BACKGROUND:The incidence of Acute Myocardial Infarction (AMI) is rising among younger populations. Despite advancements in treatment protocols, improvements in morbidity and mortality remain limited. OBJECTIVE:To identify risk factors for cardiogenic death and stroke within one year in prematureAMI patients (≤55 years) and to develop a prognostic risk prediction model and scoring scale for comprehensive risk assessment. METHODS:Utilizing clinical study NCT03297164 and the follow-up center database, we included 3630 participants enrolled from January 2017 to August 2022 to create training and testing sets. An external set (n = 472) was then selected. Cox proportional hazards and LASSO regression were employed to identify predictive factors, and β coefficients from multivariable Cox regression were utilized to develop the scoring scale. RESULTS:Seven predictors were selected. The scoring scale achieved an AUC of 0.75 (0.66-0.84) in the test set and 0.77 (0.63-0.91) in the external set, outperforming the GRACE score (0.61 and 0.50, respectively). Based on event rate distributions, patients were stratified into three risk groups, with significant differences in event rates observed across subsets (log-rank test, P < 0.05). Further optimization of binning strategies, guided by the correlation between predictors and outcomes, resulted in a model with an AUC of 0.83 (0.72-0.93) in the external set. A corresponding web application was developed for supplementary risk assessment. CONCLUSIONS:This study developed and validated a practical scoring scale and a prediction model based on optimized binning strategies for premature AMI patients, offering a comprehensive risk assessment to support clinical decision-making.

Background Acute myocardial infarction (AMI) is a leading cause of cardiac mortality, necessitating accurate risk prediction models; however, current risk assessment models may not reflect the changes in risk factors in current medical practice. This study aimed to develop and validate a machine learning-based risk prediction model for 1-year post-discharge cardiac mortality among patients with AMI who survived hospitalization, utilizing a multidimensional dataset that integrates environmental determinants and angiographic findings. Methods Data were sourced from a multicenter prospective cohort study (NCT03297164) along with the supplementary AMI cohort from the coordinating medical center, covering the period from January 2017 to July 2022. Patients from the coordinating center constituted the discovery cohort (n = 11,752), while patients from the participating centers served as the external validation cohort (n = 2,593). Random forest, XGBoost, logistic regression, CatBoost, decision tree, and LightGBM algorithms were applied, and the feature selection was performed using SelectFromModel.The model with the strongest overall performance in the internal testing cohort underwent external validation. Results The random forest model was selected, achieving areas under the curve (AUCs) of 0.86 (95% CI: 0.82–0.89) and 0.81 (95% CI: 0.75–0.86) in the internal testing and external validation cohorts, respectively. Frequently selected predictors included age, body mass index, temperature, PM2.5 concentration, Gensini score, weighted diffuse lesion value, and ejection fraction. Random forest outperformed the global registry of acute coronary events (GRACE) score in both cohorts, with AUCs of 0.80 (95% CI: 0.75–0.84) and 0.77 (95% CI: 0.71–0.83), respectively. Compared with the GRACE-based stratification, the risk stratification based on the random forest algorithm also resulted in greater discrimination in both cohorts (AUC: 0.83 vs. 0.64; 0.77 vs. 0.68). Conclusion This study presents a discharge-oriented model for 1-year post-discharge cardiac mortality risk stratification in AMI survivors. Developed and validated using multidimensional data, the model demonstrates superior predictive performance compared with the GRACE score.

The association between apolipoprotein and chronic obstructive pulmonary disease (COPD) has been reported in observational studies. However, the causality of apolipoprotein on COPD remains unknown. A 2-sample Mendelian randomization (MR) analysis was performed to investigate the causal association of apolipoprotein with COPD using summary-level data. Genome-wide association studies of two apolipoproteins, apolipoprotein A-1 (ApoA-I) and apolipoprotein B, were selected as instrumental variables. COPD was included as the outcome. A significant association between ApoA-I and COPD risk was found using the inverse-variance weighted (IVW) method (odds ratio [OR]: 0.993, 95% confidence interval [CI]: 0.990-0.997, P = .0003). However, contrasting results were observed using the weighted median (OR: 0.995, 95% CI: 0.989-1.001, P = .119) and MR-Egger (OR: 0.992, 95% CI: 0.986-0.998, P = .015) methods. Since both pleiotropy and heterogeneity tests were negative (intercept = 6.032e-06, P = .948; Q = 98.996, Q-value = 0.696), and after MR-PRESSO correction, the IVW estimates can be considered acceptable. After adjusting for confounding factors, the genetic predisposition to higher levels of ApoA-I (OR = 0.993, 95% CI: 0.990-0.997, IVW P value = 0.0003) is causally associated with a reduced risk of COPD. No causal effect was found between apolipoprotein B and COPD.

