Pasteurella spp. are non-motile, facultative anaerobic, Gram-negative coccobacilli that are commonly found in the oral cavity and the gastrointestinal tract of some animals and are known to be the cause of infections. Usually, infections by Pasteurella spp. in humans is more common in the context of an animal bite leading to a skin and soft tissue infection (SSTI). Infective endocarditis (IE) is rarely caused by Pasteurella spp.; however, it can pose diagnostic and therapeutic dilemmas due to its rarity. The aim of the present study was to systematically review all cases of IE by Pasteurella spp. in the literature. A systematic review was performed of PubMed, Scopus and the Cochrane Library (through 20 December 2021) for studies providing data on epidemiology and clinical and microbiological characteristics as well as data on treatment and outcomes of IE by Pasteurella spp. A total of 28 studies containing data for 28 patients were included. Prosthetic valve was present in 21.4% of patients. The aorta was the most commonly involved intracardiac site. Fever, sepsis, septic shock and heart failure were the most common clinical presentations. Cephalosporins, aminopenicillins and penicillin were the antimicrobials used most commonly. Overall mortality was 17.9%.

Cardiac magnetic resonance (CMR) imaging has an important emerging role in the evaluation and management of patients with cardiomyopathies, especially in patients with dilated cardiomyopathy (DCM). It allows a non-invasive characterization of myocardial tissue, thus assisting early diagnosis and precise phenotyping of the different cardiomyopathies, which is an essential step for early and individualized treatment of patients. Using imaging techniques such as late gadolinium enhancement (LGE), standard and advanced quantification as well as quantitative mapping parameters, CMR-based tissue characterization is useful in the differential diagnosis of DCM and risk stratification. The purpose of this article is to review the utility of CMR in the diagnosis and management of idiopathic DCM, as well as risk prediction and prognosis based on standard and emerging CMR contrast and non-contrast techniques. This is consistent with current evidence and guidance moving beyond traditional prognostic markers such as ejection fraction.

Gestational complications, such as preeclampsia and gestational diabetes mellitus (GDM), pose significant risks to maternal and fetal health and increase long-term cardiovascular disease risk in offspring. This review aims to synthesize current knowledge on the roles of ferroptosis and neutrophil extracellular trap formation (NETosis)—two regulated cell death pathways—in these pregnancy-related conditions. We performed a comprehensive analysis of preclinical and clinical studies that investigate the involvement of dysregulated iron metabolism, oxidative stress, inflammation, and endothelial dysfunction mediated by ferroptosis and NETosis in gestational pathologies. Evidence indicates that disturbances in maternal iron homeostasis and enhanced formation of lipid peroxides and NETs contribute to placental dysfunction and systemic inflammation, exacerbating disease severity. Therapeutic strategies targeting these pathways are emerging but require further validation. Our review also identifies key gaps in mechanistic understanding, biomarker development, and translational research needs. We conclude that modulation of ferroptosis and NETosis offers promising avenues for improving diagnosis and treatment of pregnancy complications, though carefully designed clinical studies are essential to confirm their clinical utility and safety.

Left ventricular hypertrophy (LVH) is classified as concentric or eccentric based on left ventricle relative wall thickness. Using machine learning (ML) techniques on basic clinical parameters and features from a single-lead electrocardiogram (ECG) we detected LVH in a hypertensive population without cardiovascular disease. We enrolled 812 hypertensive subjects with no indications of cardiovascular disease. Based on left ventricular mass index (LVMi) and relative wall thickness (RWT), the subjects were classified into 2 groups; i) normal geometry (NG) and concentric remodeling (CR) were classified as no-LVH, whereas ii) concentric and eccentric hypertrophy were classified as having LVH. We trained a Random Forest to distinguish between the two categories. For comparison we also trained a logistic regression and a convolutional neural network model. We performed feature importance and interaction analysis using SHAP to interpret the model's predictions for feature importance and feature interactions. Our model was able to distinguish no-LVH subjects from the ones with LVH with ROC/AUC 0.82 (95% CI: 0.71-0.91) and average precision 0.61. At threshold 0.3, specificity is 81% and sensitivity is 58%. Age, corrected QT interval, T wave duration, and being female, were the most important features that contributed to the model's predictions. Utilizing analysis of single-lead ECG combined with clinical data, we demonstrated strong performance in detecting LVH. The identification of key ECG features such as corrected QT interval and T wave morphology underscores the clinical value of single-lead ECG analysis. These findings are particularly important in the era of wearable devices, where accessible, noninvasive screening for cardiac conditions like LVH can be integrated into everyday health monitoring.

