Adenosine has emerged as a central metabolic signal linking cellular stress to systemic physiological adaptation. Under conditions such as hypoxia, ischemia, inflammation, and tissue injury, extracellular adenosine triphosphate (eATP) released from stressed cells is sequentially metabolized by the ectonucleotidases CD39 and CD73, generating adenosine that accumulates in the extracellular microenvironment. This stress-responsive nucleoside activates four G-protein-coupled receptors (A1, A2A, A2B, and A3), triggering intracellular signaling networks including the cyclic adenosine monophosphate–protein kinase A (cAMP–PKA), mitogen-activated protein kinase (MAPK), phosphoinositide 3-kinase–protein kinase B (PI3K–Akt), and hypoxia-inducible factor-1 alpha (HIF-1α) pathways. Through these integrated mechanisms, adenosine orchestrates diverse physiological processes such as vascular regulation, metabolic adaptation, immune modulation, and cellular survival. In the cardiovascular system, adenosine promotes coronary vasodilation and ischemic preconditioning, limiting reperfusion injury. In pulmonary tissues, it mediates acute anti-inflammatory responses but may also drive chronic fibrotic remodeling. Within the central nervous system, adenosine functions as a neuromodulator regulating neuronal excitability, sleep–wake homeostasis, and neuroprotection. In the tumor microenvironment, hypoxia-driven adenosine accumulation suppresses cytotoxic T cell and natural killer activity, facilitating immune evasion and tumor progression. Collectively, adenosine signaling represents a central integrative network that links metabolic stress sensing to coordinated cellular adaptation while simultaneously emerging as a clinically actionable therapeutic target across cardiovascular, inflammatory, neurological, and oncological diseases.

Background/Objectives: Recurrent urinary tract infection (rUTI) is common after menopause, but estrogen deficiency alone does not explain variation in recurrence, symptoms, and microbial profiles. This study aimed to synthesize evidence on the interactions among estrogen deficiency, urogenital microbial ecology, diabetes, obesity, microbial reservoirs, and anatomical, neurological, and functional modifiers of postmenopausal rUTI susceptibility. Methods: PubMed and Scopus were searched for original studies published from 1 January 2021 to 15 June 2026. A structured narrative synthesis included 62 original reports comprising clinical interventions, observational cohorts, microbiome and multi-omic studies, and cellular and animal experiments. Evidence was interpreted according to study design, population relevance, and biological directness. Results: Menopause was associated with reduced Lactobacillus dominance, higher vaginal pH, and altered vaginal or urinary communities, although findings were heterogeneous. Vaginal estrogen reduced recurrence and improved the local urogenital environment, but microbiome restoration is not established as its sole mechanism. Gut, rectal, vaginal, urinary, and bladder-wall reservoirs may contribute to persistence or repeated exposure. Diabetes was linked to dysbiosis and impaired urothelial defence, whereas obesity evidence remained less direct. Pelvic organ prolapse with incomplete emptying, elevated postvoid residual urine, age-related detrusor dysfunction, stroke, immobility, functional dependence, incontinence, and catheter exposure may further modify susceptibility. Conclusions: Postmenopausal rUTI is multifactorial. The urogenital microbiome–metabolic interface is a useful integrative framework, but not a validated causal or diagnostic model. Vaginal estrogen, urine culture, metabolic and bladder-function assessment, and antimicrobial stewardship remain the clinical foundation; microbiome-directed strategies require prospective validation.

Background/Objectives: The optimal dialysate calcium concentration in maintenance hemodialysis remains uncertain because reducing calcium exposure may limit calcium loading but can also stimulate parathyroid hormone secretion and impair intradialytic cardiovascular stability. We evaluated randomized evidence across bone, mineral metabolism, vascular, and acute safety outcomes. Methods: PubMed, the Cochrane Central Register of Controlled Trials (CENTRAL), and Scopus were searched from database inception through 10 July 2026, with targeted citation and publication-status updating through 1 August 2026. Randomized parallel, crossover, factorial, and multi-period trials comparing dialysate calcium concentrations in adults receiving hemodialysis or hemodiafiltration were eligible. Acute and chronic outcomes were analyzed separately. Pooled estimates used inverse-variance random-effects models with DerSimonian–Laird estimation and modified Hartung–Knapp confidence intervals. Results: Twenty-four randomized parent trials were included. Lower dialysate calcium reduced end-of-dialysis ionized calcium (paired mean difference, −0.193 mmol/L; 95% CI, −0.258 to −0.128), with substantial heterogeneity. Point estimates for chronic parathyroid hormone and total alkaline phosphatase were higher and serum calcium lower, but all confidence intervals crossed the null. No clear effects were demonstrated for phosphate, calcium–phosphate product, lumbar bone mineral density, coronary artery calcification, or carotid intima–media thickness. Acute parathyroid hormone, blood pressure, calcium-balance, and QTc estimates suggested greater parathyroid stimulation, lower hemodynamic measures, less calcium gain, and longer QTc with lower calcium, but were imprecise. Adverse events were unsuitable for pooling. Conclusions: Lower dialysate calcium consistently lowers postdialysis ionized calcium, but its long-term skeletal and vascular effects remain uncertain. No single concentration appears universally optimal; prescription should be individualized according to mineral metabolism phenotype, cardiovascular tolerance, dialysis modality, and concomitant therapy.