Visceral fat accumulation is a key factor in the onset of cardiometabolic diseases, including hypertension. Metabolic Score for Visceral Fat (METS-VF) is an innovative, non-invasive metric developed to estimate visceral fat based on commonly accessible clinical parameters. A total of 13,822 participants were included in this cross-sectional analysis. METS-VF was calculated using a validated formula incorporating age, sex, metabolic score for insulin resistance, waist-to-height ratio. Hypertension was defined based on measured blood pressure or self-reported physician diagnosis. Logistic regression models were used to estimate the association between METS-VF and hypertension, adjusting for sociodemographic, clinical, and dietary covariates. Subgroup, threshold effect, and ROC analyses were conducted to assess robustness and predictive ability. External validation was conducted using 8400 fasting participants from the China Health and Retirement Longitudinal Study (CHARLS) 2011 baseline cohort. METS-VF was positively associated with hypertension. In model 3, participants in the highest METS-VF quartile had substantially higher odds of hypertension (OR: 5.82, 95% CI 4.76-7.11, P < 0.001). A threshold effect was observed at a METS-VF value of 6.42. Subgroup analyses confirmed the consistency of associations across various demographic and clinical strata. Notably, high intake of protein and unsaturated fatty acids attenuated this association. ROC analysis showed METS-VF had the best discriminatory power for hypertension (AUC = 0.749) compared to BMI, WHtR and METS-IR. In the CHARLS external validation cohort, METS-VF also showed the highest AUC among the evaluated indices (AUC = 0.668), and logistic regression confirmed a consistent positive association with hypertension. METS-VF was significantly associated with prevalent hypertension and showed better discriminatory performance than traditional adiposity indices. External validation in CHARLS supports the robustness of these findings, although prospective validation is still warranted.

Heart failure with reduced ejection fraction (HFrEF) remains challenging to manage, particularly in Asian populations. Although vericiguat may complement guideline-directed medical therapy (GDMT), the safety and tolerability of rapid initiation and titration in Chinese patients with HFrEF require further evaluation. This single-center, prospective, single-arm, self-controlled cohort study included 140 patients who received at least 1 dose of vericiguat 5 mg and constituted the treated population; 133 had evaluable 14-day titration and short-term safety data. Patients were monitored for dose-titration success, blood pressure, renal function, electrolytes, hepatic function, hemoglobin, and N-terminal pro-B-type natriuretic peptide (NT-proBNP) over 14 days. Echocardiography was performed at 12 and 20 weeks. The mean age was 61.5 ± 14.2 years, and baseline left ventricular ejection fraction (LVEF) was 32.87 ± 8.51

Geese is one of the few poultry species with complete external genitalia, and the external genitalia abnormal development has become an important factor limiting the reproductive efficiency of the goose industry. Recent studies have shown that the gut microbiota plays an important role in regulating male reproductive processes, but its regulatory mechanisms in male geese's external genitalia development remain unclear. In this study, male geese with normal development (ND) and abnormal development (AD) external genitalia were selected as the research object, and multi-omics were used to investigate the regulatory of the microbe-mediated gut-testis axis on external genitalia development. At the transcriptomic level, we identified key DEGs (KNG1, P2RY4, SSTR5, and HRH3) in the testis and external genitalia between ND and AD groups, which were significantly enriched in the neuroactive ligand-receptor interaction pathway. Metabolomics analysis revealed that DMs in the ND and AD groups were significantly enriched in pathways related to aromatic amino acid metabolism and neural signal transduction. Furthermore, metagenomic results showed that the ND group was identified key bacterial genera g_Blautia and g_Faecousia affecting external genitalia development, which were associated with SCFAs synthesis and neuroendocrine signaling regulation. Integrated with multi-omics data, it was revealed that gut-derived neuroactive metabolic signals may participate in the molecular regulation of external genitalia development in male goose by modulating GPCRs signaling. Our findings not only provide new insights into the gut-testis axis regulates the development of external genitalia in male geese, but also contribute to improving the reproductive performance of male geese.

