Objective Glycolysis provides the metabolic requirements for proliferation of bladder cancer (BCa). Biosynthesis and energy demand of immune cells in the tumor microenvironment (TME) rely on the reprogramming of glucose metabolism. However, how glycolysis functions in the TME and responds to immunotherapy in BCa remains unclear. Methods Non-negative Matrix Factorization was used to analyze 58 513 single cells from single-cell RNA-seq data of eight BCa patients and various TME clusters in different cell subtypes were identified. A machine learning-based procedure was then applied to develop a glycolysis-related mRNA signature (GRmRS), which was compared with a public database. In vitro and in vivo experiments were conducted to explore the potential function of glycolysis-related gene COL5A1. Results A Non-negative Matrix Factorization algorithm was applied to identify different subclusters according to unique marker genes. A further analysis revealed that these glycolysis-related TME clusters were significantly associated with biological characteristics and prognostic outcomes of BCa. GRmRS was constructed based on the top 18 prospective glycolysis-related genes screened by 10 machine learning algorithms and 101 algorithm combinations, which predicted oncological survival and immune response of molecular subtypes in BCa. The meta-analysis showed GRmRS performed better than other 133 prognostic signatures. In vitro and in vivo experiments demonstrated that COL5A1 in cancer-associated fibroblasts promoted BCa proliferation and reduced infiltration of CD8+ cells. Conclusion We found that glycolysis in the TME promotes the connection to cancer cells and improves tumor immune evasion. GRmRS is a promising tool for survival prediction and individualized management of BCa patients. Meanwhile, COL5A1 in cancer-associated fibroblasts promotes BCa development and immune escape.

Cardiovascular diseases remain the leading global cause of morbidity and mortality, and thrombotic events contribute substantially to their clinical burden. Established anticoagulants, including vitamin K antagonists and direct oral anticoagulants, reduce thromboembolic events but remain limited by bleeding risk in selected patients. Factor XI (FXI), a serine protease in the intrinsic coagulation pathway, has emerged as a promising investigational target because FXI-dependent thrombin amplification appears to contribute more to pathological thrombosis than to physiological hemostasis. This review consolidates contemporary progress in FXI/activated factor XI (FXIa)-targeted therapeutics, encompassing monoclonal antibodies (e.g., abelacimab, osocimab), antisense oligonucleotides (e.g., fesomersen), and small-molecule inhibitors (e.g., milvexian, asundexian). Clinical evidence suggests that FXI/FXIa inhibition may reduce thrombosis or bleeding in selected settings, particularly postoperative venous thromboembolism prophylaxis and certain high-bleeding-risk populations; however, efficacy signals have been inconsistent across indications such as atrial fibrillation, acute coronary syndrome, and secondary stroke prevention. Remaining challenges, including long-term safety, dose selection, patient stratification, perioperative management, and definitive efficacy in outcome trials, are also discussed. Overall, FXI/FXIa inhibition remains a promising but still investigational strategy that may improve the balance between antithrombotic efficacy and bleeding risk in selected clinical contexts.

Background Degenerative valvular heart disease (VHD) is increasingly recognized as a major public health concern in aging populations. Although traditional cardiovascular risk factors have been extensively investigated, the role of loneliness and social isolation has remained largely overlooked in the context of valvular pathology. Methods We conducted a prospective cohort study involving 462 917 participants from the UK Biobank, free of VHDs at baseline. Loneliness and social isolation were assessed using validated questionnaires. Results During a median follow‐up of 13.9 years, 11 003 cases of degenerative VHD were documented. Among them, there were 4280 cases of aortic valve stenosis and 4693 cases of mitral valve regurgitation. In fully adjusted models using no loneliness as reference, the highest loneliness level was associated with significantly increased risks of degenerative VHD (hazard ratio [HR], 1.19 [95% CI, 1.09–1.28]), aortic valve stenosis (HR, 1.21 [95% CI, 1.06–1.37]) and mitral valve regurgitation (HR, 1.23 [95% CI, 1.09–1.39]) (all P for trend <0.001). This association was consistently observed for degenerative VHD‐related events. In contrast, no significant associations were observed for social isolation. Additionally, loneliness was associated with an increased risk of degenerative VHD, independently of genetic background, but the highest risk occurs in individuals with both high genetic risk and elevated loneliness (P<0.001). In mediation analyses, unhealthy lifestyles were identified as significant mediators in the association between loneliness and incident degenerative VHD. Conclusions Loneliness, rather than social isolation, was significantly associated with an increased risk of degenerative VHD. Our findings highlight novel opportunities for nonpharmacological interventions aimed at managing degenerative VHD.

