Search Results (4,714)

Background: Carbon monoxide poisoning (COP) has emerged as a significant health issue in Asian countries, including Taiwan. It poses serious risks, including long-term complications such as cardiovascular disease (CVD), neurological disorders, and even death. This study investigated the association of COP with the development of cardiovascular diseases and neurological sequelae, while evaluating all-cause and cause-specific mortality as secondary outcomes. Methods: This retrospective study utilized the National Health Insurance Research Database and included the patients aged ≥ 20 years hospitalized with a COP diagnosis between 1 January 2000 and 31 December 2015. The objective was to investigate long-term neurological complications, CVD (such as ischemic heart disease and other cardiac conditions), and associated risk factors. Cox proportional hazard regression was employed to analyze differences in long-term neurological sequelae and cardiovascular outcomes among various groups. Results: A total of 2421 COP patients were enrolled. COP patients with CVD history had a higher incidence of persistent neurological sequelae (PNS) in two different diagnostic codes (8.6%, p < 0.001 and 11.5%, p = 0.018), but COP patients without CVD history had a higher incidence of delayed neurological sequelae (DNS) only in one of the diagnostic codes (6.8%, p < 0.001). The risk from CVD factor was up to 11.92 times. Furthermore, the overall mortality was 8.8%, which is significantly higher than 3.7% in the general population. After adjusting for other factors, the mortality in COP individuals was 7.40 times higher than that of the general population. Conclusions: Patients with COP might be at high risk of developing CVD and have a significantly increased risk of CVD. COP is associated with a higher risk of long-term neurological complications and an increased incidence of CVD. These findings help mitigate the potential long-term health impacts of COP. Full article

Heart valve prostheses play a key role in regulating the normal cardiac function for patients with valvular diseases, yet even slight alterations in their flow dynamics can result in serious physiological consequences. This paper provides an overview of in vitro studies using Particle Image Velocimetry (PIV) to investigate the hemodynamics of heart valve prostheses. We first trace the historical evolution of prosthetic valve designs and highlight key milestones in their development. Key experimental considerations for PIV apparatus design are summarized. Subsequently, we review major in vitro PIV studies that have enhanced understanding of prosthetic valve hemodynamics, including flow patterns, turbulence characteristics, and flow–structure interactions. Finally, we outline current challenges and propose future research recommendations, highlighting the potential of integrating advanced PIV methods with high-fidelity imaging for improved assessment of prosthetic valve performances. Overall, the study of heart valve prostheses remains inherently complex due to the multiscale nature of hemodynamic phenomena. Recent advances in experimental fluid mechanics, particularly PIV, have significantly enhanced the ability to visualize and quantify the hemodynamics of prosthetic valves, providing valuable insights for optimizing design and improving the durability of next-generation valve prostheses. Full article

Duchenne muscular dystrophy (DMD) is a severe X-linked neuromuscular disease (NMD) caused by loss-of-function mutations in the DMD gene. RNA-based therapies, especially antisense oligonucleotides (ASO)-mediated exon skipping and adenosine deaminase acting on RNA (ADAR)-guided RNA editing, have emerged as complementary approaches that modulate pre-mRNA splicing or correct transcripts without altering genomic DNA. Current phosphorodiamidate morpholino oligomer (PMO) drugs targeting exons 51, 53, and 45 provide mutation-class-specific benefit. At the same time, next-generation delivery strategies (e.g., peptide-conjugated PMOs (PPMOs), antibody–oligonucleotide conjugates (AOC), and endosomal-escape vehicles) aim to improve skeletal, cardiac, and diaphragm exposure. In parallel, RNA editing strategies offer a route to correct select nonsense or missense variants at the base level and may, in principle, restore near-native dystrophin expression. Meaningful translation of these modalities requires predictive large-animal models. A genome-edited microminipig (MMP) bearing DMD exon-23 mutations faithfully recapitulates hallmark features of human DMD. That includes early locomotor deficits, elevated serum creatine kinase (CK) and cardiac troponin T, progressive myocardial fibrosis, and a decline in left-ventricular ejection fraction (LVEF), while maintaining a manageable lifespan of approximately 30 months suitable for long-term studies. In particular, the MMP model provides a practical platform for addressing the persistent challenge of efficient therapeutic delivery to the heart and diaphragm through longitudinal dosing, imaging, and biopsy. In this review, we synthesize clinical progress in exon skipping, outline the promise of RNA editing, and integrate recent insights from Duchenne muscular dystrophy model for microminipigs (DMD-MMPs) as an advanced surrogate for preclinical development and translational evaluation. Full article