The biological aging of vascular smooth muscle cells (VSMCs) is a critical event contributing to vascular aging and age-related diseases. The objective of this study is to assess the potential mechanism by which eugenol inhibits vascular senescence by downregulating milk fat globule-EGF factor 8 (MFG-E8) expression in VSMCs and vascular tissues. A model of angiotensin II (Ang II)-induced vascular aging in mice and a premature aging model in human vascular smooth muscle cells (HVSMCs) were established to assess the efficacy of eugenol intervention, with valsartan, an Ang II receptor antagonist, serving as a positive control drug. Senescence-associated-β-galactosidase (SA-β-gal) staining, along with the detection of senescence marker molecules p21 and p53, were used to assess the senescence status of cells and vascular tissues. The expression level of MFG-E8 was detected using immunohistochemistry, reverse transcription-quantitative PCR, and western blot analysis. HVSMC cell lines with MFG-E8 knockdown and overexpression were generated using short hairpin RNA and plasmid overexpression methods, respectively, to assess the role of MFG-E8 in the anti-senescence effects of eugenol on VSMCs. Eugenol inhibited Ang II-induced premature senescence in both vascular tissues and HVSMCs, significantly enhancing arterial stiffness and structural changes in aged vessels. It also attenuated the senescence-associated secretory phenotype (SASP) and enhanced the proliferative activity of senescent VSMCs. Ang II exposure led to increased MFG-E8 expression in cells and vascular tissues, a change that eugenol was able to reverse. Knockdown of MFG-E8 suppressed the Ang II-induced senescence phenotype in HVSMCs, whereas overexpression of MFG-E8 directly induced HVSMC senescence and counteracted the anti-aging effects of eugenol. Eugenol prevents Ang II-induced aging in VSMCs and vascular tissues by downregulating MFG-E8 expression, underscoring its potential as an antiaging drug.

Background Iron deficiency management in acute heart failure (AHF) relies on ferritin and transferrin saturation (TSAT), yet the prognostic significance of TSAT within the hyperferritinemic range (ferritin ≥ 300 ng/mL)—where patients are currently classified as iron-sufficient—has not been systematically examined in critically ill AHF populations. Methods We conducted a retrospective cohort study using the MIMIC-IV database (2008–2019), including 1,395 adult patients admitted to the intensive care unit (ICU) with AHF who had ferritin and TSAT measured within 48 hours of admission. Patients were classified into five iron metabolism phenotypes using European Society of Cardiology (ESC) guideline thresholds. The primary analysis compared HyperF+HighTSAT (ferritin ≥ 300 ng/mL, TSAT ≥ 20%, n = 306) versus HyperF+LowTSAT (ferritin ≥ 300 ng/mL, TSAT < 20%, n = 332). The primary outcome was in-hospital all-cause mortality, analyzed via multivariable logistic regression with sequential covariate adjustment (Model 0–3). Secondary outcomes included 28-day and 1-year mortality assessed by Cox proportional hazards models and Kaplan-Meier curves. Results In-hospital mortality showed a clear gradient across phenotypes: 6.6% (absolute iron deficiency), 11.9% (functional iron deficiency), 8.8% (normal iron), 14.8% (HyperF+LowTSAT), and 27.8% (HyperF+HighTSAT). Among the 638 hyperferritinemic patients, those with high TSAT had significantly higher in-hospital mortality than those with low TSAT (adjusted OR 1.71, 95% CI 1.06–2.75, P = 0.027). One-year survival was significantly worse in the high-TSAT group (adjusted HR 1.45, 95% CI 1.12–1.86, P = 0.004). Subgroup analyses showed consistent directional associations across all strata. Conclusions Among AHF patients classified as iron-sufficient by current ferritin-based criteria, an elevated TSAT (≥ 20%) identifies a subgroup with substantially increased in-hospital and 1-year mortality, independent of established illness severity markers.

