Circadian rhythms, governed by the body's endogenous clock mechanism, regulate daily fluctuations in cardiovascular function, optimizing physiological processes like blood pressure regulation, cardiac metabolism, and myocardial repair. Rhythms also align cardiovascular reactivity with predictable environmental and behavioral cycles, enabling normal function and affecting disease susceptibility. Major adverse cardiovascular events, including myocardial infarction, ventricular arrhythmias, and stroke, exhibit a distinct morning peak, with evidence for circadian regulation in cardiovascular health. Indeed, controlled human laboratory studies demonstrate that beyond the influences of sleep and other behaviors, endogenous circadian rhythms independently regulate blood pressure, autonomic nervous system activity, blood clotting, vascular tone, and metabolic function. Additionally, the kidney plays a critical role in circadian sodium handling, fluid balance, and blood pressure control, with disruptions in renal circadian rhythms contributing to hypertension and progression to heart failure. Chronic circadian misalignment resulting from shift work, irregular sleep-wake cycles, or misaligned lifestyle habits is strongly associated with increased cardiovascular risk and disease progression. The emerging field of Circadian Medicine applies circadian principles to clinical care, leveraging interventions such as optimizing light exposure, meal timing, and physical activity to restore biological alignment. Chronotherapy, the strategic timing of medications or procedures to align with a patient's diurnal or circadian rhythms, offers further potential for enhancing treatments and reducing adverse effects. By integrating circadian biology into cardiovascular medicine, novel strategies are emerging to help prevent disease, improve patient outcomes, and enhance therapeutic precision. Understanding the interplay between circadian regulation and cardiovascular physiology provides a foundation for advancing cardiovascular prevention and treatment strategies.

Cardiovascular medicine is progressively evolving towards a more personalised approach integrating advanced imaging, haemodynamic assessment, biomarkers, rehabilitation, and digital technologies. The studies featured in this issue of Acta Cardiologica provide new insights into heart failure, structural heart disease, coronary artery disease, congenital heart disease, and cardiovascular prevention. Collectively, they highlight the growing importance of comprehensive risk stratification and individualised management strategies to improve cardiovascular outcomes.

In recent decades, clinical practice has been founded on the principles of evidence-based medicine, where therapeutic decisions arise from the integration of clinical expertise, patient preferences, and scientific evidence derived from controlled studies and meta-analyses. The advent of artificial intelligence (AI) in health care, however, is driving a significant evolution in clinical research, owing to its ability to analyze large volumes of heterogeneous data and overcome the limitations of traditional statistical approaches. The availability of large-scale datasets, increasing computational capability, and reduced storage costs have supported the transition towards a "data-intensive" research model, progressively integrated with conventional methods. Within cardiology, arrhythmology represents one of the fields in which AI finds extensive application. The analysis of complex electrophysiological signals, data from implantable devices, advanced cardiac imaging, and clinical parameters enables the development of algorithms capable of identifying patterns not detectable by human interpretation. These tools have already demonstrated practical utility in the early diagnosis of arrhythmias, risk stratification, procedural planning and guidance for catheter ablation, prediction of response to cardiac stimulation therapies, and optimization of remote device monitoring. Among the key emerging benefits, AI promises increasingly personalized care, enabling more targeted interventions while reducing overtreatment. Furthermore, the development of "digital twins" opens the possibility of simulating patient-specific therapeutic scenarios to support complex clinical decision-making. This manuscript provides an overview of current evidence, emerging applications, and remaining challenges related to the integration of AI in arrhythmology, highlighting its potential to drive a transition towards predictive, preventive, and personalized cardiovascular medicine.

Targeting PERK signaling: mechanisms and roles in myocardial protection.

The rise of biologics, including recombinant proteins, gene therapies, and cell therapies, is reshaping the landscape of modern therapeutics, offering new strategies to address previously "undruggable" targets. Cardiovascular diseases (CVDs), the leading cause of mortality worldwide, remain inadequately managed by traditional therapies, but biologics offer a paradigm shift from symptom control to disease modification. This review provides a comprehensive analysis of biologics in cardiovascular medicine, focusing on five key biological processes: cardiac regeneration, cardiac reverse remodeling, genetic cardiomyopathy correction, vascular function modulation, and lipid metabolism modulation. Advances in cardiac regeneration are highlighted by the transplantation of pluripotent stem cells, direct reprogramming, stimulation of endogenous adult cardiomyocyte proliferation, and noncell strategies, all of which aim to restore cardiac tissue integrity. In reverse cardiac remodeling, therapies targeting key signaling pathways, metabolic processes, and contractility-enhancing agents offer promising new approaches for CVD management. The development of gene therapies targeting genetic cardiomyopathies, including gene replacement, genome editing, and gene silencing, is discussed. For vascular function modulation, therapies targeting angiotensinogen, natriuretic peptide receptor 1, and the gut microbiome have been explored as innovative approaches to regulate vascular tone and hemodynamics. Finally, lipid modulation therapies, including agents targeting proprotein convertase subtilisin/kexin type 9 (PCSK9) and atherogenic lipoproteins, have redefined the management of dyslipidemia and cardiovascular risk. Collectively, these advancements underscore the transformative potential of biologics to provide targeted, personalized, and disease-modifying treatments for CVD. By addressing both the pathophysiological roots and clinical manifestations of CVDs, biologics represent a promising frontier in cardiovascular medicine.

