Relationship between stress and coronary artery disease: A comprehensive review.

Coronary artery disease (CAD) poses a substantial public health challenge. This review examines the intricate relationship between psychological stress and CAD, drawing from recent research spanning the last 5 to 10 years. The literature review is organized around critical themes. It includes an analysis of genetic loci in CAD susceptibility and underscores the role of green environments in reducing cardiovascular risk. A quantitative analysis presents numerical findings for clarity, while pathophysiological mechanisms are elucidated through informative figures and diagrams. The review engages with controversies and disparities in the literature, offering a balanced perspective. A tabular comparative analysis outlines the strengths and limitations of existing approaches, emphasizing conflicting findings, and environmental factors. The review concludes by distilling key takeaways for healthcare professionals and researchers. Practical implications are explored, and lessons learned from the research process are reflected upon. The conclusion also suggests avenues for further study in understanding stress's impact on CAD.

Ethical implications of AI and robotics in healthcare: A review.

Integrating Artificial Intelligence (AI) and robotics in healthcare heralds a new era of medical innovation, promising enhanced diagnostics, streamlined processes, and improved patient care. However, this technological revolution is accompanied by intricate ethical implications that demand meticulous consideration. This article navigates the complex ethical terrain surrounding AI and robotics in healthcare, delving into specific dimensions and providing strategies and best practices for ethical navigation. Privacy and data security are paramount concerns, necessitating robust encryption and anonymization techniques to safeguard patient data. Responsible data handling practices, including decentralized data sharing, are critical to preserve patient privacy. Algorithmic bias poses a significant challenge, demanding diverse datasets and ongoing monitoring to ensure fairness. Transparency and explainability in AI decision-making processes enhance trust and accountability. Clear responsibility frameworks are essential to address the accountability of manufacturers, healthcare institutions, and professionals. Ethical guidelines, regularly updated and accessible to all stakeholders, guide decision-making in this dynamic landscape. Moreover, the societal implications of AI and robotics extend to accessibility, equity, and societal trust. Strategies to bridge the digital divide and ensure equitable access must be prioritized. Global collaboration is pivotal in developing adaptable regulations and addressing legal challenges like liability and intellectual property. Ethics must remain at the forefront in the ever-evolving realm of healthcare technology. By embracing these strategies and best practices, healthcare systems and professionals can harness the potential of AI and robotics, ensuring responsible and ethical integration that benefits patients while upholding the highest ethical standards.

Comprehensive advancements in the prevention and treatment of diabetic nephropathy: A narrative review.

Diabetic nephropathy (DN) is a common and severe complication of diabetes mellitus and is the leading cause of chronic kidney disease (CKD) worldwide. Despite current treatments, many individuals with DN progress to end-stage renal disease (ESRD), requiring dialysis or kidney transplantation. The advancement in our understanding of the pathogenesis of diabetic nephropathy has led to the development of new prevention and treatment strategies. We comprehensively reviewed the literature on advances in the prevention and treatment of DN. We searched PubMed, Scopus, and Web of Science databases for articles published between 2000 and 2023, using keywords such as "diabetic nephropathy," "prevention," "treatment," and "recent advances." The recent advances in the prevention and treatment of DN include novel approaches targeting inflammation and fibrosis, such as inhibitors of the nuclear factor kappa-B (NF-kB) pathway, inhibitors of the transforming growth factor-beta (TGF-beta) pathway, and anti-inflammatory cytokines. Other promising strategies include stem cell therapy, gene therapy, and artificial intelligence-based approaches, such as predictive models based on machine learning algorithms that can identify individuals at high risk of developing DN and guide personalized treatment strategies. Combination therapies targeting multiple disease pathways may also offer the most significant potential for improving outcomes for individuals with DN. Overall, the recent advances in the prevention and treatment of DN represent promising avenues for future research and clinical development. Novel therapies targeting inflammation and fibrosis, stem cell and gene therapies, and artificial intelligence-based approaches all show great potential for improving outcomes for individuals with DN.