Background/Objectives: Predicting 30-day mortality after in-hospital cardiac arrest (IHCA) remains challenging. We developed an interpretable CatBoost model that incorporates the m-NUTRIC score, age, and selected micronutrient biomarkers (i.e., magnesium, zinc, vitamin D, and vitamin B12). We compared its performance with that of logistic regression and quantified variable contributions using SHAP. Methods: Variables were extracted from the electronic medical records of 880 patients with IHCA admitted to a medical intensive care unit. The CatBoost and logistic regression models were trained on a stratified 80/20 split. The decision threshold was optimized using the Youden index (0.482). Discrimination (ROC-AUC with bootstrap confidence intervals), classification metrics, precision–recall analysis, calibration, and decision curve analysis were reported. Results: CatBoost achieved a ROC-AUC of 0.850 (95% confidence interval [CI]: 0.822–0.879) in the training set and 0.827 (95% CI: 0.760–0.887) in the internal test set, outperforming logistic regression (0.797; 95% CI: 0.720–0.861). The test set accuracy, precision, recall, F1-score, specificity, and average precision were 0.761, 0.847, 0.790, 0.817, 0.702, and 0.909, respectively. The Brier score was 0.186. Decision curve analysis showed net benefit across threshold probabilities of 0.20–0.70. The SHAP analysis identified m-NUTRIC and age as the dominant predictors, whereas micronutrients served as complementary contextual factors. Conclusions: The CatBoost model consistently outperformed the logistic regression and warrants prospective multicenter validation. Full article

Diabetes mellitus is projected to affect more than 1.3 billion people worldwide by 2050, with millions remaining undiagnosed or in a prediabetic state. Cardiovascular complications account for nearly half of diabetes-related deaths, highlighting the need for scalable tools capable of identifying metabolic dysregulation before irreversible cardiac damage develops. This review synthesizes current mechanistic, clinical, and computational evidence linking diabetes to cardiac electrophysiological remodeling and examines electrocardiography (ECG) as a non-invasive modality for early detection of dysglycaemia. Chronic hyperglycaemia, insulin resistance, oxidative stress, microvascular dysfunction, and cardiac autonomic neuropathy collectively contribute to measurable ECG alterations, including QT/QTc prolongation, increased QT dispersion, changes in Tp–e indices, and reduced heart rate variability. These changes often precede overt cardiovascular disease and correlate with glycaemic burden and diabetes duration. Recent advances in signal processing and artificial intelligence have expanded the diagnostic potential of ECG. Both classical machine learning approaches and large-scale deep learning models demonstrate that ECG contains latent signatures associated with incident type 2 diabetes and glycaemic status. Despite promising results, heterogeneity in study design, limited representation of prediabetes, and lack of standardized validation frameworks remain major barriers to clinical translation. Prospective, multi-ethnic studies are needed to establish ECG-based screening as a reliable component of early diabetes detection strategies. Full article

Honey, as a natural and nutritious sweetener, is one of the most widely consumed foods worldwide. However, the presence of phytotoxins in honey and the influence of honey’s intrinsic sugar matrix on the toxicity of these phytotoxins remain insufficiently explored. An optimized liquid chromatography–quadrupole trap tandem mass spectrometry method was developed to quantify 17 toxic alkaloids in 150 raw honey samples. Camptothecin was identified for the first time in the tested samples and was the most prevalent contaminant (36% detection, max 3.09 μg/kg), which induced cardiac hypertrophy and impaired cardiac function in zebrafish assays. The honey sugar matrix further potentiated these adverse cardiac effects through exacerbating oxidative stress and upregulating pro-inflammatory and pro-apoptotic gene expression, while natural honey partially mitigated such damage by upregulating the key antioxidant gene nrf2, thereby downregulating il-1β and regulating the bcl2/bax expression ratio. This study offers novel insights into honey phytotoxins’ matrix-modulated toxicity, laying a scientific foundation for optimizing safety protocols and matrix-specific risk standards. Full article

