In primary mitral valve regurgitation (MR), a failing valve induces volume overload (VO) of the left ventricle (LV), triggering neurohormonal responses and myocardial remodeling. Surgical valve repair is the most effective therapy for MR, improving symptoms and in some patients reversing cardiac hypertrophy. However, at least 20% of patients develop postoperative impairment of LV function with detrimental effects on long-term outcomes, with no known cause. Many MR patients receive pharmacological treatment to alleviate symptoms, with drugs that alter cardiac function, hemodynamics, and molecular pathways that influence cardiac remodeling. To support the advancement of medical management of MR, we developed a multiscale model of cardiac hypertrophy that links ventricular mechanics, cardiovascular hemodynamics, and cardiomyocyte molecular signaling. We calibrated the model using the Markov chain Monte Carlo algorithm, a machine learning method, to integrate data from 76 studies of experimental VO in animals. The model's predictions showed good agreement with experimental data on MR in dogs, including the chronic effects of four drugs on MR-induced hypertrophy. When simulating valve repair, our model suggests that full reversal of LV hypertrophy requires both the mechanical elimination of VO and the restoration of normal neurohormonal receptor activity. Finally, we explored selecting subsets of a large pool of pre-computed simulations to personalize model predictions for a small population or individual where insufficient data are available to refit the entire model.

Direct oral anticoagulants (DOACs) have simplified treatment for venous thromboembolism (VTE), but fewer mandatory monitoring visits may reduce opportunities for structured reassessment. We evaluated temporal changes in hospital-captured documentation of post-VTE care processes during the transition to DOAC-based treatment, including initial anticoagulation, clinical follow-up, laboratory monitoring, and selective imaging reassessment.

We conducted a single-center retrospective electronic health record cohort study using routinely collected vascular surgery outpatient and inpatient records from Peking University People's Hospital between 2009 and 2024. Patients with VTE-related evidence and a definable hospital-captured index date were included. Treatment eras were prespecified as 2009-2014, 2015-2019, and 2020-2024. The study-defined documentation measure comprised therapeutic anticoagulation within 14 days and clinical follow-up, laboratory monitoring, and selective VTE-related ultrasound or imaging reassessment within 15-90 days.

Among 5998 patients with a definable hospital-captured index VTE-related event, the median age was 64.0 years, and 55.3% were female. Documented anticoagulation within 14 days increased from 34.1% in 2009-2014 to 58.0% in 2020-2024. Within 15-90 days, clinical follow-up was documented in 1483 patients (24.7%), laboratory monitoring in 366 (6.1%), and VTE-related ultrasound or imaging reassessment in 578 (9.6%). All four prespecified domains were documented in 149 patients (2.5%) overall and in 3.2% during 2020-2024. In multivariable analysis, the 2020-2024 era, pulmonary embolism presentation, and upper-extremity or catheter-related VTE were associated with higher odds of four-domain documentation completion.

In this 16-year electronic health record cohort, hospital-captured documentation of early anticoagulation increased, whereas documentation of 90-day follow-up processes remained infrequent; incomplete documentation or care delivered outside the hospital system may have contributed. These findings highlight opportunities to strengthen continuity and traceability of post-VTE management through timely clinical review and individualized decisions regarding treatment duration, safety monitoring, and selective imaging when clinically indicated.

Older adults with hypertension commonly experience poor sleep quality and reduced health-related quality of life (HRQoL). Previous studies have mainly examined these associations using total scores, providing limited insight into interactions between specific symptom dimensions. This study aimed to construct a component- and dimension-level network linking sleep quality and HRQoL and to compare network differences across depressive-symptom status.

This study included 2,257 older adults. Sleep quality, HRQoL, and depressive symptoms were assessed using the B-PSQI, EQ-5D-5L, and PHQ-9, respectively. We estimated a component- and dimension-level network based on the EBICGlasso-regularized Gaussian graph model, calculated centrality and bridge centrality metrics, validated stability using the bootstrap method, and compared network differences between the depressive and non-depressive-symptom groups.

