Background: Induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) are redefining cardiovascular regenerative medicine, yet challenges in differentiation fidelity, functional maturation, and scalable production restrain their full clinical potential. Aim: This review evaluates the pioneering integration of large language models (LLMs)—including GPT-4, BioGPT, and BioMedLM—into iPSC-CM research and translational therapeutics, with a focus on advancing precision, efficiency, and patient-specific care. Methods: Structured searches across biomedical and artificial intelligence-focused databases were conducted to map how LLMs augment literature mining, experimental design, multi-omics integration, and clinical translation, including personalized therapy prediction and drug safety assessment. Results: LLMs demonstrably surpass traditional tools in identifying gene-phenotype links, refining clustered regularly interspaced short palindromic repeats-based differentiation protocols, and merging patient-level datasets with iPSC-CM outputs. Limitations include model interpretability, reproducibility across genetically diverse populations, and ethical considerations regarding data privacy and bias. Conclusion:Despite these barriers, early translational applications demonstrate that LLMs can accelerate hypothesis generation, optimize laboratory-to-clinic pipelines, and enable high-fidelity, patient-specific cardiomyocyte modeling. Relevance for patients: The synergy of LLM intelligence and iPSC-CM biology has the potential to deliver safer, more effective, and deeply personalized regenerative cardiac therapies—moving the field closer to truly bespoke heart repair.

Background: In the premenopausal stage, the vaginal microbiota is characterized by a high abundance of Lactobacillus, a key genus for preserving a healthy vaginal environment. However, the estrogen decline associated with menopause modifies this microbial community, leading to a reduction in Lactobacillus and promoting the proliferation of anaerobic bacteria, thereby increasing the risk of dysbiosis, as observed in bacterial vaginosis. Likewise, the urinary microbiota undergoes alterations that heighten the susceptibility of postmenopausal women to urinary tract infections. Hormonal changes also cause symptoms such as vaginal dryness, irritation, and dyspareunia, resulting from urogenital atrophy, which affects not only physical health but also emotional well-being and quality of life. Aim: The aim of the study was to describe the changes of the vaginal and urinary microbiota’s associated with estrogen deficiency in menopause, as well as their relationship with relevant clinical conditions, including pelvic floor diseases, genital infections, periodontal disease, and gynecological cancers. Relevance for patients: Understanding these microbial changes is crucial for optimizing clinical management and improving the overall health of women in this stage of life, as these alterations represent an emerging field of research with important diagnostic and therapeutic implications.

Background: Hematopoietic stem cells (HSCs) reside in the bone marrow (BM) and sustain life-long hematopoiesis by balancing quiescence, self-renewal, and differentiation. A key feature distinguishing quiescent HSCs from their activated counterparts is a shift in their metabolic profile, including changes in glycolytic flux and mitochondrial oxidative metabolism. Disruption of HSC homeostasis can lead to hematologic diseases such as BM failure, clonal hematopoiesis, or oncogenic transformation into leukemia stem cells (LSCs). Similar to HSCs, LSCs retain stem-like characteristics but acquire malignant features, including drug resistance and a reprogrammed metabolism, which results in distinct metabolic profiles that contribute to their pathogenesis. Aim: This review summarizes the key metabolic characteristics distinguishing healthy quiescent and active HSCs from oncogenic LSCs. In addition, we highlight modern tools for investigating the metabolome, which enable the identification of novel metabolites, metabolic interactions, pathways, and potential targets for diagnosis or therapeutic intervention in hematologic diseases. Conclusion: Metabolic regulation is essential for maintaining HSC quiescence, self-renewal, and lineage commitment, whereas its disruption often underlies oncogenic transformation into LSCs. Advances in metabolic profiling reveal key differences between healthy HSCs and LSCs and identify LSC vulnerabilities that sustain survival and therapeutic resistance. Targeting these hijacked metabolic pathways may facilitate the development of LSC-specific treatment while preserving normal hematopoiesis. Further investigation of stem cell metabolism will be critical for translating these insights into effective treatments for hematologic malignancies. Relevance for patients: Understanding the metabolic profiles of healthy HSCs and LSCs can facilitate the development of innovative techniques, technologies, and therapeutics. These advances can be applied to the identification, treatment, and prevention of hematologic disease. By elucidating the metabolome of LSCs, therapies can be designed to selectively target their unique metabolic pathways, dependencies, and resistance mechanisms.

Background: Fibromyalgia is a complex, multifactorial chronic pain syndrome characterized by widespread musculoskeletal pain. Its symptoms significantly impact patients’ quality of life, functional capacity, autonomy, and the ability to work or engage in leisure activities. Aims: Given the numerous hypotheses regarding the etiology of fibromyalgia, the difficulties faced by healthcare professionals in its diagnosis and management, and its substantial negative impact on the quality of life of those affected, this study aims to characterize the patient sample and assess the condition’s impact across various life domains. Methods: A cross-sectional study was conducted with participants of both sexes, achieving a statistical power of 99%. Results: A higher prevalence of fibromyalgia was observed in individuals who reported being in a stable union (71.76%) and who possessed higher education (45.78%). The majority (56.47%) reported “very severe” pain. Significant differences were found in all evaluated domains: leisure, work, self-care, ability to exercise, functionality, and quality of life, indicating a significant deterioration following fibromyalgia diagnosis. Conclusion:The observed pattern of functional decline across various domains supports the allostatic load model of chronic pain and provides empirical evidence for the fear-avoidance model. Relevance for patients: Integrated treatments addressing physical and psychological aspects simultaneously may be, therefore, more effective.

