Benrong Liu

Background: Community-dwelling individuals at high cardiovascular risk are clinically heterogeneous, but whether distinct clinical-metabolic phenotypes differ in carotid plaque burden remains unclear. Methods: From 4191 participants in a community-based screening project conducted in two communities in Guangzhou, 1015 individuals in the high-cardiovascular-risk stage with nonmissing high-plaque-burden status were included. All 1015 participants underwent exploratory clustering using 17 clinical, metabolic, lifestyle-related, and disease-history variables. High plaque burden was defined as bilateral carotid plaques, multiple plaques, or maximum plaque thickness at or above the 75th percentile among plaque-positive participants. Logistic regression examined associations between phenotypes and high plaque burden. Results: Among the 1015 participants included in the clustering analysis, 329 (32.4%) met the definition of high plaque burden. Four phenotypes were identified: relatively low metabolic burden, older age–ASCVD burden, smoking–low HDL-C, and blood pressure-loaded phenotypes. The corresponding prevalences of high plaque burden were 15.9%, 44.4%, 49.7%, and 33.2%. After adjustment for age and sex, all three non-reference phenotypes showed higher odds of high plaque burden. In sensitivity analysis excluding age and prior ASCVD from clustering, the blood pressure-loaded phenotype remained associated with high plaque burden. Conclusions: Four exploratory clinical-metabolic phenotypes showed different levels of carotid plaque burden among community-dwelling individuals at high cardiovascular risk. The blood pressure-loaded and smoking–low HDL-C phenotypes were associated with greater plaque burden and may provide an exploratory framework for describing heterogeneity within high-risk populations.

To develop and validate a machine learning (ML) model for real-time monitoring of in-hospital mortality (IHM) risk and identification of major risk factors in heart failure (HF) patients admitted to intensive care units (ICUs). Data from ICU HF patients were extracted from the multicenter eICU-Collaborative Research Database (eICU-CRD. External validation used MIMIC-IV and a real-world Chinese dataset (CHN-dataset). Daily measurements from MIMIC-IV patients staying ≥ 3 days formed a Daily Measurement (DM) dataset. After rigorous preprocessing and feature selection, five ML algorithms were trained and optimized using eICU-CRD data. Model performance was evaluated using AUC, sensitivity, specificity, and balanced accuracy. The optimal model was benchmarked against APACHE and SOFA scores. SHapley Additive exPlanations (SHAP) interpreted feature contributions. A Windows application was developed for clinical deployment. XGBoost emerged as the optimal model (Final-ML model), which incorporated only 17 routinely collected clinical variables: age, non-invasive systolic blood pressure (NI-SBP), heart rate, respiratory rate, Glasgow Coma Scale eye opening score, white blood cell count (WBC), creatinine, bicarbonate, red cell distribution width (RDW), platelet count, glucose, calcium, mean corpuscular hemoglobin concentration (MCHC), sodium, mean corpuscular volume, red blood cell count, and potassium. It achieved high AUCs: 0.876 (95%CI: 0.836-0.915; eICU-CRD test data), 0.932 (95%CI: 0.921-0.942; MIMIC-IV), and 0.879 (95%CI: 0.846-0.912; CHN-dataset). It significantly outperformed APACHE (AUC = 0.740, 95%CI: 0.720-0.761) and SOFA (AUC = 0.717, 95%CI: 0.694-0.740) scores. The model demonstrated strong generalizability across ethnicities, ward types, and genders within MIMIC-IV. Using daily data (DM dataset), predicted IHM risk accurately tracked patient trajectories: risk decreased progressively for survivors and increased for non-survivors throughout the ICU stay. SHAP analysis identified key predictors: NI-SBP, age, heart rate, WBC, glucose, and notably, RDW and MCHC. Time-dependent Cox regression confirmed RDW increase (HR = 3.783, 95%CI: 2.237-6.398) and MCHC decrease (HR = 0.173, 95%CI: 0.040-0.741) as significant independent risk factors for IHM. The developed XGBoost model provides a reliable, generalizable tool for real-time IHM risk quantification and monitoring in ICU HF patients, using only 17 routinely collected clinical variables. It surpasses traditional scoring systems and enables dynamic risk assessment throughout the ICU stay. By identifying patient-specific major risk factors via SHAP values, the model facilitates timely, personalized treatment adjustments.