The final network included 10 nodes and 32 non-zero edges among 45 possible edges, with a density of 0.711. The strongest associations were between sleep efficiency and sleep duration (SE-ST, 0.793), sleep interruption and subjective sleep quality (SW-SQ, 0.583), and self-care and usual activities (SC-UA, 0.560). Usual activities (UA) showed the highest strength centrality and expected influence, followed by subjective sleep quality (SQ), self-care (SC), and sleep efficiency (SE). Sleep efficiency had the highest bridge expected influence, followed by subjective sleep quality. Centrality indices demonstrated good stability (CS = 0.75). No significant differences were found in network structure (M = 0.224, P > 0.05) or global strength (S = 0.119, P > 0.05); repeated 1:1 subsampling broadly supported these findings.

Sleep components and HRQoL dimensions formed a closely connected network in older adults with hypertension. Usual activities showed the highest centrality, while sleep efficiency and subjective sleep quality showed prominent cross-community. These domains may be useful for screening or hypothesis generation but should not be interpreted as confirmed intervention targets.

Sleep disturbance is a prevalent issue among those who have experienced a stroke. The impact of gender on the prevalence of sleep disturbance within Asian stroke populations remains ambiguous. This research seeks to examine the prevalence of sleep disturbance among stroke survivors in Indonesia.

This quantitative prevalence analysis was based on the 2018 Indonesian Basic Health Research. A total of 7,147 stroke survivors who answered the sleep disturbance questions were included. The estimated prevalence and regression models were examined utilizing SPSS software.

The total prevalence of sleep disturbance among stroke survivors in Indonesia was 28.4% (95% CI: 27.4%-29.4%). Females exhibited a greater frequency of sleep disturbance than males (34.4% versus 26.1%, respectively). When categorized by age group, both females and males exhibited a trend of rising sleep disturbance prevalence with time. Moreover, daily smoking, low educational attainment, rural residency, and insufficient physical activity were correlated with sleep disturbance symptoms in the male cohort. In females, the presence of comorbidities such as cardiovascular disease and asthma was associated with sleep disturbance.

This study's findings revealed a significant prevalence of sleep disturbance among stroke survivors in Indonesia. Our findings indicate a gender influence on sleep disturbance prevalence, with females exhibiting a higher prevalence than males. These findings underscore the significance of sleep assessment and treatment in clinical or community environments.

BACKGROUND Eisenmenger syndrome develops from untreated or late-repaired cardiac shunts, causing irreversible pulmonary-vascular remodeling and systemic symptoms. Although timely repair has nearly eradicated Eisenmenger syndrome in high-income regions, delayed diagnosis in middle-income countries, especially when combined with chronic high-altitude hypobaric hypoxia, such as at approximately 2800 m (9186 ft) in the Ecuadorian Andes, can accelerate pulmonary hypertension through hypoxic vasoconstriction and erythrocytosis. We report a case of Eisenmenger syndrome 2 decades after surgical atrial septal defect closure. CASE REPORT A 46-year-old woman living at high altitude presented with severe cyanosis and heart failure 22 years after atrial septal defect closure. She had marked hypoxemia and secondary erythrocytosis. Echocardiography showed suprasystemic pulmonary artery pressure, severe right-chamber dilation, and reduced right ventricular systolic function. Right-heart catheterization confirmed Eisenmenger physiology with severe pulmonary-vascular resistance and low cardiac index. Chest computed tomography showed marked pulmonary artery enlargement without thromboembolic disease. Multidisciplinary management included bosentan 125 mg twice daily, tadalafil 10 mg once daily, nocturnal oxygen, diuretics, and anticoagulation, resulting in symptomatic stabilization and discharge on day 4. Transplant evaluation was initiated. CONCLUSIONS Delayed atrial septal defect repair at high altitude can lead to irreversible Eisenmenger syndrome, for which current therapy is palliative. Early defect recognition and closure, congenital heart screening, and access to pulmonary vasodilators and transplant programs are imperative in resource-constrained mountainous regions.