Dysfunction in the brain's resting-state functional networks is strongly connected with mental illness and cognitive impairment, while cardiovascular disease (CVD) is accepted as a risk factor for cognitive dysfunction. Growing interest exists in the correlation between brain and heart diseases. However, the causality between resting-state functional networks and CVD remains uncertain. In this research, a two-sample Mendelian randomization (MR) approach was applied to explore the causal association between 191 resting-state functional magnetic resonance imaging (rsfMRI) traits and 10 CVDs. This MR study employed single nucleotide polymorphisms that are strongly associated with rsfMRI phenotypes, which were sourced from the Zenodo database. We aimed to determine the causal relationship between rsfMRI phenotypes, considered as the exposure, and CVD, defined as the outcome. We engaged inverse variance weighting as our primary analytical method and executed a comprehensive sensitivity analysis to assess the heterogeneity and dependability of the results. Additionally, to validate the robustness of the findings, the test thresholds were recalibrated using the Bonferroni correction method. Functional connectivity among the angular gyrus, precuneus, cingulate gyrus, and parietal lobe also increased the hazards of atrial fibrillation (ORIVW = 0.644, 95% CI: 0.527-0.788, P = 1.83 × 10-5). Moreover, MR analyses of brain network connectivity concerning other CVDs did not meet the Bonferroni-corrected P-value threshold. Changes in functional connectivity of brain networks may be an indicator of risk for the development of atrial fibrillation but are not associated with the development of other CVDs.

Heart failure (HF) represents the terminal stage of cardiovascular disease and remains a leading cause of mortality. Epidemiological studies indicate a high prevalence and mortality rate of HF globally. Current treatment options primarily include pharmacological and non-pharmacological approaches. With the development of mesenchymal stem cell (MSC) transplantation technology, increasing research has shown that stem cell therapy and exosomes derived from these cells hold promise for repairing damaged myocardium and improving cardiac function, becoming a hot topic in clinical treatment for HF. However, this approach also presents certain limitations. This review summarizes the mechanisms of HF, current treatment strategies, and the latest progress in the application of MSCs and their exosomes in HF therapy.

Cardiovascular diseases (CVD) remain the primary cause of morbidity and mortality in developed countries, highlighting the urgent need to identify biomarkers associated with CVD and its risk factors. Vascular adhesion protein-1 (VAP-1), a 170 kDa surface molecule expressed predominantly by endothelial cells, smooth muscle cells, and adipocytes, has garnered significant attention in this field. Beyond its role in inducing inflammatory mediators, VAP-1 is closely linked to coronary artery disease, heart failure, diabetes, obesity, and other CVDs, along with their associated risk factors. Notably, elevated plasma VAP-1 activity has been observed in patients with CVD and diabetes. The toxic metabolites produced by its enzymatic activity contribute to vascular endothelial injury and oxidative stress, thereby accelerating atherosclerosis and diabetes-related cardiovascular complications. Consequently, understanding the pathophysiological roles of VAP-1 in CVD has become a major research focus. This review examines the effects of VAP-1 on CVD pathogenesis and explores the therapeutic potential of VAP-1 inhibitors in managing these conditions.

Cardiac bridging integrator 1 (cBIN1) is a cardiomyocyte-specific protein critical for excitation–contraction coupling. The cBIN1 score (CS), derived from plasma cBIN1 levels, serves as a non-invasive biomarker reflecting myocardial microstructural integrity and is unaffected by systemic inflammation or BMI. A total of 108 HFpEF patients and 108 matched controls were retrospectively included. All subjects underwent clinical evaluation, echocardiography, and biochemical testing. Plasma cBIN1 was measured by ELISA, and CS was calculated. Multivariate logistic regression and ROC analyses were used to assess the diagnostic and prognostic value of CS for HFpEF and major adverse cardiac events (MACE) during 1-year follow-up. A sensitivity analysis was performed by excluding patients with chronic kidney disease or eGFR < 60 ml/min/1.73 m² to address renal-related confounding. CS levels were significantly higher in the HFpEF group (p < 0.001). LVEF, E/e′, neutrophil-to-lymphocyte ratio (NLR), BNP, and CS were independently associated with HFpEF. CS showed positive correlations with BNP, sST2, left atrial diameter, and E/e′, and a negative correlation with LVEF. ROC analysis yielded an AUC of 0.805 for CS in diagnosing HFpEF (sensitivity 70.4

