PubMed Health⌕ Search

Biomedical subjects

Jun Liu

Publications and source records attributed to Jun Liu.

9 recordsLinked to original sources
PubMed2026

Genomic and epigenetic regulatory mechanisms in exercise-based rehabilitation processes: Cellular and tissue remodeling, microvascular adaptation, and circulating biomarkers.

While exercise-based rehabilitation is known to positively impact functionally related parameters, the role of genomic and epigenomic responses coordinated with cellular, extracellular matrix (ECM), mitochondrial, and microvascular adaptations remains insufficiently investigated. This narrative review summarizes mechanistic evidence linking exercise-associated mechanical, metabolic, hypoxia-redox, inflammatory, and hemodynamic stimuli with tissue remodeling and clinically relevant biomarkers. Current findings indicate that integrin-focal adhesion kinase (FAK) signaling and Hippo YAP/TAZ pathways contribute to mechanical signal transduction, cytoskeletal regulation, and gene expression, whereas metabolic adaptation, ATP homeostasis, and protein synthesis are regulated through AMPK-PGC-1α, SIRT1, and mTOR-dependent pathways. Epigenetic mechanisms, including DNA methylation, histone modifications, chromatin remodeling, and noncoding RNA regulation, further influence cell-specific responses in myofibers, satellite cells, fibro-adipogenic progenitors, endothelial cells, pericytes, and immune cells. In addition, VEGF-VEGFR2, eNOS-NO, and KLF2/KLF4 signaling, together with extracellular matrix turnover and inflammation resolution, contribute to tissue repair and microvascular adaptation during rehabilitation. Importantly, acute exercise-induced molecular responses should not be interpreted as direct evidence of sustained tissue adaptation. Circulating microRNAs, extracellular vesicles, cell-free DNA, collagen-related markers, and vascular proteins represent promising approaches for monitoring rehabilitation-related changes; however, their clinical translation remains limited by challenges related to tissue specificity, biomarker kinetics, analytical variability, and the need for standardized validation alongside structural and functional outcomes.

AMPK–PGC-1α signaling↗
PubMed2026

Spatial multiomics in biomedical research: advances beyond transcriptomics.

Coordinated changes in gene expression, epigenetic regulation, protein and metabolic activities together drive disease progression and determine clinical outcomes. While spatially resolved transcriptomics has been widely adopted across biomedical fields, it offers an incomplete picture limited to transcriptomic levels. Here, we survey the latest developments in spatial multiomics technologies, with particular emphasis on platforms that extend beyond conventional transcriptomics and profile genomics, epigenomics, proteomics, or metabolomics within intact tissues. These approaches are rapidly becoming commercialized, and here we highlight major technical breakthroughs, enhanced sample compatibility, emerging applications, and computational tools for data analysis. This Review aims to equip researchers with a clear understanding of the current technological landscape and to accelerate the adoption of spatial multiomics methods in biomedical research.

Humans↗
PubMed2026

Enhancing Evidence Generation by Linking Randomized Clinical Trials to Real-World Data: The INVESTED-Medicare Linkage Study.

Real-world evidence (RWE) derived from real-world data (RWD) can complement randomized controlled trials (RCTs), yet the validity of RWD relative to RCT data remains insufficiently characterized. We obtained post hoc consent and linked individual participant data from the US-based INVESTED trial (2016-2019) with Medicare fee-for-service claims (2012-2020) to validate demographic factors, baseline characteristics (using 183-, 365-, and 730-day lookback periods) and outcomes, and to assess post-trial events. Among 5260 trial participants, 126 were enrolled and eligible for linkage. Among 115 participants with demographic information available from Medicare enrollment files, agreement between RCT- and RWD-based demographic factors was high: only one major age discrepancy, 100% agreement for sex, and an overall agreement of 0.89 for race. Participants with Medicare claims data (n = 65) were older and more likely to be White compared with the overall RCT population. For the 365-day lookback period, baseline comorbidities showed high sensitivity (median 0.80) and specificity (0.89), as did medication use (sensitivity 1.00, specificity 0.88). Lengthening the lookback period to 730 days increased sensitivity but decreased specificity, whereas shortening to 183 days decreased sensitivity but increased specificity. Clinical outcomes showed high specificity (0.88-0.94) but low sensitivity (0.18-0.50). Among those with Medicare coverage beyond the trial end date (n = 45), 22% experienced cardiopulmonary, 18% cardiovascular, and 7% heart failure (HF) hospitalizations, highlighting the value of RWD for extending RCT evidence. Proactive planning of future RCT-RWD linkage initiatives can improve the efficiency of linkage studies, leading to more actionable results.