Myocyte enhancer factor 2A (MEF2A), a transcription factor implicated in coronary artery disease, remains unexplored in vascular redox regulation. To address this gap and overcome the limitations of current antioxidant therapies, we investigate the role of MEF2A in oxidative defense via human umbilical vein endothelial cells (HUVECs) and murine models. Adenoviral vectors encoding MEF2A-specific shRNAs or mRNAs are used to silence or overexpress MEF2A in HUVECs. For in vivo validation, endothelial-targeted MEF2A knockdown is achieved via AAV1-shRNA delivery in mice fed a high-fat diet. Systemic redox status is assessed by measuring reactive oxygen species (ROS), glutathione homeostasis (GSH/GSSG ratio), the NADH/NAD⁺ balance, the mitochondrial membrane potential (ΔΨm), and 8-hydroxy-2′-deoxyguanosine (8-OHdG). Mechanistic insights are derived from immunofluorescence, qPCR, western blotting, and dual-luciferase reporter assays. MEF2A silencing induced redox imbalance, characterized by elevated ROS, a reduced GSH/GSSG ratio, and ΔΨm collapse. Conversely, MEF2A overexpression synergizes with SIRT1 to restore the glutathione pool, maintain NAD⁺ homeostasis, and suppress ROS under oxidative stress. Chromatin immunoprecipitation confirm that MEF2A directly binds to two cis-elements in the SIRT1 promoter, driving transcriptional activation. In vivo, MEF2A-deficient mice present increased vascular oxidative damage, as indicated by elevated DNA damage marker (8-OHdG) and ROS levels. The downregulation of SIRT1/PGC-1α in MEF2A-silenced cells is verified in vivo. Our findings establish MEF2A as a master regulator of endothelial redox defense via the SIRT1-PGC-1α axis, providing a mechanistic foundation for the treatment of oxidative cardiovascular disorders. This work suggests that pharmacological MEF2A activation is a novel strategy for precision antioxidant therapy in vascular medicine.

The stress hyperglycemia ratio (SHR) reflects relative hyperglycemia levels. Prior studies indicate that SHR is related to the prognosis of certain diseases. This study investigated the predictive accuracy of SHR for in-hospital and intensive care unit (ICU) mortality in acute kidney injury (AKI) patients. We analyzed 4,418 AKI patients from the Medical Information Mart for Intensive Care (MIMIC-IV) database. SHR was calculated as admission blood glucose (mg/dl) divided by (28.7 × HbA1c(%) − 46.7). Patients were stratified into four groups based on SHR levels. Restricted cubic splines (RCS) and Cox proportional hazards models were employed to assess the association between SHR and mortality, and Kaplan-Meier survival analysis was conducted to compare mortality rates stratified by SHR groups. Subgroup analyses evaluated the consistency of these associations across clinically relevant populations. Machine learning algorithms (Boruta feature selection, logistic regression, random forest) were employed to build predictive models. Among 4,418 patients (36.03% female), in-hospital and ICU mortality rates were 6.88% and 4.48%, respectively. A U-shaped relationship was observed between SHR and mortality (nonlinear p = 0.015 for in-hospital, p = 0.048 for ICU mortality). Kaplan-Meier analysis revealed significant survival differences across SHR groups (log-rank p < 0.01). Cox regression showed that each unit increase in SHR was associated with 23% higher in-hospital mortality (HR = 1.23, 95% CI: 1.09–1.40) and 47% higher ICU mortality (HR = 1.47, 95% CI: 1.25–1.74). Machine learning models achieved AUCs of 0.76–0.77 for mortality prediction. In critically ill AKI patients, higher SHR is associated with increased mortality after adjustment for key covariates. However, its modest standalone discriminative capacity indicates that SHR is best combined with other clinical variables rather than used alone.

Myocyte enhancer factor 2A (MEF2A), a transcription factor implicated in coronary artery disease, remains unexplored in vascular redox regulation. To address this gap and overcome limitations of current antioxidant therapies, we investigated MEF2A’s role in oxidative defense using human umbilical vein endothelial cells (HUVECs) and murine models. Adenoviral vectors encoding MEF2A-specific shRNA or mRNA were employed to silence or overexpress MEF2A in HUVECs. For in vivo validation, endothelial-targeted MEF2A knockdown was achieved via AAV1-shRNA delivery in mice fed a high-fat diet. Systemic redox status was assessed by measuring reactive oxygen species (ROS), glutathione homeostasis (GSH/GSSG ratio), NADH/NAD ⁺ balance, mitochondrial membrane potential (ΔΨm), and 8-hydroxy-2′-deoxyguanosine (8-OHdG). Mechanistic insights were derived from immunofluorescence, qPCR, western blotting, and dual-luciferase reporter assays. MEF2A silencing induced redox imbalance, characterized by elevated ROS, reduced GSH/GSSG ratio, and ΔΨm collapse. Conversely, MEF2A overexpression synergized with SIRT1 to restore glutathione pools, maintain NAD ⁺ homeostasis, and suppress ROS under oxidative stress. Chromatin immunoprecipitation confirmed direct MEF2A binding to two cis-elements in the SIRT1 promoter, driving transcriptional activation. In vivo, MEF2A-deficient mice exhibited amplified vascular oxidative damage, including elevated DNA damage marker (8-OHdG) and ROS levels. Downregulation of SIRT1/PGC-1α in MEF2A silenced cells was verified in vivo. Our findings establish MEF2A as a master regulator of endothelial redox defense via the SIRT1-PGC-1α axis, offering a mechanistic foundation for targeting oxidative cardiovascular disorders. This work suggests pharmacological MEF2A activation as a novel strategy for precision antioxidant therapy in vascular medicine.