Brain injury remains the leading cause of mortality and morbidity among patients who experience cardiac arrest and cardiopulmonary resuscitation (CA/CPR). There is an urgent need to explore simpler and cheaper biomarkers to predict post-CA neurological outcomes. The red blood cell distribution width-to-albumin ratio (RA) has been used to assess inflammatory responses and prognosis in several diseases. This study was conducted to assess the correlation between RA levels and post-CA neurological outcomes, and to determine the value of RA in predicting neurological function after CA/CPR.

We conducted a retrospective observational study on out-of-hospital cardiac arrest (OHCA) cases presenting to our hospital's emergency department between January 2023 and April 2026. All patients were divided into cohorts with good or poor neurological outcomes according to cerebral performance categories (CPCs). Cox regression models were used to estimate the correlation between RA and neurological outcomes. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the ability of RA to predict neurological outcomes in patients after CA/CPR.

In total, 80 patients were involved, of whom 10 survived to hospital discharge with good neurological function (CPC ≤ 2), while the remaining subjects showed poor neurological function (CPC ≥ 3). RA levels were significantly higher in patients with poor neurological outcomes than in those with good outcomes. The AUC for the RA was 0.90, indicating excellent predictive accuracy. The RA values were independently associated with poor neurological outcomes following CA/CPR, even after adjusting for potential confounding factors.

We found that RA is associated with post-CA neurological outcomes, and higher RA levels could serve as a predictor of worse neurological outcomes in patients who undergo CPR after experiencing CA.

Recovery of upper-limb motor function after stroke often requires intensive, repetitive, task-oriented rehabilitation. Multimodal sensory-feedback robot-assisted training has the potential to enhance patient engagement and sensorimotor integration, and thereby improve rehabilitation outcomes.

To investigate the clinical and neurophysiological effects of adding multimodal sensory-feedback robot-assisted training to conventional rehabilitation for post-stroke upper-limb recovery using functional near-infrared spectroscopy (fNIRS).

A total of 38 stroke patients were randomly assigned to a control group (conventional rehabilitation, n = 19) or an experimental group (dose-matched conventional rehabilitation plus multimodal sensory-feedback robot-assisted training, n = 19). Upper-limb motor function was assessed before and after intervention using the Fugl-Meyer Assessment for the Upper Extremity (FMA-UE). fNIRS was used to evaluate resting-state functional connectivity (Fisher z-transformed connectivity, zFC) and task-evoked cortical activation (HbO) during shoulder, elbow, and finger flexion tasks.

No significant between-group difference in FMA-UE was observed at baseline (p > 0.05). After intervention, the experimental group showed significant improvement in FMA-UE, whereas the control group showed a smaller, non-significant improvement; the magnitude of pre-post change differed significantly between groups (p < 0.05). Resting-state fNIRS showed no significant between-group differences in zFC at baseline, whereas post-intervention analyses showed enhanced fronto-motor zFC in the experimental group, including connections involving PreM&SMC, DLPFC, and FEF. Task-fNIRS revealed channel-specific group × time interaction effects in HbO responses during the three motor tasks; post-hoc analyses showed significant post-intervention reductions in cortical activation at selected channels in the control group, whereas the experimental group showed a relatively preserved activation pattern.

Adding multimodal sensory-feedback robot-assisted training to dose-matched conventional rehabilitation may improve short-term post-stroke upper-limb motor recovery. fNIRS further revealed intervention-related changes in cortical activation and resting-state functional connectivity.

Identifier, ChiCTR2400080101.

