Acute myocardial infarction (MI) is a leading cause of mortality worldwide. Although reperfusion restores coronary blood flow, it paradoxically induces secondary injury that limits therapeutic benefits, and effective interventions for myocardial ischemia/reperfusion injury (MI/RI) remain lacking. Here, we identify scavenger receptor class A member 3 (SR-A3) as a previously unrecognized cardioprotective factor that plays a central regulatory role in ischemic injury. SR-A3 was significantly downregulated in myocardial tissues from MI/RI patients. Global or cardiomyocyte-specific deletion of SR-A3 exacerbated MI/RI-induced cardiac damage, whereas AAV9-mediated overexpression alleviated myocardial injury and improved cardiac function. Notably, SR-A3 expression in cardiomyocytes underwent the most dramatic reduction upon I/R stress, underscoring its critical role in the injured myocardium. Mechanistically, SR-A3 interacts with ubiquitin-specific peptidase 18 (USP18) to suppress interferon-stimulated gene 15 (ISG15)-dependent ISGylation, thereby negatively regulating activation of the STING signaling pathway and its downstream innate immune inflammatory cascades. Treatment with Selonsertib, an ASK1 inhibitor that increased USP18 abundance in our MI/RI model, recapitulated the cardioprotective effects, highlighting the translational potential of targeting this signaling axis. Collectively, our findings uncover a novel SR-A3/USP18/ISG15/STING regulatory pathway governing innate immune activation in MI/RI and position SR-A3 as a promising therapeutic target for ischemic heart disease.

Infective endocarditis requires long-term antibiotic treatment, often involving a lengthy hospitalisation. These extended stays frequently lead to patients experiencing feelings of isolation from their daily lives, which can result in loneliness and concerns for their families. Despite this, there is a notable gap in recent research regarding patients' experiences during long-term hospitalisation and treatment.

This study aimed to explore the experiences of adult patients diagnosed with infective endocarditis during their long-term hospitalisation and treatment trajectory within a cardiac ward setting.

This qualitative study explored patients' lived experiences of long-term hospitalisation with infective endocarditis. Ten patients diagnosed with infective endocarditis were purposively sampled. Data were collected through semi-structured interviews and analysed using Braun and Clarke's thematic analysis framework. The COREQ guidelines were followed to ensure transparency.

Three themes and six subthemes were identified: (1) Experiencing time in connection and isolation, with subthemes (a) perceptions of time and (b) moments of connection shape the day; (2) Fragmented care and a fragile sense of self, with subthemes (a) I am still a whole person and (b) bodily experience during treatment; and (3) Navigating uncertainty and seeking trust, with subthemes (a) no one can tell me when… and (b) seeking stability and trust.

Patients with infective endocarditis experienced long-term hospitalisation as characterised by temporal uncertainty, social isolation despite regular family contact, fragmented attention to health needs beyond the infection, and disrupted continuity in relationships with healthcare professionals. Although patients did not always perceive themselves as acutely ill, continuous monitoring and prolonged intravenous antibiotic treatment restricted their everyday routines and social participation. These findings highlight the importance of relational continuity, communication, and attention to patients' psychosocial needs during long-term hospitalisation with infective endocarditis.

Echocardiography is one of the most commonly used diagnostic methods in cardiovascular diseases because it is non-invasive, widely available, and capable of providing real-time assessment of function and cardiac structure. Despite these advantages, conventional echocardiography is often limited by operator dependence, interobserver inconstancy, the time-intensive nature of manual acquisition and measurement. Recent advances in artificial intelligence (AI), particularly deep learning, have created new opportunities to automate multiple steps of the echocardiographic workflow, starting from image acquisition and view classification to chamber segmentation, functional quantification, and hemodynamic estimation. This review provides an overview of the current clinical applications of artificial intelligence (AI) throughout the echocardiographic workflow. It focuses on key areas where AI has been applied, including automated view recognition, image quality assessment, cardiac phase identification, chamber segmentation, left ventricular ejection fraction estimation, strain analysis, and prediction of hemodynamic and disease-related parameters. Major challenges limiting wider clinical implementation were also highlighted in this review, such as insufficient external validation, dependence on image quality, differences between ultrasound vendors and patient populations, limited model interpretability, and lack of clear evidence demonstrating improved patient outcomes. Several AI-based tools, particularly those for automated view classification and chamber quantification, are becoming increasingly integrated into routine clinical practice, but many more advanced applications are possible, for which research is ongoing. The successful adoption of AI in echocardiography will depend not only on continued improvements in algorithm performance, but also on rigorous clinical validation, smooth integration into existing workflows, transparent reporting of model development and evaluation, and evidence that these technologies provide meaningful benefits for patient care.

Coronary artery bypass grafting (CABG) and percutaneous coronary intervention (PCI) are established revascularization procedures for coronary artery disease. While both improve survival and relieve symptoms, their comparative impact on long-term quality of life (QoL), particularly in low- and middle-income countries like India, remains underexplored. This study aimed to assess and compare Quality of life in patients one year after CABG and PCI.