Cardiac regeneration represents a major unmet goal in cardiovascular medicine. While adult mammalian hearts have very limited capacity to regenerate after injury, newborn mouse hearts can fully restore myocardial structure and function following ischemic damage. This remarkable regenerative ability is rapidly lost within the first postnatal week, but the molecular mechanisms remain poorly understood. Long non-coding RNAs (lncRNAs) have emerged as important regulators of tissue repair and regeneration. Therefore, we aimed to identify lncRNAs involved in neonatal cardiac regeneration and to investigate the function of a candidate lncRNA in regenerating mouse hearts. RNA-sequencing of postnatal day 1 (P1) and P7 mouse hearts revealed approximately 700 significantly differentially expressed lncRNAs. Mapping three neonatal heart RNA-sequencing datasets identified the conserved lncRNA H19 as a major nodal point. To assess its potential regenerative function, permanent left anterior descending artery (LAD) ligation surgeries were performed in P1 H19 knockout (KO) and wild type (WT) mice. Myocardial infarction (MI) induction and cardiac function were evaluated by echocardiography. Hearts were harvested for molecular biological and histopathological analyses. Unlike H19WT mice, H19KO neonates failed to recover cardiac function after MI. While H19WT hearts showed no fibrotic scarring and complete cardiac regeneration, H19KO hearts exhibited increased collagen and Mmp9 expression one-week post-MI and exhibited fibrotic healing at one and two weeks post-MI. Additionally, H19KO mice displayed increased proliferation of non-cardiomyocytes and altered immune cells when compared to H19WT mice, indicating substantially impaired cardiac regeneration. In conclusion, H19 is essential for complete cardiac regeneration after MI in neonatal mice.

Clinical trials in cardiovascular medicine aim to deliver high-quality evidence with greater efficiency, including smaller sample sizes and shorter timelines. The selection of sensitive and reliable end points is central to this goal. Right ventricular (RV) structure and function play a critical role in many cardiovascular conditions; however, RV-specific parameters remain underused and inconsistently applied in interventional clinical trials. In this article, the current and emerging role of RV-focused imaging and hemodynamic parameters as end points in clinical trials are explored and a comprehensive framework for their development, validation, and broader implementation is proposed. Across multiple disease domains, RV-focused parameters derived from echocardiography, cardiac magnetic resonance imaging, computed tomography, and right-sided heart catheterization demonstrate potential value in assessing the therapeutic effects of new medicines or devices across a wide range of conditions including heart failure, cardiomyopathies, valve diseases, pulmonary hypertension, and congenital heart conditions. However, their use is inconsistent, and feasibility challenges are common, particularly in multicenter clinical trial settings. Key limitations include variability in imaging acquisition, incomplete data capture, lack of standardized protocols, and insufficient validation linking short-term RV changes to long-term clinical outcomes. Emerging tools such as artificial intelligence may improve reproducibility and efficiency, while collaborative, multidisciplinary efforts are essential for advancing end-point development. RV-specific end points hold substantial promise for enhancing the sensitivity and mechanistic insight of clinical trials but remain inadequately integrated into current practice. Optimal end-point selection requires balancing clinical relevance, analytical validity, and operational feasibility, with consideration of disease-specific pathophysiology and trial design. Standardization of acquisition, validation of clinically meaningful changes, and centralized data analysis are important next steps. Broader adoption of robust RV metrics supported by technological innovation and cross-sector collaboration has the potential to improve trial efficiency, accelerate therapeutic development, and ultimately enhance patient outcomes.