Functional neurological recovery after ischemic stroke remains a formidable challenge in neuroscience. Exosomes serve as pivotal mediators of intercellular communication, and the microRNAs (miRNAs) they carry, in particular, offer a promising "cell-free therapy" strategy for promoting neurological repair. This review systematically summarizes the multi-target mechanisms by which exosomal miRNAs regulate the neurovascular unit (NVU) and outlines technical strategies to enhance exosomal therapeutic efficacy through targeted modification and engineered cargo loading, with the aim of constructing a smart drug delivery system capable of precise navigation. Following the trajectory of "natural exosomes-engineered exosomes-clinical translation", this review addresses the core scientific question of how to transform exosomal miRNAs from natural messenger molecules with basic reparative activity into an intelligent therapeutic system for precise targeted delivery. It further explores precision exosome treatment models based on the pathological staging of stroke progression, and integrates single-cell, spatial transcriptomic, and multi-omics technologies to decode the "miRNA-cell source-target cell-signaling pathway" regulatory axis, thereby identifying candidate miRNA combinations with translational potential. Finally, this review provides an in-depth analysis of the core challenges in translating such nanotherapeutic strategies from the bench to the bedside, including manufacturing standardization, quality control, and potency assessment, with the aim of providing a theoretical basis for advancing exosomal miRNA therapies from mechanistic studies to precision stroke treatment.

Quality control (QC) and quality assurance (QA) are critical for validating laboratory data in longitudinal studies. The Tehran Lipid and Glucose Study (TLGS), the first large cohort study in Iran, was designed to investigate the incidence of and risk factors for cardiovascular diseases. This article reviews the methodological quality control system used for biochemical testing in the TLGS, with an emphasis on its design, implementation, evaluation, and data stability across study phases.

In this methodological review, internal and external quality-control protocols used in phases 2 to 7 of the TLGS were analyzed and compared with international standards, including those of the Cardiovascular Health Study and the Atherosclerosis Risk in Communities study. Analytical precision data (coefficient of variation [CV%]) for glucose, creatinine, total cholesterol, triglycerides, HDL-C, ALP, ALT, and AST were extracted from a central database, and temporal trends were evaluated. Internal quality control was performed daily using two levels of control sera (normal and abnormal), and interlaboratory accuracy was assessed through participation in an external evaluation program.

The mean CV for all tests across the study phases was less than 5% (glucose, 1.95%; creatinine, 3.10%; cholesterol, 2.05%; triglycerides, 2.16%; HDL-C, 3.33%; ALP, 2.10%; ALT, 3.00%; and AST, 3.35%). External quality-control results received an "Excellent" rating for all parameters. The temporal trend in CVs demonstrated stability and a gradual improvement in precision across phases. Levey-Jennings charts, Westgard rules, and weighted regression methods were effective in detecting systematic deviations and enabling prompt corrective action.

Establishing a multilevel QC/QA system in the TLGS ensured the stability and accuracy of biochemical data in a large national cohort. The findings indicate that the accuracy of biochemical testing was consistent with international standards and that the resulting data are highly reliable for epidemiological and clinical analyses. This experience may serve as a local model for other longitudinal studies in developing countries.

Atherosclerosis (AS) remains a leading cause of cardiovascular morbidity and mortality worldwide, with current treatments focused primarily on reducing low-density lipoprotein levels while failing to repair damaged endothelial cells, thus highlighting the urgent need for novel therapeutic drugs. To address this challenge, we analyzed human AS patient single-cell RNA sequencing datasets to identify disease-driving genes and then employed connectivity map analysis to screen for potential therapeutic compounds. Using network pharmacology and machine learning to predict core drug targets, the study validated drug-target interactions through molecular docking, molecular dynamics simulations, and surface plasmon resonance analysis, with experimental validation conducted using endothelial cell damage models and ApoE ^-/- atherosclerotic mice. The integrative approach successfully identified narciclasine as a promising therapeutic compound that targets vascular cell adhesion molecule 1 and intercellular adhesion molecule-1 (VCAM-1/ICAM-1) for AS treatment, with molecular studies confirming strong binding affinity and experimental validation demonstrating significant alleviation of endothelial dysfunction through downregulation of VCAM-1/ICAM-1 expression and reduction of aortic plaque burden in mouse models. This multiplatform methodology combining single-cell sequencing, network pharmacology, machine learning, computational simulation, and experimental validation provides a robust framework for drug discovery while positioning narciclasine as a promising therapeutic candidate warranting clinical investigation for AS treatment.