BACKGROUND:Systemic inflammation has been implicated in valvular degeneration, but prospective evidence across major non-rheumatic valvular phenotypes remains limited. We investigated the associations of circulating inflammatory indicators with incident valvular heart disease in the UK Biobank. METHODS:This prospective cohort study included 250,532 participants free of cardiovascular disease, valvular heart disease, and autoimmune disease at baseline. Baseline systemic inflammation response index (SIRI), neutrophil-to-lymphocyte ratio (NLR), neutrophil-to-platelet ratio (NPR), lymphocyte-to-monocyte ratio (LMR), and C-reactive protein were assessed. Multivariable Cox proportional hazards models were used to examine associations with clinically diagnosed incident aortic stenosis (AS), mitral regurgitation (MR), aortic regurgitation (AR), and valve-related events. Restricted cubic spline analyses, subgroup analyses, and sensitivity analyses were performed. RESULTS:Over a median follow-up of 13.22 years, incident AS occurred in 1,904 participants, incident MR in 2,140, and incident AR in 757; 1,369 valve-related events were also recorded. Higher SIRI was associated with increased risks of AS (hazard ratio [HR] per 1-standard deviation [SD], 1.07; 95% CI, 1.03-1.11), MR (1.10; 1.05-1.14), and valve-related events (1.08; 1.03-1.13). Higher LMR was associated with lower risks of AS (0.91; 0.86-0.96), MR (0.93; 0.89-0.98), and valve-related events (0.88; 0.82-0.94). NPR was positively associated with MR and valve-related events, whereas no indicators showed a clear association with AR after full adjustment. These patterns were broadly consistent across dose-response, subgroup, and sensitivity analyses. CONCLUSIONS:Systemic inflammatory indices, particularly SIRI and LMR, were independently associated with incident AS, MR, and valve-related events, whereas no clear association was detected for AR. These findings support a phenotype-specific relationship between systemic inflammation and non-rheumatic valvular heart disease.

Background The development and progression of bladder cancer are closely linked to its complex tumor microenvironment. Hedyotis diffusa and Scutellaria barbata (HD-SB) are commonly used as a prominent herbal pair for treating bladder cancer. However, the pharmacological targets and molecular mechanisms by which HD-SB impacts bladder cancer require further elucidation. Additionally, it remains uncertain whether this herbal pair affects the prognosis and treatment efficacy of bladder cancer. Methods We employed network pharmacology to predict the targets of HD-SB and bladder cancer, identifying overlaps with prognostic genes linked to the overall survival of bladder cancer patients in the TCGA dataset. Subsequently, we utilized least absolute shrinkage and selection operator (LASSO) and Cox regression analyses to pinpoint a prognostic signature and construct a prognostic model. We further explored the correlations between risk scores, immune cells, immune checkpoint genes, and treatment efficacy. Single-cell RNA-sequencing (scRNA-seq) was used to profile the expression of prognostic genes across various cell types, and immunohistochemistry validated the protein levels of these targets. Molecular docking studies were conducted to clarify the interactions between HD-SB components and the identified genes, and in vitro experiments demonstrated the effects of HD-SB on bladder cancer cells. Results Venn diagram analysis identified 497 common targets shared between HD-SB and bladder cancer. LASSO and Cox regression identified a 15-gene prognostic signature, including VEGFA, EGFR, MYC, PDGFRA, JUN, FN1, PTPN6, PTGER3, MAP2, CALM1, CTSV, CES1, ADRA1D, PYGL, and PLA2G1B. Kaplan-Meier analysis showed better overall survival in the low-risk group (median 19.8 months) versus the high-risk group (median 15.9 months). Linear regression analysis revealed a significant correlation between risk scores and specific immune cell types, as well as the dysregulated expression of immune checkpoint genes across different groups. The prognostic gene-based risk score was also found to correlate with the efficacy of both immunotherapy and chemotherapy. Six key targets-VEGFA, MYC, JUN, FN1, PTPN6, and CALM1-were validated through scRNA-seq and immunohistochemistry. Molecular docking analysis demonstrated that components of HD-SB bind with high affinity to these signature targets. In vitro experiments showed that HD-SB effectively inhibited bladder cancer cell viability, colony formation, and migration. Conclusion This is the first study to explore the potential of HD-SB in enhancing the prognosis and treatment outcomes of bladder cancer through network pharmacology, bioinformatics, and experimental approaches. While the focus is primarily on tumor microenvironment-related factors, the findings provide valuable insights into the molecular mechanisms of HD-SB and identify potential novel targets for bladder cancer therapy.