Glucagon-like peptide-1 receptor agonists (GLP-1RAs) have moved from the margins of diabetes care to the center of cardiovascular medicine. Although initially developed as glucose-lowering agents, their most important clinical effects arise from broader actions on body weight, vascular biology, inflammation, and metabolic stress. Randomized trials have established that several GLP-1RAs reduce major adverse cardiovascular events and mortality in patients with type 2 diabetes and, more recently, in individuals with overweight or obesity and established cardiovascular disease without diabetes. However, their cardiovascular effects are not uniform across syndromes. The clearest benefit is observed in atherosclerotic disease, whereas their role in heart failure is phenotype-specific and largely confined to obesity-associated heart failure with preserved ejection fraction. Emerging data suggest that GLP-1RAs may also influence arrhythmic risk and outcomes in selected populations, although these observations remain hypothesis-generating. Together, these findings support a unifying concept: GLP-1RAs function as cardiometabolic substrate-modifying therapies, acting through effects on weight, inflammation, vascular biology, myocardial energetics, and autonomic regulation. This framework provides a coherent explanation for their heterogeneous clinical profile and supports a phenotype-directed approach to their use in contemporary cardiovascular care.

ABSTRACT Introduction Based on the principles of DRG, this study aimed to analyze the current status and existing problems in the clinical use of high-value medical consumables for certain specialized diseases in orthopedics and cardiovascular medicine, and propose application standards and targeted management strategies. Methods DRGs involving the use of high-value medical consumables in orthopedic total hip replacement and cardiovascular percutaneous coronary drug-eluting stent implantation were selected. Data from all patients within these groups were extracted, and the total hospitalization costs and high-value medical consumable costs were calculated for each patient. The cost structure of consumables was analyzed in relation to DRGs payment standards, and the related differences were evaluated. Results Within the same DRGs, the average proportion of high-value medical consumable costs in orthopedics and cardiovascular medicine were 43.12% and 62.02%, respectively. Compared to the DRG payment standards, a high percentage of cases in orthopedics and cardiovascular medicine exceeded the total cost, that rates of 81.56% and 77.41%, respectively, and were the main drivers of total hospitalization costs. Conclusion DRG can be used to evaluate the use of high-value medical consumables, which would lay the foundation for establishing reasonable standards for the proportion of consumable costs in specialized diseases.

Alcohol intake reprograms hepatic immune-metabolic circuits to exacerbate murine atherosclerosis and human cardiovascular risk.

Inflammation plays a central role in the pathogenesis and progression of cardiovascular diseases, including atherosclerosis, myocardial infarction and heart failure. Despite advances in conventional diagnostic and therapeutic strategies, limitations in sensitivity, specificity and targeted drug delivery still remain. Nanomedicine has emerged as a promising yet underexplored approach to address these challenges by enabling precise molecular imaging and site-specific therapeutic interventions. This review summarizes current and emerging nanotechnology-based approaches for the diagnosis and treatment of cardiovascular inflammation, highlighting their potential in clinical practice and remaining challenges. In addition, recent advances, including the development of biomimetic nanoplatforms, are discussed, along with future perspectives and the potential integration of artificial intelligence to further enhance precision in cardiovascular medicine.

Arterial thrombosis remains a leading cause of morbidity and mortality worldwide, while its mechanistic understanding and clinical management remain limited. In this review, we discuss how recent advances in microfluidic thrombosis models, mechanobiology, and microrobotic technologies may enable the development of clinically actionable and personalized thrombosis platforms. Recent findings demonstrate that arterial thrombus formation is strongly regulated by dynamic shear stress, platelet-rich aggregation, and von Willebrand factor (vWF)-mediated interactions. Emerging evidence further shows that shear-induced platelet aggregates, also known as SIPA clots, can form mechanically robust thrombi independently of classical coagulation pathways, highlighting thrombosis as a highly mechanosensitive process. Although microfluidic and flow-based systems have improved the physiological modeling of thrombosis, current platforms still face major limitations in capturing multidimensional shear dynamics, mechanobiological complexity, and patient-specific variability. Recent progress in vessel-on-a-chip technologies, computational modeling, artificial intelligence, and microrobotic systems suggests a pathway toward integrated and feedback-driven thrombosis management. These approaches may enable not only the measurement and prediction of thrombotic behavior but also its active modulation through targeted interventions. Collectively, this perspective supports a transition from static thrombosis assays toward dynamic and controllable mechanobiological platforms for precision cardiovascular medicine.

Simulation-based training in cardiovascular intervention and cardiac surgery: bridging skill, safety, and innovation.

