Ectopic trypsin in the myocardium promotes dilated cardiomyopathy after influenza A virus infection.

We have previously reported that ectopic trypsin in the myocardium triggers acute myocarditis after influenza A virus (IAV) infection. As myocarditis is a common precursor to dilated cardiomyopathy (DCM), the aim of the present study was to investigate the influence of trypsin on the progression of DCM after IAV infection. IAV-infected mice treated with saline or trypsin inhibitor were euthanized on days 0, 9, 20, 40 and 60 postinfection. Trypsin expression colocalized with myocardial inflammatory loci and IAV-induced myocarditis peaked on day 9 postinfection and alleviated by day 20 but persisted until day 60 postinfection, even though replication of IAV was not detected from day 20 postinfection. Similar time courses were observed for the activation of pro-matrix metalloproteinase (pro-MMP)-9 and expression of the proinflammatory cytokines IL-6, IL-1ß, and TNF-α. Degradation of collagen type I, proliferation of ventricular interstitial collagen, and expression of collagen type I and III mRNA increased significantly during acute and chronic phases; collagen type III mRNA increased more significantly than collagen type I mRNA. Cardiac function progressively deteriorated with progressive left ventricular dilation. The trypsin inhibitor aprotinin suppressed pro-MMP-9 activation and cytokine release, alleviated myocardial inflammation, and restored collagen metabolism during acute and chronic phases of myocarditis. This effectively prevented ventricular dilation and improved cardiac function. These results suggest that ectopic trypsin in the myocardium promoted DCM through chronic activation of pro-MMP-9, persistent induction of cytokines, and mediation of collagen remodeling. Pharmacological inhibition of trypsin activity might be a promising approach for the prevention of viral cardiomyopathy.

GSEA analysis identifies potential drug targets and their interaction networks in coronary microcirculation disorders.

Coronary microcirculation dysfunction (CMD) is one of the main causes of cardiovascular disease. Traditional treatment methods lack specificity, making it difficult to fully consider the differences in patient conditions and achieve effective treatment and intervention. The complexity and diversity of CMD require more standardized diagnosis and treatment plans to clarify the best treatment strategy and long-term outcomes. The existing treatment measures mainly focus on symptom management, including medication treatment, lifestyle intervention, and psychological therapy. However, the efficacy of these methods is not consistent for all patients, and the long-term efficacy is not yet clear. GSEA is a bioinformatics method used to interpret gene expression data, particularly for identifying the enrichment of predefined gene sets in gene expression data. In order to achieve personalized treatment and improve the quality and effectiveness of interventions, this article combined GSEA (Gene Set Enrichment Analysis) technology to conduct in-depth research on potential drug targets and their interaction networks in coronary microcirculation dysfunctions. This article first utilized the Coremine medical database, GeneCards, and DrugBank public databases to collect gene data. Then, filtering methods were used to preprocess the data, and GSEA was used to analyze the preprocessed gene expression data to identify and calculate pathways and enrichment scores related to CMD. Finally, protein sequence features were extracted through the calculation of autocorrelation features. To verify the effectiveness of GSEA, this article conducted experimental analysis from four aspects: precision, receiver operating characteristic (ROC) curve, correlation, and potential drug targets, and compared them with Gene Regulatory Networks (GRN) and Random Forest (RF) methods. The results showed that compared to the GRN and RF methods, the average precision of GSEA improved by 0.11. The conclusion indicated that GSEA helped identify and explore potential drug targets and their interaction networks, providing new ideas for personalized quality of CMD.

Development and trends in research on hypertension and atrial fibrillation: A bibliometric analysis from 2003 to 2022.

BACKGROUND: This study aimed to comprehensively analyze research related to hypertension and atrial fibrillation, 2 common cardiovascular diseases with significant global public health implications, using bibliometric methods from 2003 to 2022. METHODS: From the Web of Science Core Collection database, literature on the theme of hypertension and atrial fibrillation was retrieved. Subsequently, comprehensive bibliometric analyses were conducted across multiple dimensions utilizing software tools such as VOSviewer, Citespace, Pajek, Scimago Graphica, and ClusterProfiler. These analyses encompassed examinations of the literature according to country/region, institution, authors, journals, citation relationships, and keywords. RESULTS: It revealed an increasing interest and shifting focus in research over the years. The analysis covered 7936 relevant publications, demonstrating a gradual rise in research activity regarding hypertension combined with atrial fibrillation over the past 2 decades, with a stable growth trend in research outcomes. Geographically, Europe and the Americas, particularly the United States, have shown the most active research in this field, while China has also gained importance in recent years. Regarding institutional contributions, internationally renowned institutions such as the University of Birmingham and the Mayo Clinic have emerged as core forces in this research direction. Additionally, Professor Lip Gregory, with his prolific research output, has stood out among numerous scholars. The American Journal of Cardiology has become a primary platform for publishing research related to hypertension and atrial fibrillation, highlighting its central role in advancing knowledge dissemination in this field. The research focus has shifted from exploring the pathophysiological mechanisms to investigating the treatment of complications and risk factors associated with hypertension and atrial fibrillation. Future research will focus on in-depth exploration of genetic and molecular mechanisms, causal relationship exploration through Mendelian randomization studies, and the application of machine learning techniques in prediction and treatment, aiming to promote the development of precision medicine for cardiovascular diseases. CONCLUSION: In conclusion, this study provides a comprehensive overview of the developmental trajectory of research on hypertension and atrial fibrillation, presenting novel insights into trends and future research directions, thus offering information support and guidance for research in this crucial field of cardiovascular medicine.

Reinforcing CoO Covalency via Ce(4f)─O(2p)─Co(3d) Gradient Orbital Coupling for High-Efficiency Oxygen Evolution.

Rare-earth (RE)-based transition metal oxides (TMO) are emerging as a frontier toward the oxygen evolution reaction (OER), yet the knowledge regarding their electrocatalytic mechanism and active sites is very limited. In this work, atomically dispersed Ce on CoO is successfully designed and synthesized by an effective plasma (P)-assisted strategy as a model (P-Ce SAs@CoO) to investigate the origin of OER performance in RE-TMO systems. The P-Ce SAs@CoO exhibits favorable performance with an overpotential of only 261 mV at 10 mA cm-2 and robust electrochemical stability, superior to individual CoO. X-ray absorption spectroscopy and in situ electrochemical Raman spectroscopy reveal that the Ce-induced electron redistribution inhibits CoO bond breakage in the CoOCe unit site. Theoretical analysis demonstrates that the gradient orbital coupling reinforces the CoO covalency of the Ce(4f)─O(2p)─Co(3d) unit active site with an optimized Co-3d-eg occupancy, which can balance the adsorption strength of intermediates and in turn reach the apex of the theoretical OER maximum, in excellent agreement with experimental observations. It is believed that the establishment of this Ce-CoO model can set a basis for the mechanistic understanding and structural design of high-performance RE-TMO catalysts.