BACKGROUND:Oxidative stress (OS) is linked to the development of multiple sclerosis (MS), but the causal relationship in terms of genetic pathophysiology remains ambiguous. We employed Mendelian randomization (MR) and colocalization analysis to explore the relationship between OS genes and MS, utilizing an integrative multi-omics approach. METHODS:We obtained data from a genome-wide association study (GWAS) of MS from the International Multiple Sclerosis Genetics Consortium (Discovery phase) and the FinnGen study (Replication phase). Mendelian randomization analyses were conducted using summary data to evaluate the association between molecular features of OS-related genes and MS. Additional colocalization analyses were undertaken to ascertain whether the identified signal pairs shared causal genetic variants. RESULTS:Integration of multi-omics data, including mQTL-eQTL and eQTL-pQTL, revealed that the STAT3 gene is associated with MS, supported by Level 1 evidence. The CR1 gene shows an association with MS risk, evidenced by Level 3 support. Methylation at cg24718015 and cg17833746 in the STAT3 gene correlates with reduced expression of STAT3. At the protein level, high circulating levels of STAT3 are inversely associated with MS risk (OR: 0.43, 95% CI, 0.33-0.54). Elevated levels of TNFRSF1A are also linked with a decreased risk of MS (OR: 0.21; 95% CI, 0.12-0.37), while higher levels of CR1 are positively associated with an increased risk of MS (OR: 1.17; 95% CI, 1.08-1.27). CONCLUSION:This study identifies specific OS genes that are associated with MS and enhances our understanding of its pathogenesis.

PurposeThis research aimed to investigate the association between neutrophil-percentage-to-albumin ratio (NPAR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI) with disease severity in patients diagnosed with acute myocarditis.MethodsA total of 185 patients were diagnosed with acute myocarditis at the First Hospital of Jilin University between 2018 and 2024. The related values of NPAR, SII, SIRI, and AISI were computed based on the pertinent blood indices that were acquired within 12 hours of admission. The best cut-off values for NPAR, SII, SIRI, and AISI, as well as their associated sensitivity and specificity, were determined using ROC curve analysis in order to assess their predictive usefulness for poor prognosis upon admission.ResultsPatients with fulminant myocarditis exhibited significantly higher NPAR, SII, SIRI, and AISI values compared to those with mild myocarditis. Spearman correlation analysis revealed significant associations between these inflammatory indices and NYHA scores at admission (r = 0.370, 0.296, 0.284, and 0.246, respectively; P < 0.01). Multivariate logistic regression analysis identified high NPAR (OR: 5.44 95%, CI:1.81 ~ 16.36, P=0.003), SII (OR: 1.01 95%CI:1.01 ~ 1.01, P=0.010), SIRI (OR: 1.21, 95%CI:1.06 ~ 1.37, P=0.005), and AISI (OR: 1.01 95%CI:1.01 ~ 1.01, P=0.007) values as independent risk factors for myocarditis severity.ConclusionsOur study demonstrated that inflammatory biomarkers - NPAR, SII, SIRI, and AISI - show associations with the severity of acute myocarditis.

Collaborative robots, or cobots, face ongoing safety challenges when operating in direct contact with human operators. This study explores how Series Clutch Actuators (SCAs) can enhance collision safety beyond mere detection and avoidance, focusing on strategies for mitigating sustained forces during and after collisions. Three distinct post-collision response strategies were implemented to enable a human to move the robot after an impact, while the robot remains stationary against gravity: partially engaged clutches (off-power torque-limit), minimally engaged clutches (clutch torque-limit equivalent to torque from gravity), and continuously slipping clutches due to motor input. We used the collaborative robot Nicebot-7 with SCA-joints. Unlike previous iterations of Nicebot, Nicebot-7 does not require passive gravity compensation. The torque instability of the friction clutches in Nicebot-7 was experimentally evaluated and addressed with damping terms when the clutches slipped. Experimental evaluations were conducted in different motion planes (horizontal and vertical), enabling an analysis of escape forces. Results demonstrate that continuously slipping clutches minimize post-collision escape forces especially against gravity. This improvement is particularly relevant for quasi-static collisions, where users experience sustained compression (see Fig. 1). We demonstrate how cobots can become safer to operate, reducing risk to human partners.