Coronary artery disease (CAD) is a leading global cause of mortality, yet the predictive accuracy of conventional risk models is limited. Here, we integrate conventional risk factors, polygenic risk scores, and large-scale proteomics to develop a unified model for enhanced CAD risk prediction. Using data from UK Biobank, participants with plasma proteomics and genetic risk data were included after excluding prevalent CAD. Participants from England were split into training (n=32 330) and internal validation (n=13 857) sets, and Scotland/Wales participants formed an external validation set (n=5775). Incident CAD was ascertained from linked health records. A 202-protein proteomic risk score was derived by least absolute shrinkage and selection operator Cox regression, and CatBoost models were trained using conventional risk factors alone and with incremental addition of polygenic risk scores and protein proteomic risk scores; Shapley Additive Explanations-guided forward selection identified a compact protein panel. Across cohorts, the median age was 58 years and ∼45% were men. Protein proteomic risk score was dose-dependently associated with CAD risk. Compared with conventional risk factors alone, integrating polygenic risk scores and protein proteomic risk scores improved discrimination, with the area under the curve increasing from 0.750 (95% CI, 0.732-0.767) to 0.789 (95% CI, 0.772-0.805) in internal validation and from 0.717 (95% CI, 0.683-0.750) to 0.762 (95% CI, 0.732-0.791) in external validation. A 9-protein panel (GDF15 [growth differentiation factor 15], MMP12 [matrix metalloproteinase 12], NPPB [natriuretic peptide B], PGF [placental growth factor], REN [renin], ADGRG2 [adhesion G-protein coupled receptor], ACE2 [angiotensin-converting enzyme 2], CDCP1 [CUB domain-containing protein 1], CXCL17 [C-X-C motif chemokine ligand 17)]) captured most proteomic predictive information. Our findings demonstrate that integrating conventional risk factors, polygenic risk scores, and proteomic data improves CAD risk prediction. This study highlights the utility of proteomics in precision cardiovascular medicine and simplified risk stratification tools.

The unprecedented expansion of approved oncology therapies has prolonged survival and transformed the prognosis for many patients diagnosed with cancer. However, cancer treatments may be associated with cardiovascular toxicities that manifest through vascular, myocardial, or metabolic pathways, potentially limiting the use of cancer therapeutics and adversely affecting outcomes. Oncology clinical trials provide an important opportunity to evaluate cardiovascular safety signals by generating data on the incidence, timing, and spectrum of toxicities. However, progress has been limited by inconsistent definitions and variable approaches to event characterization. This scientific statement aligns the advances in cardiovascular medicine and cardiovascular clinical trials to provide criteria for systematic selection, rigorous characterization, and adjudication of cardiovascular endpoints in contemporary oncology trials. The proposed framework links drug-specific mechanisms to endpoint selection and standardizes the approach to definitions of adverse cardiovascular events, including heart failure, arrhythmias, myocarditis, and thrombotic events. Definitions of major adverse cardiac events, clinical events, and surrogate endpoints are discussed, along with strategies for alignment with the Common Terminology Criteria for Adverse Events and patient-reported outcomes. Practical guidance is provided for prospective surveillance, decentralized and hybrid clinical trial designs, independent endpoint adjudication, and statistical approaches to competing risks and late-emerging toxicities. By harmonizing cardiovascular endpoint assessment across oncology trials, this scientific statement aims to enhance risk stratification, facilitate regulatory acceptance, and inform clinical decision-making, ultimately improving patient safety while supporting innovation in cancer therapeutics.

The unprecedented expansion of approved oncology therapies has prolonged survival and transformed the prognosis for many patients diagnosed with cancer. However, cancer treatments may be associated with cardiovascular toxicities that manifest through vascular, myocardial, or metabolic pathways, potentially limiting the use of cancer therapeutics and adversely affecting outcomes. Oncology clinical trials provide an important opportunity to evaluate cardiovascular safety signals by generating data on the incidence, timing, and spectrum of toxicities. However, progress has been limited by inconsistent definitions and variable approaches to event characterization. This scientific statement aligns the advances in cardiovascular medicine and cardiovascular clinical trials to provide criteria for systematic selection, rigorous characterization, and adjudication of cardiovascular endpoints in contemporary oncology trials. The proposed framework links drug-specific mechanisms to endpoint selection and standardizes the approach to definitions of adverse cardiovascular events, including heart failure, arrhythmias, myocarditis, and thrombotic events. Definitions of major adverse cardiac events, clinical events, and surrogate endpoints are discussed, along with strategies for alignment with the Common Terminology Criteria for Adverse Events and patient-reported outcomes. Practical guidance is provided for prospective surveillance, decentralized and hybrid clinical trial designs, independent endpoint adjudication, and statistical approaches to competing risks and late-emerging toxicities. By harmonizing cardiovascular endpoint assessment across oncology trials, this scientific statement aims to enhance risk stratification, facilitate regulatory acceptance, and inform clinical decision making, ultimately improving patient safety while supporting innovation in cancer therapeutics.