Background/Objectives: Pacing-induced cardiomyopathy (PiCM) is a recognized complication of chronic right ventricular pacing (RVP), characterized by left ventricular (LV) dysfunction, adverse remodeling, and progression to heart failure. MicroRNAs (miRs) regulate gene expression and play an important role in ventricular remodeling. This study aimed to observe whether dynamic changes in miRs according to a novel peripheral blood mononuclear cell (PBMC)-based approach could serve as early predictive biomarkers of PiCM. Methods: A prospective, single-center cohort study was conducted in adult patients undergoing pacemaker implantation. Clinical characteristics, echocardiographic parameters and expression levels of miR-208b-3p and miR-9 were assessed immediately and 3 months post-pacemaker implantation. PiCM was defined as a ≥10% reduction in LVEF at one year, with no alternative cause. Statistical analyses included correlation testing, ROC curve analysis, and multivariate regression to identify factors associated with PiCM. Results: Among 126 patients, 11.1% developed PiCM. Compared with the non-PiCM group, those who developed PiCM exhibited more pronounced 3-month changes in miR-208b-3p (median Δ₃log miR: +1.3 vs. −0.4, p = 0.013) and miR-9 (median Δ₃log miR: −1.7 vs. +0.21, p = 0.011). In multivariate analyses, Δ₃LV-GLS, Δ₃logmiR-208b-3p, and Δ₃logmiR-9 were associated with a higher likelihood of PiCM. Among PiCM patients, Δ₃logmiR-208b-3p correlated inversely with Δ₃LV-GLS (r = −0.73, p = 0.016), while Δ₃logmiR-9 correlated positively (r = 0.88, p < 0.001). ROC analyses demonstrated good predictive ability for Δ₃LV-GLS (AUC = 0.924), Δ₃log miR-208b-3p (AUC = 0.783), and Δ₃log miR-9 (AUC = 0.835), with no significant differences between curves. Conclusions: Early LV-GLS deterioration and dynamic changes in expression of miR-208b-3p and miR-9 in PBMCs precede overt LV systolic dysfunction. These miRs may serve as early predictive biomarkers for PiCM.

Heart Failure with Preserved Ejection Fraction (HFpEF) is an increasingly prevalent clinical syndrome that poses a significant public health challenge due to its complex pathophysiology, diagnostic limitations, and lack of effective therapies. Central to its development are multifactorial and interrelated mechanisms, including left ventricular diastolic dysfunction, myocardial fibrosis, inflammation, endothelial dysfunction, and cardiomyocyte hypertrophy. In recent years, noncoding RNAs (ncRNAs)—particularly microRNAs (miRNAs) and long noncoding RNAs (LncRNAs)—have emerged as critical regulators of these cellular and molecular pathways. This review outlines the major pathophysiological mechanisms underlying HFpEF and highlights the noncoding RNAs most extensively studied in this context. Several ncRNAs have shown promise as biomarkers for the diagnosis and prognosis of HFpEF, owing to their tissue specificity, stability in circulation, and involvement in disease-relevant pathways. However, their integration into routine clinical practice remains limited. Importantly, the regulatory functions of ncRNAs in HFpEF pathophysiology also position them as potential therapeutic targets. Early experimental studies demonstrate encouraging results, suggesting that ncRNA-targeted interventions may support the development of personalized treatment strategies tailored to the diverse clinical phenotypes observed in HFpEF.