AIMS:Heart failure (HF) is a major global public health challenge, with obesity being one of its key risk factors. Although several HF risk prediction models have been developed in the general population, few are specifically tailored to individuals with obesity. This underscores the urgent need for precise biomarkers to improve individual risk stratification and enable personalized prevention strategies. We aimed to develop and validate a plasma proteomics-based protein risk score (PRS) to predict incident HF among individuals with obesity. MATERIALS AND METHODS:We analysed 9831 participants with obesity (BMI ≥ 30 kg/m2) from the UK Biobank with baseline measurements of 2911 circulating proteins and up to 16 years of follow-up. Multivariable Cox regression identified proteins associated with incident HF after comprehensive covariate adjustment. A PRS was constructed using LASSO regression and evaluated in a held-out test set. Protein trajectories before HF onset were reconstructed using LOESS modelling. To enhance clinical feasibility, a minimal protein panel was identified using LightGBM with forward feature selection. RESULTS:A total of 727 participants developed HF during follow-up. Multivariable cox analyses identified 578 proteins significantly associated with HF. LASSO regression further selected 81 proteins to build the PRS, which showed a strong association with HF risk in both training (HR 3.57; 95% CI 3.19-4.00) and test cohorts (HR 2.45; 95% CI 2.20-2.74). Adding the PRS improved prediction beyond age and sex (ΔC = 0.091) and beyond the Pooled Cohort Equations to Prevent Heart Failure (PCP-HF) model (ΔC = 0.052), with consistent gains in NRI and IDI. Proteomic deviations were detectable up to 16 years before diagnosis. A four-protein panel (GDF15, NT-proBNP, TNFRSF10B, CTHRC1) achieved robust discrimination (AUC 0.789), outperforming NT-proBNP alone (AUC 0.695) and complementing the PCP-HF model (combined AUC 0.803). DISCUSSION:Large-scale plasma proteomics substantially improves HF risk prediction in individuals with obesity and reveals long-standing molecular alterations preceding clinical onset. A simplified four-protein panel maintains robust predictive accuracy and provides a practical approach for the early detection and targeted prevention of obesity-related HF.

The Atherogenic Index of Plasma (AIP), a composite lipid index based on triglycerides (TG) and HDL-C, has been linked to cardiovascular risk. However, the prognostic relevance of AIP after coronary artery bypass grafting (CABG) in patients with multivessel coronary disease (MVD) is not well established. Therefore, we examined whether AIP predicts long-term outcomes in our cohort. Consecutive patients with MVD undergoing CABG (2015–2020) were included. The baseline and 1-year AIP were used to define tertiles. Major adverse cardiovascular and cerebrovascular events (MACCEs) were evaluated across AIP groups using Kaplan–Meier methods and Cox regression with multivariable adjustment. Restricted cubic splines (RCS) were used to assess potential non-linear (dose–response) relationships between AIP and MACCEs. In total, 1,602 patients were analysed, and 414 MACCEs occurred during a median follow-up of 43 months. Kaplan–Meier curves showed that group 3 had a significantly lower survival rate than those in the other two groups (P = 0.022). In adjusted Cox models, with group 1 as the reference, the hazard ratios were 1.11 (95

