The human gut microbiota is a complex ecosystem that influences host metabolism, immune function, and cardiovascular health. Dysbiosis, defined as an imbalance in microbial composition or function, has been linked to the development and progression of atherosclerosis. This connection is mediated by microbial metabolites that enter the systemic circulation and interact with vascular and immune pathways. Among these, trimethylamine N-oxide (TMAO) has been most extensively studied and is consistently associated with cardiovascular events. Other metabolites, including lipopolysaccharides (LPS), short-chain fatty acids (SCFAs), and secondary bile acids, also contribute by modulating inflammation, endothelial function, and lipid metabolism. Recent research has expanded to emerging metabolites such as indoxyl sulfate, indole-3-propionic acid, and polyamines, which may provide additional mechanistic insights. These microbial products are increasingly explored as biomarkers of cardiovascular risk. TMAO has shown predictive value in large human cohorts, while microbiota composition and diversity measures remain less consistent across studies. However, interpretation of these biomarkers is limited by methodological variability, interindividual differences, and lack of standardization. Therapeutic interventions targeting the gut–heart axis are under investigation. Dietary strategies such as the Mediterranean diet and fiber-rich nutrition, probiotics and prebiotics, and fecal microbiota transplantation (FMT) show promise, while pharmacological approaches targeting TMAO or bile acid pathways are in early stages. This review summarizes current knowledge on the mechanistic, diagnostic, and therapeutic links between the gut microbiota and atherosclerosis, highlighting both established findings and emerging directions for future research.

This review aims to analyze the critical role of gut microbiota-derived metabolites in the pathogenesis of atherosclerosis, a chronic inflammatory disease driven by lipid accumulation and immune dysregulation, and a leading cause of cardiovascular mor-bidity and mortality. Gut dysbiosis, marked by reduced microbial diversity and over-growth of pro-inflammatory bacteria, compromises intestinal barrier integrity, allow-ing translocation of lipopolysaccharides (LPS) and peptidoglycans, which activate TLR/NF-κB pathways and promote systemic inflammation. Trimethylamine N-oxide (TMAO), derived from dietary choline and L-carnitine, exacerbates endothelial dys-function, foam cell formation, and thrombosis, while secondary bile acids, such as de-oxycholic and lithocholic acid, modulate inflammation via FXR/TGR5 signaling, with effects varying by concentration. In contrast, short-chain fatty acids (SCFAs), particu-larly butyrate, exert anti-atherogenic effects by enhancing gut barrier function, reduc-ing inflammation, and improving lipid and glucose metabolism through GPCR and HDAC pathways. Therapeutic strategies, including dietary interventions (fiber-rich Mediterranean diets), probiotics (Lactobacillus, Bifidobacterium), prebiotics, fecal mi-crobiota transplantation (FMT), and small-molecule inhibitors ( DMB, IMC), target these metabolites to mitigate atherosclerosis. This review highlights gut microbio-ta-derived metabolites as pivotal biomarkers and therapeutic targets, emphasizing the potential of personalized microbiome-based interventions for atherosclerosis preven-tion and management.

This review aims to analyze the role of heat shock protein 47 (HSP47) in thrombosis and evaluate its potential as a therapeutic target for deep vein thrombosis (DVT). A systematic literature review was conducted using PubMed, Scopus, and Web of Science to identify studies on HSP47, thrombosis, and collagen, selecting only relevant and methodologically rigorous articles. HSP47 regulates platelet function and collagen interaction, playing a key role in deep vein thrombosis (DVT). HSP47, known for stabilizing collagen, also improves platelet–collagen binding and thrombus formation. In addition, reduced HSP47 levels reduce platelet adhesion, resulting in reduced thrombus formation, while inhibitors that target HSP47 decrease platelet aggregation in animal models. Naturally low levels of HSP47 during prolonged immobility are also found in hibernating mammals, such as bears, and are associated with reduced formation of thrombi, indicating a possible natural mechanism of thrombo-protection. This observation could inform new therapeutic approaches. Current studies use in vitro platelet aggregation assays, flow chamber assays, and collagen binding studies to investigate the role of HSP47 in clotting. This review aims to synthesize existing evidence to better understand HSP47’s role in clot formation and explore its potential as a target for novel DVT therapies.

Cardiovascular imaging is a cornerstone of modern cardiology, yet its clinical impact is limited by operator dependence, inter-observer variability, time-consuming workflows, and unequal access to advanced expertise. Artificial intelligence (AI), particularly machine learning and deep learning, offers new opportunities to overcome these limitations. This review aims to summarize current and emerging AI applications in cardiovascular imaging and to evaluate their potential clinical value in precision diagnostics and decision support. This narrative review synthesizes clinically relevant literature on AI applications across major cardiovascular imaging modalities, including echocardiography, cardiovascular magnetic resonance, cardiac computed tomography, and nuclear cardiology. Evidence was analyzed with a focus on AI-enabled acquisition support, image segmentation, quantitative and functional assessment, workflow automation, and risk stratification, alongside key methodological and implementation considerations. Across imaging modalities, AI-driven approaches have demonstrated improved reproducibility, efficiency, and scalability of cardiovascular imaging workflows. Automated algorithms reduce operator dependence, facilitate standardized extraction of imaging biomarkers, and support advanced functional assessment and prognostic stratification. Recent developments in video-based, temporal, and multimodal models further expand AI capabilities from technical automation toward integrated disease phenotyping and personalized clinical decision support. However, translation into routine practice remains limited by heterogeneous datasets, insufficient external validation, algorithmic bias, limited interpretability, and challenges related to regulatory approval and workflow integration. Artificial intelligence has the potential to reshape cardiovascular imaging into a more efficient, reproducible, and patient-centered precision medicine tool. Real-world clinical impact will depend on outcome-driven evaluation, robust external validation, multimodal data integration, and human-in-the-loop implementation strategies that ensure safe, equitable, and clinically meaningful adoption.

Background: The neutrophil-to-lymphocyte ratio (NLR) has been the focus of extensive research in recent years as an inexpensive inflammatory biomarker with prognostic value in oncology, but its relationship with tumor grade across solid malignancies remains uncertain. Methods: This systematic review evaluated original clinical studies reporting the association between peripheral blood NLR and histological tumor grade in solid tumors. PubMed and Web of Science were searched using Boolean strategies, and eligible full-text studies were synthesized qualitatively because of heterogeneity in tumor type, grading system, NLR threshold, and statistical reporting. Results: The qualitative synthesis included 13 retrospective primary studies comprising 5394 patients. Eight studies reported statistically significant associations between higher NLR and higher tumor grade or poorer differentiation, most consistently in bladder cancer and in single studies of prostate cancer, soft tissue sarcoma, renal cell carcinoma, pancreatic cancer, breast cancer, and colorectal cancer with synchronous liver metastases. Four studies reported no statistically significant grade-related association, mainly in heterogeneous breast cancer and ovarian cancer cohorts, whereas a small colorectal adenocarcinoma cohort study showed a non-significant positive trend. Conclusions: The available evidence suggests a possible relationship between systemic inflammation and tumor grade in selected malignancies, but the evidence remains preliminary, tumor-specific, retrospective, and vulnerable to confounding. NLR should not be interpreted as a surrogate for histological grade.