Large-scale multi-omics identifies drug targets for heart failure with reduced and preserved ejection fraction
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PGRMC2 is a pressure-volume regulator critical for myocardial responses to stress in mice
Progesterone receptors are classified into nuclear and membrane-bound receptor families. Previous unbiased proteomic studies indicate a potential association between cardiac diseases and the progesterone receptor membrane-bound component-2 (PGRMC2); however, the role of PGRMC2 in the heart remains unknown. In this study, we use a heart-specific knockout (KO) mouse model (MyH6•Pgrmc2flox/flox) in which the Pgrmc2 gene was selectively deleted in cardiomyocytes. Here we show that PGRMC2 serves as a mediator of steroid hormones for rapid calcium signaling in cardiomyocytes to maintain cardiac contraction, sufficient stroke volume, and adequate cardiac output by regulating the cardiac pressure-volume relationship. The KO hearts from male and female mice exhibit an impairment in pressure-volume relationship. Under hypoxic conditions, this pressure-volume dysregulation progresses to congestive left and right ventricular failure in the KO hearts. Overall, we propose that PGRMC2 is a cardiac pressure-volume regulator to maintain normal cardiac physiology, especially during hypoxic stress.
Revealing the mechanism of cold metal transfer
Cold metal transfer (CMT) is a pioneering feeding system widely used in wire-arc additive manufacturing (WAAM) and welding. However, process optimisation remains challenging. Although CMT has been extensively applied in various industrial sectors, its underlying mechanism is poorly understood because of the complex physics of the interactions between the wire and molten material and the wire’s highly dynamic motion. To elucidate the complexity and features of CMT, we explore the dynamic behaviour and anatomy of molten materials during wire motions (withdrawal and dipping cycles) using high-speed photography at a timescale of microseconds. We reveal a crucial driving force in the melt pool and the frequent ejection of streams or particles during CMT. This study contributes to WAAM and welding by presenting the influential features of ultra-high-dynamics CMT and facilitating the progression of process optimisation.
A machine learning approach to leveraging electronic health records for enhanced omics analysis
Omics studies produce a large number of measurements, enabling the development, validation and interpretation of systems-level biological models. Large cohorts are required to power these complex models; yet, the cohort size remains limited due to clinical and budgetary constraints. We introduce clinical and omics multimodal analysis enhanced with transfer learning (COMET), a machine learning framework that incorporates large, observational electronic health record databases and transfer learning to improve the analysis of small datasets from omics studies. By pretraining on electronic health record data and adaptively blending both early and late fusion strategies, COMET overcomes the limitations of existing multimodal machine learning methods. Using two independent datasets, we showed that COMET improved the predictive modelling performance and biological discovery compared with the analysis of omics data with traditional methods. By incorporating electronic health record data into omics analyses, COMET enables more precise patient classifications, beyond the simplistic binary reduction to cases and controls. This framework can be broadly applied to the analysis of multimodal omics studies and reveals more powerful biological insights from limited cohort sizes.
A novel wearable device integrating ECG and PCG for cardiac health monitoring
The alarming prevalence and mortality rates associated with cardiovascular diseases have emphasized the urgency for innovative detection solutions. Traditional methods, often costly, bulky, and prone to subjectivity, fall short of meeting the need for daily monitoring. Digital and portable wearable monitoring devices have emerged as a promising research frontier. This study introduces a wearable system that integrates electrocardiogram (ECG) and phonocardiogram (PCG) detection. By ingeniously pairing a contact-type PZT heart sound sensing structure with ECG electrodes, the system achieves the acquisition of high-quality ECG and PCG signals. Notably, the signal-to-noise ratios (SNR) for ECG and PCG signals were measured at 44.13 dB and 30.04 dB, respectively, demonstrating the system’s remarkable stability across varying conditions. These collected signals were subsequently utilized to derive crucial feature values, including electromechanical delay (EMD), left ventricular ejection time (LVET), and pre-ejection period (PEP). Furthermore, we collected a dataset comprising 40 cases of ECG and PCG signals, enabling a comparative analysis of these three feature parameters between healthy individuals and coronary heart disease patients. This research endeavor presents a significant step forward in the realm of early, non-invasive, and intelligent monitoring of cardiovascular diseases, offering hope for earlier detection and more effective management of these life-threatening conditions.
Cardiac conduction system regeneration prevents arrhythmias after myocardial infarction
Arrhythmias are a hallmark of myocardial infarction (MI) and increase patient mortality. How insult to the cardiac conduction system causes arrhythmias following MI is poorly understood. Here, we demonstrate conduction system restoration during neonatal mouse heart regeneration versus pathological remodeling at non-regenerative stages. Tissue-cleared whole-organ imaging identified disorganized bundling of conduction fibers after MI and global His–Purkinje disruption. Single-cell RNA sequencing (scRNA-seq) revealed specific molecular changes to regenerate the conduction network versus aberrant electrical alterations during fibrotic repair. This manifested functionally as a transition from normal rhythm to pathological conduction delay beyond the regenerative window. Modeling in the infarcted human heart implicated the non-regenerative phenotype as causative for heart block, as observed in patients. These findings elucidate the mechanisms underpinning conduction system regeneration and reveal how MI-induced damage elicits clinical arrhythmogenesis.
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