BACKGROUND AND PURPOSE:This study aims to examine the global, regional, and national burden of stroke in young adults from 1992 to 2021. METHOD:We conducted a comprehensive assessment of stroke metrics among individuals aged 15-49 using data from the 2021 Global Burden of Disease (GBD) database, covering 204 countries at global, regional, and national levels. The metrics evaluated included age-standardized incidence rates (ASIR), death rates (ASDR), disability-adjusted life years (DALYs), average annual percentage changes (AAPCs), and joinpoint regression analysis. RESULTS:Between 1992 and 2021, the ASIR, ASDR, and DALYs for ischemic stroke (IS), intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH) among young adults globally decreased. The incidence, mortality, and DALYs for all three stroke types declined in both young females and males. In countries with low-middle and middle Socio-demographic Index (SDI), the ASIR for IS showed an upward trend, while the ASIR for ICH and SAH decreased across different SDI countries. Nationally, the incidence, death, and DALYs for all three types of stroke decreased in the vast majority of countries, with only a few countries showing an increased trend. CONCLUSION:From 1992 to 2021, the overall trend in stroke burden among young adults was downward. However, in certain countries and regions, incidence, death, and DALYs related to stroke still rose. It is crucial for nations around the globe to adopt comprehensive, easily accessible, and cost-effective strategies aimed at improving stroke monitoring, prevention, emergency treatment, and rehabilitative care, ultimately alleviating the impact of stroke.

Insulin resistance (IR) reduces insulin efficacy and heightens the danger of cardiovascular diseases including hypertension. The Metabolic Score for Insulin Resistance (METS-IR), which is based on triglyceride (TG) and high-density lipoprotein cholesterol (HDL-C), body mass index (BMI), and fasting glucose levels, provides a simpler way to assess IR. As the hypertension’s prevalence increases, particularly in those with metabolic disorders, exploring the relationship between hypertension and METS-IR has become crucial. 16,310 individuals from the 2007–2018 National Health and Nutrition Examination Survey dataset was included. Hypertension was defined by asking participants about their medical history and blood pressure measurements. METS-IR was calculated as follows: ln([ HDL-C (mg/dL)] × [2 × fasting glucose (mg/dL)] + TG (mg/dL) × BMI (kg/m2)). The study adjusted for covariates like sex; age; race; poverty-income ratio; marital status; educational background; total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and serum creatinine levels; smoking; stroke; alcohol consumption; diabetes; and coronary heart disease (CHD). This study was conducted using a multi-factor regression model. This research demonstrated a significant positive relationship between hypertension and METS-IR. Each 1-unit rise in METS-IR corresponds to a 3

This article presents a novel 3-axis Halbach permanent magnet elastomer (H-PME) sensor for the robotic application, which effectively reduces crosstalk along when two sensors are used simultaneously in close proximity, for example, during grasping of thin and delicate objects, needle threading, etc. This sensor integrates a Halbach-array magnetic elastomer, a 3x3 Hall sensor matrix, and a silicone layer. The magnetic elastomer is produced by combining NdFeB powders with a diameter of 5 mu m into silicone, following a weight ratio of 50%, and then magnetized using 2D Halbach-array magnets. Simulation results reveal the capability to adjust magnetic field strength and distribution by altering the magnet's orientation. The sensor's efficacy in 3-axis sensing is validated through calibration with a linear model, achieving a good root-mean-square error below 0.7 N in force measurement. The H-PME sensor, with a thickness of merely 4.5 mm, can detect forces up to 50 N. It's simple 3-layer design allows the thickness to be reduced to as low as 2 mm, while also offering ease of replacement. Crucially, crosstalk evaluation experiments show that the proposed H-PME sensor can dramatically mitigate crosstalk interference. Magnetic tactile sensors experience crosstalk when multiple sensors operate nearby, complicating tasks like gripping thin objects. Magnetic noise between Hall sensing units also affects calibration within a single sensor. This article thus introduces a soft 3-axis Halbach permanent magnet elastomer (H-PME) sensor, supporting 3-axis force sensing with a 4.5 mm thickness and up to 50 N sensing range.image (c) 2024 WILEY-VCH GmbH