Background Endothelial dysfunction is a pivotal contributor to cardiovascular complications in individuals with diabetes. However, the precise role of macrophages and their exosomes in the diabetic milieu remains elusive. Methods Exosomes (Exos) were isolated from the supernatants of macrophages treated with advanced glycation end products (AGE) or bovine serum albumin (BSA) using ultracentrifugation. Following coculture with AGE-Exos or BSA-Exos, human umbilical vein endothelial cells (HUVECs) were subjected to CCK-8, EdU, cell migration, monocyte adhesion, and tube formation assays. ELISA and Western blotting were employed to assess inflammatory cytokine release and protein expression levels in HUVECs. The miRNA expression profiles of AGE-Exos and BSA-Exos were analysed using miRNA arrays. Potential targets of miR-22-5p were predicted via miRNA databases and validated through RT‒qPCR, dual-luciferase reporter assays, and rescue experiments. Furthermore, a Rab27a knockout mouse model of type 2 diabetes mellitus (T2DM) was established. Aortic tissues were analysed via immunofluorescence for CD63 and CD31 expression, immunohistochemistry for VCAM-1 and ICAM-1 expression, and Western blotting for FOXP1 expression. Results AGE stimulation increased the secretion of exosomes from macrophages. Compared with BSA-Exos, AGE-Exos significantly impaired endothelial cell proliferation, migration, and tube formation capabilities while increasing monocyte adhesion and proinflammatory cytokine release without affecting cell viability. miR-22-5p was enriched in AGE-Exos, which were subsequently transferred to HUVECs, specifically targeting FOXP1, resulting in endothelial dysfunction. Overexpression of miR-22-5p in HUVECs using lentiviral vectors recapitulated the inflammatory effects observed with AGE-Exos, whereas anti-miR-22-5p conferred protective effects. Rab27a knockout significantly reduced exosome accumulation in T2DM model mouse aortic tissues, alleviating endothelial discontinuity, downregulating VCAM-1 and ICAM-1 expression, and upregulating FOXP1 expression. Conclusions AGE-induced release of macrophage-derived exosomes may partially depend on Rab27a transport, which delivers miR-22-5p to ECs. This miR-22-5p targets FOXP1 in ECs, leading to inflammation and resulting in endothelial dysfunction that accelerates the development of diabetic vascular lesions.

Both resveratrol and myocyte enhancer factor 2A (MEF2A) may protect vascular endothelial cell (VEC) through activating the expression of SIRT1. However, the relationship between resveratrol and MEF2A is unclear. We aimed to investigate the deeper mechanism of resveratrol in protecting vascular endothelial cells and whether MEF2A plays a key role in the protective function of resveratrol. Human umbilical vein endothelial cell (HUVEC) was used for in vitro study, and small interfere RNA was used for silencing MEF2A. Silencing MEF2A in the vascular endothelium (VE) of ApoE^−/− mice was performed by tail injection with adeno associated virus expressing si-mef2a-shRNA. The results showed that treatment of HUVEC with resveratrol significantly up-regulated MEF2A, and prevented H₂O₂-induced but not siRNA-induced down-regulation of MEF2A. Under various experimental conditions, the expression of SIRT1 changed with the level of MEF2A. Resveratrol could rescue from cell apoptosis, reduction of cell proliferation and viability induced by H₂O₂, but could not prevent against that caused by silencing MEF2A with siRNA. Silencing MEF2A in VE of apoE^−/− mice decreased the expression of SIRT1, increased the plasma LDL-c, and abrogated the function of resveratrol on reducing triglyceride. Impaired integrity of VE and aggravated atherosclerotic lesion were observed in MEF2A silenced mice through immunofluorescence and oil red O staining, respectively. In conclusion, resveratrol enhances MEF2A expression, and the upregulation of MEF2A is required for the endothelial protective benefits of resveratrol in vitro via activating SIRT1. Our work has also explored the in vivo relevance of this signaling pathway in experimental models of atherosclerosis and lipid dysregulation, setting the stage for more comprehensive phenotyping in vivo and further defining the molecular mechanisms.