The non-high-density lipoprotein cholesterol-to-high-density lipoprotein cholesterol ratio (NHHR) has emerged as a promising lipid predictor for various cardiovascular conditions. However, its role in predicting long-term outcomes after coronary artery bypass grafting (CABG), particularly in multivessel disease (MVD) patients, remains unclear. We conducted a retrospective study of MVD patients who underwent CABG between 2011 and 2020. Patients were stratified into NHHR quartiles at baseline and 1-year post-CABG. The primary outcome was the incidence of major adverse cardiovascular and cerebrovascular events (MACCEs), including cardiac death, myocardial infarction, stroke, repeat revascularization, and cardiac rehospitalization. Cox proportional hazards models and restricted cubic spline (RCS) analysis were used to assess the relationship between NHHR and MACCEs. A total of 2,072 patients (mean age 60.8 ± 8.3 years; 83.5

Bisphenol A (BPA), recognized as an environmental endocrine disruptor, has been implicated in modulating the behavior of urothelial cells, precipitating detrimental effects in the bladder and contributing to lower urinary tract dysfunction in mice. However, the exact link between urinary BPA levels and the development of overactive bladder (OAB) is not yet fully understood. This study aimed to examine the potential association between urinary BPA levels and OAB in a nationally representative group of individuals. The investigation was conducted using extensive datasets from the National Health and Nutrition Examination Survey (NHANES), which covered the years 2003-2016. Urinary BPA concentrations were quantified via solid-phase extraction coupled with high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). The diagnosis of OAB was established when participants attained a total score of 3 or higher on the Overactive Bladder Symptom Score (OABSS) assessment. The association between urinary BPA and OAB was investigated using survey-weighted logistic regression models and subgroup analyses. The study included a cohort of 9143 participants, 1803 of whom (19.7%) were diagnosed with OAB. Urinary BPA concentrations spanned 0.14 - 965 ng/mL across the cohort. Participants were stratified into tertiles based on these levels. The highest tertile of BPA was found to be linked to a higher risk of OAB by the logistic regression analyses(OR = 1.15; 95% CI: 0.96-1.39; P = 0.12), albeit not statistically significant. Female participants showed a greater risk of OAB compared to male participants (OR = 1.75; 95% CI: 1.42-2.15; P < 0.0001). To explore this further, separate logistic regression analyses were conducted for male and female participants, respectively. Noteworthy, the logistic regression analyses, adjusting for age, ethnicity, education, marital status, BMI category, smoking status, drinking status, hypertension, and diabetes, demonstrated a significant link between elevated urinary BPA tertiles and heightened OAB risk in female participants (OR = 1.34; 95% CI: 1.05-1.71; P = 0.02). This trend of progressively increasing risk across exposure categories was further supported by subgroup analyses. Taken together, these results indicate that greater urinary BPA exposure correlates with elevated OAB susceptibility among women. Thus, minimizing BPA exposure emerges as a potential strategy for OAB risk reduction in this demographic, with implications for both prevention and clinical management.

BackgroundThe frequency of adding salt to foods reflects an individual’s long-term salt preference, and excessive salt intake may increase cardiovascular risk. However, the association between this behavioral indicator and extracoronary atherosclerotic vascular disease, along with its underlying metabolic signature, remains inadequately characterized.MethodsWe included 495,291 participants from the UK Biobank and assessed the frequency of adding salt to foods. Cox proportional hazards regressions modeled the associations of salt-adding frequency with incident peripheral arterial disease (PAD) and incident carotid artery stenosis (CAS), and related events, respectively.ResultsDuring a median of 13.9 years of follow-up, 7,461 incident cases of PAD and 8,067 cases of CAS were identified. When fully adjusted for confounders, participants who sometimes, usually, or always added salt to foods showed an increased risk of developing PAD of 8%, 16%, and 35%, respectively, compared to those who never/rarely did. A comparable pattern of risk increase was also evident for CAS, with 26% higher risk in participants who always added salt to foods. In addition, consistent associations were observed for vascular-related events. Genetic analyses further revealed that the association between salt-adding frequency and PAD was independent of genetic predisposition. Finally, a metabolic signature for salt-adding frequency was constructed using 26 metabolites, which mediated 36.4% and 19.9% of the increased risks for PAD and CAS, respectively.ConclusionOur study shows that frequently adding salt to foods is associated with an increased risk of extracoronary atherosclerotic vascular disease and related events, with circulating metabolites playing a partial mediating role.