Background: The role of artificial intelligence (AI) in supporting clinical decision-making across the perioperative continuum remains incompletely defined. Although the presence of many AI models that perform well in terms of their predictive performance has been established, their role in the actual surgical decision-making process in the real-world in terms of specialties and perioperative phases has not been fully mapped. Objective: To map the existing literature on the application of AI in surgical decision-making across the perioperative continuum, describe its use in preoperative, intraoperative, and postoperative phases, and identify key barriers and gaps affecting clinical implementation. Methods: A scoping review was conducted in accordance with the PRISMA-ScR guidelines. PubMed, Scopus, and Google Scholar were searched for studies evaluating AI applications in surgical decision-making. Eligible studies included primary research and evidence syntheses applying machine learning, deep learning, radiomics, or computer vision to diagnosis, risk stratification, surgical planning, intraoperative guidance, or postoperative outcome prediction. Study characteristics, perioperative phase, clinical application, AI methodology, and reported implementation barriers were extracted and charted using a standardized data form. Results: Fifty- five sources of evidence were included. Sources addressing multiple or cross-phase perioperative applications constituted the largest category, while among phase-specific applications, preoperative applications were the most frequent and primarily focused on diagnosis, risk stratification, and surgical planning. Intraoperative applications were less common and were limited by data availability, workflow integration, and real-time implementation challenges. Postoperative applications mainly addressed complication prediction, survival estimation, and recovery monitoring. Conclusion: AI in surgical decision-making is expanding rapidly, with preoperative applications showing comparatively greater evidence maturity than intraoperative and postoperative applications. However, prospective validation and real-world implementation remain limited across the perioperative continuum.

Perioperative management of antirheumatic medications in adults with rheumatoid arthritis (RA) undergoing orthopedic surgery requires balancing postoperative infection and impaired wound healing against disease flare, pain, and delayed rehabilitation. This systematic review aimed to evaluate how perioperative continuation, withholding, interruption timing, restart timing, dose modification, or exposure to antirheumatic medications relates to postoperative outcomes in adults with RA undergoing arthroplasty and non-arthroplasty orthopedic procedures. PubMed, Scopus, and the Cochrane Central Register of Controlled Trials were searched from database inception to 18 April 2026 for English-language full-text clinical studies. The primary outcomes were surgical site infection/periprosthetic joint infection, delayed wound healing, and postoperative RA flare. Secondary outcomes included reoperation, revision, readmission, mortality, venous thromboembolism, dislocation, and other procedure-specific complications. Original studies were classified as direct perioperative strategy evidence, medication-exposure evidence, or supportive clinical-context evidence. Forty-three original clinical studies were included, together with six non-original contextual sources. The evidence was predominantly observational, clinically heterogeneous, and of very low certainty. Methotrexate continuation was not associated with an evident increase in early postoperative complications, whereas direct evidence for other conventional synthetic agents was limited. Longer interruption of biologic or targeted synthetic therapy did not consistently reduce infection or wound-healing complications, while several studies associated treatment interruption with postoperative flare. Chronic baseline glucocorticoid exposure was associated with adverse outcomes but was clinically distinct from short-term perioperative administration; stress-dose supplementation was not directly evaluated. Medication decisions should therefore be individualized according to drug class, disease control, glucocorticoid burden, surgical procedure, and patient risk profile.

Background: Glucagon-like peptide-1 (GLP-1)-based therapies offer significant cardiometabolic benefits. Obesity-related heart failure with preserved ejection fraction (HFpEF) arises from a complex interplay of increased lipids, chronic inflammation, and metabolic disturbances. These factors not only exacerbate the disease but also affect GLP-1 pathways, supporting the potential role of GLP-1-based therapies in targeting this condition. Objective: This review aimed to synthesize the current evidence on GLP-1-based therapy in HFpEF, focusing on mechanisms of action, clinical outcomes, and practical significance. Methodology: A narrative review using PubMed and Scopus was conducted, including studies published between January 2020 and March 2026. Evidence from randomized trials, pooled analyses, mechanistic studies, and observational data was incorporated. Results: GLP-1-based therapies, including semaglutide and tirzepatide, demonstrated significant improvements in symptoms, exercise capacity, and quality of life. These benefits are closely linked to weight loss, reduced inflammation, and improved congestion indices. Tirzepatide use has also been associated with a reduction in heart failure-related complications. The underlying mechanisms likely involve coordinated effects on metabolism, inflammation, hemodynamics, and cardiac remodeling. Current evidence suggests that its efficacy in improving morbidity rates is stronger than its efficacy in reducing mortality rates. Conclusions: GLP-1-based therapies offer a promising, phenotypically targeted approach to managing obesity-associated HFpEF. However, their long-term effects on mortality remain unclear, highlighting the need for further research. Further studies should refine patient selection and define optimal clinical integration.