infiltration patterns, influencing the RPL4-MDM2-p53 axis and contributing to p53 ubiquitination and degradation. CONCLUSION: These findings underscore the oncogenic significance of CCT8 in CRC and shed light on its molecular mechanisms, paving the way for potential therapeutic applications.

Humans↗

PubMed2025

Comparative analysis of DREB gene family in buckwheat: the role of FtDREB02 in the delphinidin biosynthesis and drought stress response.

Dehydration response element binding (DREB) transcription factors play a pivotal role in plant abiotic stress responses, but its evolutionary and functional characterization in buckwheat remains unexplored. Here, we conducted a comprehensive analysis of the DREB gene family across three buckwheat species, revealing segmental duplication as the primary driver of family expansion and potential purifying selection during evolution. A FtDREB02 gene, classified as group A2, was identified through genome-wide association analysis (GWAS) on drought tolerance and delphinidin content. Functional validation in Arabidopsis thaliana and the hairy root of Tartary buckwheat (Fagopyrum tataricum) demonstrated that overexpression of this gene promotes delphinidin biosynthesis and enhances plant resistance to water scarcity. Through the integration of DAP-seq and PEG transcriptome cluster analysis, a FtANS candidate was screened. Functional studies showed that FtDREB02 regulates delphinidin content by binding directly to DRE elements of the FtANS promoter. This research identifies and comprehensively analyzes the DREB family within buckwheat species, elucidating the regulatory mechanisms of FtDREB02 in controlling flavonoid biosynthesis and drought resistance, providing potential genetic resources for breeding buckwheat varieties with excellent agronomic traits.

Anthocyanins↗