Journal Article↗
PubMed2026

Endovascular thrombectomy versus best medical therapy for acute vertebrobasilar artery occlusion in patients with low NIHSS scores: a meta-analysis.

OBJECTIVE: The efficacy of endovascular thrombectomy (EVT) for acute vertebrobasilar artery occlusion (VBAO) presenting with mild symptoms (National Institutes of Health Stroke Scale [NIHSS] score ≤10) remains uncertain. This meta-analysis aimed to compare the effectiveness and safety of EVT versus best medical therapy (BMT) in this population. METHODS: We systematically searched PubMed, Embase, and the Cochrane Central Register of Controlled Trials from inception to September 2025 for comparative studies. The primary outcome was 90-day excellent functional outcome (modified Rankin Scale [mRS] score 0-1). Secondary outcomes included functional independence (mRS 0-2), symptomatic intracranial hemorrhage (sICH), and all-cause mortality. Pooled odds ratios (OR) with 95% confidence intervals (CI) were calculated using a random-effects model. RESULTS: Seven observational studies involving 3,107 patients were included. In unadjusted analyses, EVT was associated with a higher rate of excellent functional outcome (OR 2.17; 95% CI 1.58-2.96) but not with functional independence (OR 1.58; 95% CI 0.90-2.77). After adjustment for confounders, EVT was associated with higher rate of excellent functional outcome (OR 2.86; 95% CI 1.89-4.31) and functional independence (OR 1.91; 95% CI 1.01-3.62). Safety outcomes including sICH and mortality did not differ significantly between groups. CONCLUSION: In patients with acute VBAO and mild symptoms, EVT may be associated with superior functional outcomes compared to BMT alone, without a significant increase in procedural risks. These findings suggest a potential role for EVT in selected patients with low NIHSS scores and underscore the need for confirmation in randomized trials.

Humans↗
PubMed2026

The Impact of Hemoglobin Concentration on Prognosis in Patients With Diabetic Foot: A Systematic Review and Meta-Analysis of Risk Factors for Adverse Outcomes and Clinical Management.

BackgroundDiabetic foot (DF) complications, including diabetic foot ulcers (DFUs), lead to significant morbidity, disability, and economic burden. Hemoglobin (Hb) levels may influence the prognosis of DF patients, but their relationship with adverse clinical outcomes remains unclear. This systematic review and meta-analysis aimed to assess the association between hemoglobin concentration and the risk of adverse outcomes in diabetic foot patients, including amputation and mortality.MethodsWe followed PRISMA guidelines to conduct a systematic literature review. A meta-analysis was performed on observational studies assessing the impact of hemoglobin levels on amputation, mortality, and ulcer incidence. A random-effects model was applied, and risk bias was evaluated using the Newcastle-Ottawa Scale.ResultsA total of 22 observational studies involving 10,984 patients were included. Our meta-analysis revealed that lower hemoglobin levels were significantly associated with a higher risk of amputation (OR = 0.97, 95% CI: 0.94-0.99, P < .001), and lower hemoglobin concentrations were found in amputation cases compared to non-amputation cases (SMD = -0.14, 95% CI: -0.24 to -0.04, P < .01). However, no significant association was found between hemoglobin levels and mortality (OR = 0.99, 95% CI: 0.33-2.89, P > .05). Sensitivity and publication bias analyses indicated robust results.ConclusionLower hemoglobin levels were associated with higher odds of amputation in patients with diabetic foot. However, pooled effects were small and heterogeneity was substantial across studies; therefore, hemoglobin likely functions primarily as a marker of overall disease burden and perioperative risk rather than a proven modifiable target. Prospective interventional studies are needed to determine whether correcting anemia improves limb outcomes and survival.

Humans↗
PubMed2025

MyESL: A Software for Evolutionary Sparse Learning in Molecular Phylogenetics and Genomics.

Evolutionary sparse learning uses supervised machine learning to build evolutionary models where genomic sites loci are parameters. It uses the Least Absolute Shrinkage and Selection Operator with bi-level sparsity to connect a specific phylogenetic hypothesis with sequence variation across genomic loci. The MyESL software addresses the need for open-source tools to perform evolutionary sparse learning analyses, offering features to preprocess input phylogenomic alignments, post-process output models to generate molecular evolutionary metrics, and make Least Absolute Shrinkage and Selection Operator regression adaptable and efficient for phylogenetic trees and alignments. The core of MyESL, which constructs models with logistic regressions using bi-level sparsity, is written in C++. Its input data preprocessing and result post-processing tools are developed in Python. Compared to other tools, MyESL is more computationally efficient and provides evolution-friendly inputs and outputs. These features have already enabled the use of MyESL in two phylogenomic applications, one to identify outlier sequences and fragile clades in inferred phylogenies and another to build genetic models of convergent traits. In addition to the use in a Python environment, MyESL is available as a standalone executable compatible across multiple platforms, which can be directly integrated into scripts and third-party software. The source code, executable, and documentation for MyESL are openly accessible at https://github.com/kumarlabgit/MyESL.