BackgroundAlthough pulse pressure (PP) predicts individual cardiometabolic diseases (CMDs), its role in the progression of cardiometabolic multimorbidity (CMM) remains uncertain. This study aimed to investigate the association between PP and CMD progression, from incident CMD to CMM development and all-cause mortality.MethodsUK Biobank participants (N = 403,851) were prospectively assessed. PP was evaluated per 1-standard-deviation (SD) increase and across quartiles (Q1–Q4) using Cox proportional hazards models for associations with: (1) incident CMD, (2) progression to CMM (defined as two or more of type 2 diabetes, coronary heart disease, or stroke), and (3) all-cause mortality. Restricted cubic splines were used to examine nonlinearity, and threshold effects were identified using piecewise regression. Competing-risk analyses (Fine-Gray models) and sensitivity analyses excluding the first 2 years of follow-up were performed to address mortality-related competing events and potential reverse causality, respectively. Subgroup analyses were stratified by age, sex, and body mass index (BMI).ResultsAmong 403,851 UK Biobank participants who were free of CMD at baseline, per 1-SD increase in PP was significantly associated with transitions from health to CMD (HR = 1.13, 95% CI: 1.12–1.14) and to CMM (HR = 1.18, 95% CI: 1.15–1.21), with Q4 versus Q1 comparisons indicating 36% higher risks for both outcomes. Notably, the PP–CMM association was strongest among patients with stroke, with an HR of 1.23 (95% CI: 1.11–1.36) per 1-SD increase. Subgroup analyses further showed that this association was most pronounced in participants aged < 60 years, women, and those with BMI 18.5 ≤ 25 kg/m2. Threshold-effect analyses identified specific risk turning points: 40 mmHg for incident CMD, 42 mmHg for mortality, and 52 mmHg for CMM development among healthy participants, and 57 mmHg for mortality among participants with established CMM.ConclusionOur study demonstrates that elevated PP is significantly associated with higher risks of CMD progression and mortality.

Objective: Chronic kidney disease (CKD) is characterized by a gradual decline in kidney function overtime. The role of dietary inflammatory index (DII) and systemic immune-inflammation index (SII) in individuals with CKD remains uncertain. We aimed to explore the potential correlation between DII and SII with the prevalence of CKD in adult Americans. Methods: This cross-sectional study used data from the National Health and Nutrition Examination Study between 1999 and 2018. The DII was calculated based on the 24-hour dietary history interview, while the SII was calculated as the product of platelet count multiplied by neutrophil count and divided by lymphocyte count. CKD was diagnosed based on impaired glomerular filtration rate (<60 mL/ min per 1.73 m(2)) or urinary albumin-creatinine ratio >= 30 mg/g. Multivariable logistic regression analyses and subgroup analyses were performed to examine the association between DII/SII and CKD. Results: In total, this study included 40,388 participants, of whom 7443 (18.4%) had CKD. The prevalence of CKD changed from 14.84% (95% confidence interval (CI): 13.20-16.48%) in 1999-2000 to 12.76% (95% CI: 11.10-14.43%) in 2017-2018. According to adjusted multivariate logistic regression models, individuals with higher DII scores had a higher likelihood of having CKD (odds ratio = 1.24; 95% CI: 1.12-1.37). Similarly, higher SII scores were associated with a higher risk of CKD (odds ratio = 1.37; 95% CI: 1.25-1.50). Subgroup analyses further demonstrated relatively stronger associations between DII/SII and CKD among individuals with other factors such as sex, age, body mass index, smoking status, drinking status, hypertension, and diabetes. Conclusions: The DII and SII scores were significantly positively associated with higher risks of CKD. Anti-inflammatory diet might have the potential to prevent CKD. The SII may serve as a cost-effective and straightforward approach for detecting CKD. Further prospective longitudinal studies are needed to verify the causality.