Myocardial infarction (MI) remains a leading cause of cardiovascular-related morbidity and mortality worldwide. Its primary pathophysiological cascade involves the ischemic and hypoxic necrosis of cardiomyocytes (CMs), the degradation of the extracellular matrix (ECM), and the subsequent formation of fibrotic scar, which collectively drive the progression toward terminal heart failure. Current clinical interventions, which predominantly include pharmacotherapy, device implantation and reperfusion strategies, are largely palliative and mainly focus on restoring blood perfusion or alleviating symptoms. Consequently, they fail to fundamentally reverse the permanent loss of functional CMs and the structural devastation of the ECM post-MI. In recent years, hydrogels have emerged as highly promising platforms for myocardial tissue repair and regeneration, owing to their excellent biocompatibility, tunable mechanical properties, inherent biodegradability, and highly biomimetic three-dimensional (3D) network architectures. This review systematically summarizes recent advances in hydrogel engineering for MI repair, analyzing these systems from the dual perspectives of material composition and functional mechanisms. First, we highlight the design strategies underlying major material platforms, including stimuli-responsive systems, cell-engineered platforms and RNA/miRNA-loaded hydrogels. Second, we elucidate the mechanistic roles of hydrogels in myocardial repair, emphasizing mechanical support, microenvironmental modulation, and multifunctional integration. Finally, we critically evaluate the translational barriers facing hydrogel-based therapies and outline prospective future directions. Ultimately, this review aims to provide critical insights and a strategic roadmap for the fundamental research and clinical translation of hydrogels in cardiovascular regenerative medicine. STATEMENT OF SIGNIFICANCE: Myocardial infarction leads to irreversible cardiac injury and high cardiovascular mortality, with conventional therapies unable to restore heart function. Hydrogels represent promising repair materials with tunable mechanics, favorable biocompatibility and biomimetic microenvironments. This review systematically integrates hydrogel design and cardiac pathophysiology, classifying responsive hydrogels, evaluating cell/cell-free platforms, analyzing repair mechanisms, and outlining translational hurdles. It summarizes cutting-edge advances and provides valuable references for biomaterials and cardiovascular researchers exploring infarct repair hydrogels.

Acute myocardial infarction (AMI) is an acute heart disease that can result in high rates of disability and mortality. Biomarkers can reflect the pathophysiological progress of AMI, such as myocardial ischemia injury, ventricular remodelling and oxidative stress, and provide advantages in the prognostic evaluation of AMI. Finding novel biomarkers can help improve the risk stratification of AMI. A total of 180 patients who were diagnosed with AMI in the Department of Cardiovascular Medicine of Hunan Provincial People's Hospital from July 2020 to March 2021 were included in this study. Baseline circulating ANGPT-2 and TIE-2 levels were measured, and patients underwent a regular follow-up to record the occurrence of major adverse cardiovascular events (MACE) after discharge. During the entire follow-up period with an average of 444 (356-586) days, 55 patients developed MACE. Multivariate Cox regression analysis revealed that ANGPT-2 (HR: 2.400; 95% CI: 1.380-4.523; P = 0.002) and TIE-2 (HR: 2.004; 95% CI: 1.127-3.562; P = 0.018) were independent predictors of MACE in patients with AMI. The area under the curve (AUC) of circulating ANGPT-2 for predicting MACE was 0.756 (95% CI: 0.682-0.785; P < 0.001), and the AUC of circulating TIE-2 for predicting MACE was 0.664 (95% CI: 0.572-0.755; P < 0.001).The Kaplan-Meier survival curve revealed that patients with an ANGPT-2 level ≥ 1.896 ng/mL had a greater risk of MACE than those with an ANGPT-2 level < 1.896 ng/mL (HR = 3.189; 95% CI: 1.856-5.481; P < 0.001), and patients with a TIE-2 level ≥ 21.886 ng/mL had a greater risk of MACE than those with a TIE-2 level < 21.886 ng/mL (HR = 2.912; 95% CI: 1.681-5.042; P < 0.001). ANGPT-2 and TIE-2 are significantly correlated with the prognosis of AMI, which suggests that they might be potential biomarkers for predicting prognosis.

From DNA to drug discovery AI models for cardiovascular precision medicine.

Congenital Heart Disease in Sub-Saharan Africa: Equity Crisis and Global Test for Cardiovascular Medicine.