Phylogeny↗
PubMed2025

Dissecting metabolic dysfunction- and alcohol-associated liver disease (MetALD) using proteomic and metabolomic profiles.

BACKGROUND & AIMS: Metabolic dysfunction- and alcohol-associated liver disease (MetALD) is a poorly understood condition that bridges cardiometabolic and alcohol-related pathological characteristics. We aimed to differentiate patients with MetALD whose molecular signatures more closely resemble either alcohol-related liver disease (ALD) or metabolic dysfunction-associated steatotic liver disease (MASLD), and to assess their relative risks of complications and mortality. METHODS: We analysed data from 443,453 European participants in the UK Biobank, including 34,147 with MetALD, 11,220 with ALD, and 124,034 with MASLD. Elastic net regression was used to classify ALD and MASLD based on 249 plasma metabolites and/or 2,941 plasma proteins, with multiple sensitivity analyses. We then applied the resulting concise model to patients with MetALD to identify an alcohol-predominant group (classified as ALD) and a cardiometabolic-predominant group (classified as MASLD). Finally, we evaluated their 15-year risk of major outcomes (heart failure, myocardial infarction, stroke, cirrhosis, hepatocellular carcinoma, and mortality) using Cox regression. RESULTS: The metabolome alone discriminated ALD from MASLD with an AUC of 0.86, while the proteome alone achieved an AUC of 0.96. Adding age, sex, BMI, liver enzymes, or metabolome information did not enhance the AUC of the proteome model. A 10-protein model differentiated ALD from MASLD with an AUC of 0.93. This model identified that patients with alcohol-predominant MetALD had significantly higher risks of mortality, and cirrhosis, along with elevated fibrosis scores and higher fibrosis stages, compared to patients with cardiometabolic-predominant MetALD. CONCLUSIONS: This study highlights the value of proteomic subtyping in MetALD, enabling more personalized treatment strategies and improved prognostic assessment. IMPACT AND IMPLICATIONS: This study underscores the critical importance of distinguishing subtypes of metabolic dysfunction- and alcohol-associated liver disease (MetALD) using proteomic data, providing a foundation for personalized treatment strategies. The findings hold significant relevance for healthcare providers, researchers, and policymakers by highlighting the differing risks associated with alcohol-predominant vs. cardiometabolic-predominant MetALD. Clinicians can apply the classification model developed in this study to more accurately assess patients and guide targeted therapies and preventive measures based on individual profiles. However, limitations of the study, such as reliance on self-reported alcohol consumption and the specificity of diagnostic criteria, necessitate further validation in diverse cohorts.

Humans↗
PubMed2023

MYH16 upregulation is associated with lung adenocarcinoma aggressiveness and immune infiltration.

Myosin heavy chain 16 (MYH16) may significantly affect cell cycle progression. Nevertheless, there is a lack of evidence about the clinical relevance of MYH16 upregulation in pan cancers, including lung adenocarcinoma (LUAD). MYH16 expression patterns were evaluated in various bioinformatics databases using The Cancer Genome Atlas data set. Clinical and pathological factor data were employed to risk-stratify patients. The Kaplan-Meier plotter approach was used to estimate survival rates. Tumor immune infiltration was explored via the TIMER tool, and gene set enrichment analysis (GSEA) was used to identify the pathways involved in MYH16 upregulation. The results showed that MYH16 was abnormally upregulated in pan cancers, including LUAD. MYH16 expression induction in LUAD was found to be related to the tumor stage. Furthermore, MYH16 upregulation was correlated with LUAD development and worse overall survival, particularly in women. Notably, MYH16 overexpression in LUAD tissues corresponded to the amount of immune infiltration in the tumor. Additionally, univariate Cox hazard regression analysis revealed that MYH16 may be an independent prognostic indicator for LUAD. Furthermore, a nomogram was constructed according to MYH16 expression and clinical characteristics. BMP6 expression deficiency may be a key factor contributing to MYH16 upregulation in LUAD. Finally, GSEA demonstrated that MYH16 might mediate meiosis and gene silencing through RNA signaling pathways. This study, for the first time, showed that MYH16 upregulation in LUAD is associated with various risk factors, increased cancer aggressiveness, enhanced infiltration of tumor immune cells, and reduced survival rates.

Female↗