Cardiac fibrosis remains a major clinical challenge with limited therapeutic options, and the role of PFKFB3 in its pathogenesis remains unclear. Single-cell RNA sequencing analysis was applied and the results demonstrated that glycolysis was most prominently enhanced in activated cardiac myofibroblasts (myoCFs) in cardiomyopathy. Western blot analysis revealed that PFKFB3 expression was significantly increased in fibrotic hearts and TGF-β1-stimulated myoCFs. Genetic (Pfkfb3+/−) and pharmacological (3PO) inhibition of PFKFB3 attenuated myoCF activation, proliferation, and migration, while also reducing cardiac fibrosis in isoproterenol- and coronary ligation- induced mouse models. Mechanistically, TGF-β1 upregulated PFKFB3 in a HIF-1α-dependent manner, and extracellular PFKFB3 further promoted fibroblast activation and inflammatory responses. Clinically, elevated plasma PFKFB3 levels, as measured by ELISA, were significantly associated with fibrosis severity in patients with cardiomyopathy. These findings reveal for the first time that PFKFB3 drives cardiac fibrosis dually through intracellular glycolytic regulation and extracellular signaling, highlighting its translational potential.

BACKGROUND:Aortic aneurysms and aortic dissections (AA/AD) are serious vascular conditions that often progress without symptoms and are associated with high mortality, highlighting the need for improved tools to predict the occurrence. This study aims to identify plasma proteins that can predict the risk of future AA/AD events and to combine these biomarkers with traditional risk factors to construct risk prediction model. MATERIALS AND METHODS:We analyzed plasma proteomic data from 22 416 participants in the UK Biobank, measuring 2911 proteins using the Olink Explore proximity extension assay. Plasma proteomics data were analyzed using Cox regression and machine learning techniques. Proteins significantly associated with AA/AD risk were identified, and predictive models were constructed by integrating these biomarkers with traditional risk factors such as age, sex, and blood pressure. RESULTS:The Cox regression models identified 25 proteins significantly associated with AA/AD risk, after adjusting for demographic factors. Furthermore, light gradient-boosting machine was used to rank the importance of these proteins and applied forward stepwise selection to identify four key predictive proteins (cystatin 3 [CST3], matrix metallopeptidase 12 [MMP12], multiple EGF-like domains 9 [MEGF9], and C-X-C motif chemokine ligand 17 [CXCL17]). The protein panel demonstrated an overall predictive AUC of 0.725 for AA/AD. The demographic model achieved an AUC of 0.740. Integration of these biomarkers with demographic factors significantly enhanced predictive accuracy, achieving an AUC of 0.777 (DeLong test P <0.001). Temporal trajectory analysis revealed that elevated levels of CST3, MMP12, and CXCL17 were detectable up to 10 years prior to AA/AD diagnosis. CONCLUSION:Our study highlights the potential of plasma proteomics, particularly combination of four proteins (CST3, MMP12, MEGF9, and CXCL17), as a valuable strategy for predicting AA/AD risk. The integration of proteomic biomarkers with demographic factors enhances predictive accuracy and offers insights into the underlying molecular mechanisms, which could lead to improved early detection and personalized treatment for AA/AD.

This study aimed to investigate the underlying mechanisms of Fibroblast Growth Factor 21 (FGF21) in myocardial ischemia/reperfusion (I/R) injury. First, FGF21 was upregulated in the serum of patients with myocardial I/R injury as well as in I/R hearts of mice and hypoxia/reoxygenation (H/R) neonatal rat cardiomyocytes (NRCMs). While FGF21 knockout exacerbated such injury, which was mitigated by rhFGF21. Bioinformatics analysis identified immunity-related GTPase M1 (Irgm1) as a key autophagy-related gene downregulated in ventricular tissue of FGF21-/- I/R mice. Impaired autophagic flux in FGF21-/- mice during I/R could be rescued by rhFGF21 through the signal transducers and activators of transcription 1 (STAT1) pathway. The beneficial effects of rhFGF21 in reducing H/R injury were limited in Irgm1 knockdown NRCMs. This study suggested that FGF21 deficiency intensifies myocardial I/R injury by exacerbating the impairment of autophagic flux. Activation of FGF21 or Irgm1 may serve as a promising therapeutic strategy for myocardial I/R injury.