Background: Resynchronization therapy has become a cornerstone in patients with heart failure (HF). Recent advancements in this field have led to the development of the so-called “left bundle branch area pacing” (LBBAP), a form of pacing where a single ventricular catheter directly addresses the left bundle for a more physiological stimulation. The current literature provides encouraging evidence regarding this topic, but there is still limited data for the older population, particularly those aged ≥75 years. This review aims to clarify how LBBAP has been explored in this cohort and if its application could be safe and effective even in the most advanced stages of life. Methods: A search of articles from PubMed was conducted. Patients were considered older if above 75 years of age. Data regarding Italian statistics were obtained from national registries. Results: The current literature supports the safety and effectiveness of LBBAP in older patients across different indications, with outcomes comparable to those reported in younger patients and a suggested cost-effectiveness. Conversely, data regarding patients affected by cardiac amyloidosis are still inconclusive. Conclusions: LBBAP represents a valuable resource for patients of all ages, but frailty is a major issue in the older population that needs to be addressed. The potential integration of this technology with defibrillator capabilities will enable an even more extensive application in the near future. Full article

Artificial Intelligence (AI) has strong potential in health monitoring systems to support high-quality healthcare while mitigating cybersecurity risks. AI-based solutions for health and wellness applications, particularly for cardiovascular disease monitoring, are being explored to address complex healthcare challenges and improve patient outcomes. The integration of quantum and AI-based techniques is also gaining attention for enhancing future healthcare applications and communication technologies. Purpose: The primary objective is to improve cardiac care by accurately predicting symptoms and mitigating cyber-risks that threaten digital health integrity. By leveraging Integrated Quantum Networks (IQNs) and AI-driven protocols, this research aims to reduce the prevalence/incidence of non-communicable diseases by 50% by 2035 through proactive prevention and superior treatment management. Method: The framework utilizes AI-based techniques and AI-quantum-enhanced sensors and IQN to build a secure, proactive monitoring system. This theoretical framework integrates high-precision data collection with robust risk management systems to protect against vulnerabilities in digital health infrastructure. These components work in tandem to ensure that sensitive medical data remain resilient against emerging cyber threats. Anticipated Results and Conclusions: The system is expected to improve cybersecurity resilience, system performance, and energy efficiency (EE), supporting the development of secure and advanced future healthcare applications. Full article

The mammalian heart rapidly loses regenerative capacity after birth and responds to myocardial infarction (MI) with scar formation and development of interstitial fibrosis. Cardiac fibroblasts orchestrate extracellular matrix (ECM) remodeling and cell–cell communication during development and injury; however, how fibroblast heterogeneity and fibroblast communication networks differ between regenerative neonatal and non-regenerative adult hearts remains incompletely defined. We performed scRNA-seq analysis on metabolically active CD45⁻/CD31⁻ nonmyocyte cells from the left ventricles of normal neonatal (P3) and adult (P84) mice to probe heterogeneity in a cardiac fibroblast-enriched population. We identified five transcriptionally distinct cardiac fibroblast subclusters (CF0-CF4) demonstrating different distributions across ages, including an adult-enriched immune/complement-associated program (CF0); an ECM structural-associated program present across ages (CF1); and neonatal-enriched contractile/ECM-remodeling (CF2), Wnt-modulating matrix-regulatory (CF3), and proliferative (CF4) programs. Matrisome category scoring revealed age-dependent divergence in ECM programs: neonatal fibroblasts showed higher enrichment of core matrisome components (particularly collagens and proteoglycans), whereas adult fibroblasts were relatively enriched for matrisome-associated categories, including ECM regulators and secreted factors. Ligand–receptor inference using CellChat demonstrated a broad reduction in fibroblast–fibroblast interaction strength and information flow in adult networks, and adult-enriched signaling was dominated by immune/chemotactic pathways. Finally, projection of subcluster marker programs onto an independent bulk RNA-seq dataset of cardiac fibroblasts 3 days after MI revealed that adult injury partially recapitulates neonatal-associated programs, including activation of the contractile/ECM-remodeling program (CF2) and robust induction of a cell-cycle-associated program (CF4), but lacks an additional neonatal-specific injury program associated with the Wnt-modulating subset (CF3), which was weakly induced or absent in adults. This cardiac fibroblast-enriched single-cell study defines age-dependent fibroblast states, ECM specialization, and communication network architecture that distinguish regenerative neonatal from non-regenerative adult hearts. It also provides a framework to interpret divergent stromal responses after MI and to prioritize fibroblast programs for regenerative and anti-fibrotic strategies. Full article