Background: At present, there is no therapy for the long-term (chronic) rejection of transplanted organs. This condition leads to tissue fibrosis and occlusion of the blood vessels. Aim: The overall goal of the current research is to identify a clinically applicable therapy for chronic rejection in transplanted organs. Our previous study showed that inhibitors of the RhoA/Rock pathway, such as Rezurock and fingolimod, prevent chronic rejection in rodent transplantation models, with Rezurock being superior in reducing fibrosis. Materials and methods: In this study, we analyzed the effect of a Rezurock and fingolimod combination on the transcriptome of mouse peritoneal macrophages and protein expression in both mouse and human macrophages. Results: The Rezurock/fingolimod combination resulted in the differential expression of 4,855 genes (2,477 downregulated and 2378 upregulated). Downregulated genes were related to fibrotic pathways, extracellular matrix, blood vessel development, cell adhesion, and cytokine production. Protein expression analysis showed that Rezurock/fingolimod treatment had a significantly stronger effect on the expression of pentraxin 3, chemokine (C-C motif) ligand 2, C-C motif chemokine receptor 2, and transforming growth factor beta 1 in mouse macrophages, and was much more effective in reducing the expression of Notch1 and Rho-associated coiled-coil kinase 2 in human macrophages compared to individual treatments. Conclusion: Rezurock/fingolimod treatment not only affects fibrotic pathways but also downregulates genes related to cell cycle progression and cytokine production and disrupts macrophage recruitment signaling. These findings indicate that Rezurock, alone or in combination with other immunomodulators, may be a promising candidate for clinical therapy targeting chronic rejection.

Background: The role of uric acid in prostate cancer risk remains uncertain, with evidence suggesting both carcinogenic and protective effects. Genetic factors may be key modifiers of this association. Objective: This study aimed to determine whether the relationship between uric acid and prostate cancer risk differs by the rs9399005 genotype of connective tissue growth factor (CTGF). Methods: We examined 6,259 Japanese-American men in Hawaii, cancer-free at baseline (1965-1968, ages 45-68), who were followed for incident prostate cancer until 1999. Hyperuricemia was defined as serum uric acid ≥7.0 mg/dL. CTGF genotypes were classified as common allele homozygotes (CC) or minor allele carriers (T). Cox proportional hazards models estimated hazard ratios (HRs), adjusting for age and potential confounders. Results: During a median follow-up of 29.7 years, 285 prostate cancer cases were identified. A significant interaction between CTGF and hyperuricemia was observed. Among men with the CTGF-T genotype, hyperuricemia was not associated with risk (HR = 0.77, 95% confidence interval [CI]: 0.51-1.17). In contrast, among CTGF-CC homozygotes, hyperuricemia was linked to a higher risk (HR = 1.91, 95% CI: 1.21-2.99). Men with both the CTGF-CC genotype and hyperuricemia had a higher risk (HR = 1.72, 95% CI: 1.17-2.54) compared with all other subjects. Conclusion:The association between uric acid and prostate cancer varied by CTGF genotype. Hyperuricemia increased risk among CTGF-CC homozygotes, whereas a nonsignificant protective effect was seen among T allele carriers. Relevance to patients: Monitoring and lowering serum uric acid may help reduce prostate cancer risk in men with the CTGF-CC genotype.

Background: The escalating complexity of clinical trial protocols has considerably increased the workload for research coordinators, exacerbating staffing shortages and contributing to operational inefficiencies. These challenges are particularly pronounced at under-resourced and minority-serving research institutions, where limited capacity may hinder the implementation of trials. Early and accurate estimation of research coordinator effort is essential for effective planning, resource management, and successful clinical trial conduct. Aim:This study assesses the accuracy of an adopted Ontario Protocol Assessment Level (OPAL) score in predicting coordinator workload to improve operational planning in clinical research. Methods: A prospective observational study was conducted over a 12-month period at a Historically Black College and University medical school. Seven coordinators recorded hours for seven actively enrolling interventional trials. Estimated workloads were calculated using a published, adapted OPAL reference table, and were compared with actual hours using descriptive statistics and paired t-tests. To ensure consistent benchmarking, workday equivalencies (7.5 h for institutional standards and 8 h for industry standards) were applied. Results: There was no statistically significant difference between estimated and actual hours, with an average difference of 24.1 h (p=0.761). The mean absolute error was 167.0 h, equivalent to roughly 1 month of full-time work. Conclusion: The adapted OPAL score provides a practical tool for estimating coordinator workload and aligning staffing with protocol complexity, including in under-resourced settings. However, broader multi-site validation is required to confirm its generalizability and to support its integration into feasibility planning. Relevance for patients: Accurate workload forecasting enhances trial efficiency, supporting timely, high-quality studies, and accelerating access to new treatments.