This cross-sectional comparative study included 100 patients aged 40-65 years, comprising 50 individuals who underwent coronary artery bypass grafting (CABG) and 50 who underwent percutaneous coronary intervention (PCI), evaluated one year after their respective revascularization procedures. Data were collected using a semi-structured proforma, and quality of life was assessed with the Hindi version of the World Health Organization Quality of Life - BREF (WHOQOL-BREF) scale.

Baseline sociodemographic and clinical characteristics were comparable between groups. CABG patients had significantly higher total QoL scores compared to PCI patients (66.59±6.69 vs. 63.34±9.39, p=0.050). Physical health (p=0.012) and environmental (p=0.030) domains were significantly better in the CABG group. Psychological and social domains showed no significant difference. Comorbidities including Diabetes and Hypertension negatively affected QoL in both groups, while education was positively associated with QoL in CABG patients.

The study revealed that CABG is associated with better physical, environmental, and overall QoL one year after revascularization compared to PCI. Addressing comorbidities and sociodemographic factors is essential to improve long-term QoL in these patients.

Cardiovascular diseases (CVDs) continue to be a major cause of death and morbidity throughout the world, and there is an increasing need for better diagnostic and predictive approaches. Existing methods do not fully reflect complex clinical interactions, and new computational methods possess greater capabilities. The limitations, including a lack of diversity in datasets, low generalizability, and limited interpretability, limit general use in the clinic. The review highlights the latest developments in artificial intelligence (AI) for diagnosing and predicting cardiovascular risk factors, with a focus on its clinical applications and current challenges. A literature review was conducted on machine learning (ML) and deep learning (DL) applications in imaging, electrocardiography (ECG), and predictive modeling. AI has been shown to improve diagnostic accuracy, facilitate earlier diagnosis, and enhance the ability to stratify disease risk compared with traditional methods. The seamless integration with wearable technologies ensures continuous monitoring and proactive management. While these developments help to ensure more accurate and individualized care, there are issues of validation, ethics, and integration. Moreover, integration of multi-modal data sources and real-time analytics enhances clinical decision-making and risk assessment. As technology continues to evolve, its scalability and applicability across various healthcare settings are expected to improve. In summary, AI has the potential to revolutionize cardiovascular care and enhance clinical outcomes by leveraging data-driven approaches.

Doxorubicin (DOX) is a potent antineoplastic agent, but its clinical application is limited by the life-threatening cardiotoxic effects. Poly(ADP-ribose) polymerase 1 (PARP1) transfers ADP-ribose groups from donor NAD⁺ molecules onto target substrates upon oxidative stress, which may promote apoptosis and myocardial injury. The detailed molecular pathways of PARP1 activation, however, remain unclear. Here, we found that reactive oxygen species (ROS) function as signalling molecules to promote CBP-mediated PARP1 lactylation in an ATM-dependent manner, which induces PARP1 PARylation and ultimate cell apoptosis. We identified CBP and SIRT1 as specific lactyltransferase and delactylase of PARP1, respectively. Besides, the lactylation of PARP1 depends on the LDHA activity and lactate production. Moreover, Myocardium-specific CBP knockout mice decrease PARP1 lactylation and prevent doxorubicin-induced cardiac dysfunction. Our findings unravelled that excessive oxidative stress-induced ROS accumulation activates the ATM-CBP-PARP1 signalling pathway via a lactylation-PARylation cascade to promote apoptosis and myocardial injury.

Objective: Micronutrient deficiencies among university students may adversely influence their sleep quality, mental health, and memory function. The overarching purpose of this study was to evaluate the associations between dietary micronutrient intake and memory performance, mental health, and sleep quality among medical university students. Method : This was a cross-sectional study conducted on a sample of 985 university students. The Food Frequency Questionnaire, Prospective & Retrospective Memory Questionnaire, Depression, Anxiety and Stress Scale-21, and Pittsburgh Sleep Quality Inventory were used to assess dietary intake, memory function, mental health, and sleep quality, respectively. An undirected network was constructed via the EBICglasso model, and a directed acyclic graph was developed employing a Bayesian network. Results: The average age of the students was 22.44 ± 1.95 years. Among these participants, 500 (50.76%) were female and 485 (49.24%) were male. Assessments showed that 485 (49.20%) participants had depression symptoms, 490 (49.70%) had anxiety symptoms, 620 (62.90%) had stress, and 535 (54.30%) experienced sleep disturbances based on the cut-off scores of the questionnaires. Network analyses identified zinc, magnesium, B-group vitamins, vitamin D, and vitamin C as central nodes related to mental health, memory function, and sleep quality. Conclusion: Zinc, magnesium, vitamin B2, vitamin D, and vitamin C emerged as key micronutrients associated with mental health, memory function, and sleep quality. These micronutrients represent promising targets for future clinical studies.

Transforaminal epidural injection (EI) is an effective treatment for lumbar disorders. We used a novel ultrasound (US)-guided approach to identify the lumbar transforaminal epidural space without radiation or electrical stimulation. This technique shows a characteristic "Lambda sign over Horizontal Line (LHL)" view focused on the pars interarticularis. Therefore, we aimed to determine the anatomical background of the intervertebral foramen and clinical outcomes of this technique.