Background/Objectives: The incidence of cardiac arrest among critically ill patients has been increasing, with many patients experiencing clinical exacerbation prior to the event. Early detection and rapid treatment are essential to reduce the risks associated with cardiac arrest; however, difficulties such as limited ICU resources and inadequate monitoring of vital signs reduce the effectiveness of treatment. Various cardiac arrest prediction systems have been developed to overcome these issues. This study performed a summative evaluation of a Central Monitoring System with AI-based Cardiac Arrest Prediction. Methods: A summative usability evaluation was conducted in a simulated ICU environment with 22 ICU nurses experienced in using patient monitoring devices. Participants completed tasks based on the device workflow and then filled out the System Usability Scale (SUS) and satisfaction surveys, with task performance and survey responses analyzed to assess usability. Results: The usability test achieved a task success rate of 90%, with critical tasks achieving success rates ranging from 73% to 100%. The SUS score was 67.3 (“OK”), and the satisfaction survey showed an average score of 4.5, indicating generally positive user perception. Conclusions: Participants generally rated the system as acceptable, although some tasks showed lower success rates due to design issues such as poor button visibility. Further studies in clinical settings are needed to evaluate the system’s effectiveness, user experience, and contribution to the timely detection of cardiac arrest. Full article

Background: Myocardial infarction (MI) is the leading cause of morbidity and mortality globally. A major pathological progression of MI is the excess generation of reactive oxygen species (ROS), which results in oxidative stress and damage to the ischemic heart. Because damage to the myocardium is irreversible, the development of new therapeutic agents that can decrease the degree of ischemic damage following MI is crucial. The traditional Chinese medicine formulation, Qishen Yiqi dropping pills (QSYQ), has been clinically used in the treatment of various cardiovascular diseases; however, the precise mechanisms underlying its therapeutic effects remain unelucidated. Methods: In this study, we established murine models of MI via coronary artery ligation to investigate the protective effects and mechanisms of QSYQ following MI. Results: The administration of QSYQ significantly improved cardiac function, reduced infarct size, and attenuated ventricular remodeling in mice that underwent MI. Moreover, MI-induced oxidative stress and downregulated levels of antioxidant enzymes were prevented in mice administered QSYQ via upregulating the SIRT3/FOXO3a signaling pathway. Importantly, pretreatment with a selective SIRT3 inhibitor 3-TYP abolished the cardioprotective effects of QSYQ. Conclusions: Our findings elucidate the role and mechanism of QSYQ in protecting against oxidative damage and restoring redox homeostasis following myocardial infarction. This study provides support for the therapeutic potential of QSYQ in the clinical treatment of myocardial ischemic diseases. Full article

Remote tower (rTWR) operations are reshaping air traffic control but introduce significant human-factor risks, notably cognitive fatigue induced by prolonged screen-based visual surveillance. To mitigate these risks in a safety-critical domain where missed detections can be catastrophic, we propose a non-intrusive, multimodal fatigue detection framework fusing ocular and cardiac signals. A high-fidelity simulation study with 36 controllers was conducted to collect eye-tracking and electrocardiogram (ECG) data, from which a 12-dimensional feature vector—integrating gaze entropy and heart rate variability (HRV)—was extracted. Addressing the severe class imbalance and scarcity of fatigue samples in physiological data, we developed a cost-sensitive XGBoost classifier combining SMOTE oversampling with a dynamically weighted loss function. Experimental results show that the proposed framework performed well under mixed-subject evaluation and improved sensitivity to fatigue events. Although a marked performance drop was observed under LOSO evaluation, personalized calibration partially alleviated this limitation, indicating the potential of the framework for real-time fatigue monitoring in remote tower operations. Full article

Next-generation sequencing (NGS) and antisense oligonucleotide (ASO) technologies are converging to transform the diagnosis and treatment of rare monogenic disorders. NGS enables comprehensive, single-test molecular diagnoses through targeted panels, whole-exome sequencing, and whole-genome sequencing, which together reveal pathogenic variants across coding, intronic, and structural domains. Integration with transcriptomic analyses, including RNA sequencing, further refines genotype–phenotype correlations and identifies splicing aberrations amenable to correction by ASOs. Therapeutic advances now span RNase H1-dependent gapmers for transcript knockdown, splice-modulating phosphorodiamidate morpholino oligomers (PMOs), and peptide/antibody-conjugated PMOs that enhance muscle and cardiac delivery. These platforms underpin the rise in N-of-1 ASO therapies—customized drugs developed for individual patients with unique pathogenic variants. Landmark cases such as Milasen and Atipeksen illustrate the clinical feasibility and ethical complexities of personalized RNA therapeutics, while updated FDA guidance supports expedited, patient-specific investigational pathways. Despite progress, challenges persist in delivery efficiency, long-term efficacy, and equitable access. Emerging approaches—including long-read sequencing, AI-driven oligo design, and improved delivery—promise to extend ASO precision and reach. This review synthesizes current advances linking genomic diagnosis to individualized RNA-targeted interventions, outlining how integrated NGS-ASO pipelines are reshaping the therapeutic landscape for rare genetic diseases. Full article