In one cadaver, indigo carmine was injected into the sacral hiatus, and the L3 vertebra was removed with the L3/4 facet joint. The specimens were sectioned longitudinally along the L3 spinal nerve and examined using hematoxylin-eosin staining. For clinical analysis, 18 individuals with lower limb pain underwent our novel US-guided lumbar transforaminal EI. The Japanese Orthopedic Association Back Pain Evaluation Questionnaire (JOABPEQ) was assessed before and at one, two, and four weeks after the first intervention, and scores for three visual analog scales (VASs) and five domains were compared between baseline and 4 weeks. Additionally, patients were divided into two groups based on the number of injections (single-trial versus multiple-trial), and baseline demographic data were compared between them.

Histological sections revealed oblique ligamentous tissue on the laterodorsal edge of the pars interarticularis, with the epidural space extending laterally. Among 15 complete follow-up cases, VAS scores for low back pain, lower limb pain, and all JOABPEQ domains except mental health improved significantly. Only the diagnosis differed significantly between the single-trial and multiple-trial groups.

Our novel US-guided transforaminal EI approach ("LHL") may improve pain and quality of life. However, multiple trials are required for cases of bony stenosis.

Breastfeeding is strongly recommended for infant and maternal health, and the Baby-Friendly Hospital Initiative (BFHI) aims to improve breastfeeding-supportive care; hence, teaching nursing students to adopt BFHI concepts is critical.

To explore nursing students' experiences and perspectives of BFHI training, with attention to communication and cultural sensitivity.

A phenomenological qualitative design was used. Thirty undergraduate nursing students (13 males, 17 females) who completed BFHI-related learning participated in individual semi-structured interviews. The interviews were audio-recorded, transcribed, translated into English, and analyzed using thematic analysis with independent coding by two researchers.

Six themes were identified: (1) training was experienced as structured, clear, and educational; (2) readiness and confidence improved through supervision, feedback, and skills practice-especially simulation; (3) permission-based, professional communication was central to breastfeeding education; (4) male identity created initial culturally influenced discomfort that improved with adaptation and professionalism; (5) team-based support-particularly involving female staff-and indirect teaching tools increased acceptability; and (6) real-clinical barriers (e.g., access, patient preference, role ambiguity) led to recommendations for clearer roles, more simulation, and culturally sensitive guidance.

When combined with structured curriculum, supervised practice, and simulation, BFHI training can boost students' confidence and communication skills. To deepen learning and improve clinical application, male trainees in culturally sensitive settings require explicit advice on consent-based communication, boundaries, teamwork (including female staff assistance), and role clarification.

Introduction Depression and loneliness have been linked to cardiovascular disease (CVD), but few studies explore their combined impact. Loneliness has been identified as an independent CVD risk factor, while depression has been tied to elevated CVD risk. This study examined relationships among University of California-Los Angeles (UCLA) Loneliness Scale scores, Patient Health Questionnaire-9 (PHQ-9) depression scores, and CVD risk factors in patients at a free medical clinic in South Carolina. Methods Thirty-one English-speaking adults aged 20-79 with a recent lipid panel completed the PHQ-9 and UCLA Loneliness Scale. Scores were calculated per standard guidelines, and lifetime Atherosclerotic Cardiovascular Disease (ASCVD) risks were computed using the American College of Cardiology (ACC) ASCVD calculator. Pearson correlations, multiple regressions, and t-tests were performed to explore relationships. Subgroup sizes varied for analysis depending on the availability of UCLA Loneliness data, permissible lipid profiles, and unreliable psychosocial responses. Results Multiple regression showed PHQ-9 and UCLA Loneliness scores significantly predicted total cholesterol (TCHOL) (R²=0.27, p=0.024). This association was stronger among non-statin users (n=14; R²=0.54, p=0.014), where PHQ-9 was inversely associated with TCHOL (b=-11.9, p=0.0044) and UCLA Loneliness score was positively associated with TCHOL (b=5.69, p=0.0056), although small sample instability substantially confines this analysis. A similar pattern was observed for high-density lipoprotein (HDL) among non-statin users (R²=0.44, p=0.04). PHQ-9 and UCLA Loneliness scores were strongly correlated (R=0.70, 95% CI: (0.43, 0.85), p<0.0001, n=27). These findings should be interpreted with caution, as relationships may have been inflated by multicollinearity, especially in non-statin group analyses. Current/former smokers had significantly higher PHQ-9 (p=0.009) and UCLA Loneliness scores (p=0.04) compared to never-smokers. Correlations among PHQ-9, UCLA scores, and ASCVD lifetime risk among non-statin users were weak and nonsignificant (PHQ-9: R=0.165, p=0.574; UCLA: R=0.280, p=0.404). Conclusion While no significant associations were observed between psychosocial scores and ASCVD lifetime risk, significant associations among depression, loneliness, and lipid values, particularly among non-statin users, along with associations between psychosocial scores and smoking status, suggest a potential link between mental health and cardiovascular risk factors. Larger studies are warranted to confirm and quantify these relationships.