Cardiac Ca²⁺ handling is critical for excitation–contraction coupling (ECC), with the ryanodine receptor type 2 (RyR2) serving as the key sarcoplasmic reticulum (SR) Ca²⁺ release channel in cardiomyocytes. The dysfunction of RyR2 is linked to fatal cardiac arrhythmias, including heart failure (HF) and catecholaminergic polymorphic ventricular tachycardia (CPVT). This review aims to elucidate the structural basis of RyR2, its core role in cardiac ECC and Ca²⁺ homeostasis, and the regulatory mechanisms of key modulators on its activity. By integrating recent high-resolution cryo-EM structural analyses with molecular and cellular studies on RyR2 regulation, as well as clinical evidence of RyR2 mutations in arrhythmogenic heart diseases, we provide a comprehensive overview of the field. Cryo-EM has unraveled RyR2’s gating mechanisms, ligand-binding sites, and structural features. Functionally, RyR2 mediates calcium-induced calcium release (CICR) and maintains Ca²⁺ homeostasis through coordination with SERCA2a and NCX. Key modulators (CaM, FKBP12.6, and PKA/CaMKII) and disease-linked mutations regulate RyR2 activity through distinct pathways, with defective RyR2 leading to store-overload-induced Ca²⁺ release (SOICR) and arrhythmias. Furthermore, reactive oxygen species (ROS) can induce RyR2 oxidation, establishing a pathological Ca²⁺ leak-ROS cycle in heart disease. In conclusion, RyR2 is a pivotal sensor of myocardial function, with its structural and regulatory mechanisms now well-characterized by recent studies. However, the effects of numerous RyR2 mutations remain unclear, and deeper mechanistic insights will lay a key foundation for developing novel therapies against RyR2-related cardiac diseases. Full article

Background/Objectives: Patients with pre-existing heart failure (HF) represent a clinically vulnerable population with increased susceptibility to adverse outcomes during acute systemic illnesses, including coronavirus disease 2019 (COVID-19). Systemic inflammation is increasingly recognized as a central pathophysiological mechanism linking cardiovascular vulnerability with infection-related organ dysfunction. However, the prognostic role of inflammatory biomarkers in hospitalized COVID-19 patients with pre-existing HF remains incompletely defined. This study aimed to evaluate the association between inflammatory biomarkers and clinical outcomes in this high-risk population. Methods: This retrospective single-center cohort study included 395 consecutive adult patients hospitalized with confirmed COVID-19 between March 2020 and December 2024 at a tertiary referral center. Pre-existing HF was documented in 143 patients (36.2%). Inflammatory biomarkers, including C-reactive protein (CRP), interleukin-6 (IL-6), procalcitonin, and D-dimer, were measured at admission. The primary outcomes were development of sepsis and in-hospital mortality. Multivariable logistic regression models were constructed to identify independent predictors of adverse outcomes after adjustment for demographic characteristics, comorbidities, disease severity, and cardiac biomarkers. Results: Patients with pre-existing HF had significantly higher in-hospital mortality compared with those without HF (11.9% vs. 4.8%, p = 0.016) and showed a trend toward increased intensive care unit admission. HF patients exhibited higher admission IL-6 levels, indicating enhanced inflammatory activation. In univariable analysis, HF was associated with mortality (OR 2.67, 95% CI 1.22–5.83, p = 0.014). After multivariable adjustment, the association between HF and mortality was attenuated, whereas IL-6 remained an independent predictor of mortality (adjusted OR 1.38, 95% CI 1.04–1.82, p = 0.021). Elevated IL-6 and procalcitonin levels were also independently associated with sepsis development. Conclusions: Pre-existing heart failure identifies a population at increased risk of adverse outcomes in hospitalized COVID-19 patients, and this excess risk appears to be partly mediated by systemic inflammatory activation. Interleukin-6 emerged as a key biomarker linking cardiovascular vulnerability, immune dysregulation, and clinical deterioration. These findings support the potential role of inflammation-based risk stratification to improve prognostic assessment and guide personalized management in high-risk patients with underlying cardiovascular disease. Full article