Background: Population aging is accompanied by progressive immune remodeling, chronic low-grade inflammation, and increased susceptibility to neurodegenerative diseases. Although the microbiota–gut–brain axis is increasingly recognized as a regulator of neuroimmune homeostasis, mechanisms linking age-associated dysbiosis with immunosenescence, barrier dysfunction, and brain aging remain incompletely understood. This review integrates current evidence into the proposed Gut–Immune–Brain Resilience Axis (GIBRA), a systems-level model describing how microbial signaling shapes neuroimmune resilience during aging. Methods: A structured narrative review was conducted using PubMed and the Web of Science Core Collection from database inception up to July 2026. Evidence from systematic reviews, meta-analyses, consensus statements, mechanistic and translational studies, longitudinal cohorts, randomized clinical trials, and observational studies was synthesized. Results: Current evidence supports an important role for the disruption of microbial functional signaling in neuroimmune aging, while microbial taxonomy and functional profiles provide complementary levels of biological information. Reduced short-chain fatty acid production, dysregulated tryptophan metabolism, microbial translocation, endotoxin-mediated innate immune activation, and gut-conditioned adaptive immune responses promote immunosenescence, inflammaging, barrier dysfunction, and microglial priming. The proposed Double-Barrier Hypothesis links intestinal and blood–brain barrier dysfunction as complementary mechanisms underlying chronic neuroinflammation. GIBRA highlights functional microbiome endotypes, biomarkers, multi-omics, and artificial intelligence as emerging tools for precision medicine. Conclusions: GIBRA provides an integrated systems biology perspective connecting microbial signaling, immune resilience, barrier integrity, and brain resilience during aging. Prioritizing functional resilience over microbial taxonomy may improve biomarker discovery, patient stratification, and microbiome-targeted interventions for neurodegenerative disease prevention. Prospective longitudinal studies integrating multi-omics are needed to support clinical translation.

Introduction. Traditionally, surgical aortic valve replacement has been considered the gold standard for treating symptomatic patients with severe aortic stenosis. However, the development of transcatheter technology has introduced the concept of sutureless aortic valve replacement. As a result, minimal invasive aortic valve surgery is becoming increasingly popular and effective option in experienced centers, offering enhanced patient satisfaction and fewer complications. The utilization of sutureless valves has the potential to simplify and optimize aortic valve surgery by reducing the duration of the operation and facilitating prosthesis implantation. Nonetheless, there remain uncertainties regarding the optimal therapeutic choice, durability, and long-term outcomes. Case Reports. The case series involving 10 patients who underwent Perceval valve implantation demonstrated that the procedure was well-tolerated and yielded favorable outcomes. The surgery resulted in reduced implantation time and a decrease in complications. The patients experienced a postoperative course free from complications or cardiac rhythm disturbances, and they were discharged from the hospital on the fifth day of hospitalization. Conclusion. In essence, sutureless valves such as Perceval offer a promising solution for patients with aortic stenosis, particularly in the context of minimal invasive surgery. They can provide excellent hemodynamic performance, shorter the duration of the operation, and reduce hospital stay morbidity and mortality. However, long-term results and further research are necessary to definitively confirm their benefits.

Background/Objectives: Postbiotics are increasingly recognized as biologically active products of microorganisms with emerging potential as microbiome-inspired therapeutic interventions. While most microbiome-based strategies focus on modifying microbial composition, restoration of microbial signaling has received comparatively less attention. This review examines postbiotics through the lens of microbial signaling restoration and proposes a unified Metabolite–Immune–Redox (MIR) axis linking microbial-derived signals with immune regulation, redox homeostasis, endothelial integrity, and host resilience. Methods: This narrative review synthesizes current evidence on postbiotics, microbial metabolites, structural microbial components, and extracellular vesicles, with emphasis on their roles in immunometabolic regulation, redox biology, endothelial function, and host-directed interventions. Results: Current evidence suggests that short-chain fatty acids, indole derivatives, bile acid metabolites, and microbial extracellular vesicles are important mediators of host–microbe communication. These signals influence interconnected pathways involving mitochondrial function, inflammasome activity, immune calibration, endothelial and glycocalyx homeostasis, and disease tolerance. The review highlights the endothelium as an underrecognized therapeutic target and discusses biomarkers, including soluble thrombomodulin, von Willebrand factor, and D-dimer, as potential tools for identifying patients most likely to benefit from host-directed interventions. Major translational challenges include product heterogeneity, incomplete mechanistic characterization, uncertain exposure–response relationships, and unresolved regulatory considerations. Conclusions: The proposed MIR axis provides a hypothesis-generating framework for understanding how restoration of microbial signaling may contribute to precision host-directed therapeutic strategies. Further mechanistic and clinical studies are needed to validate this concept and define its translational potential in inflammatory, infectious, and critical illness settings.

Artificial intelligence (AI) is entering cardiac surgery through predictive modelling, multimodal imaging, perioperative monitoring, workflow automation, and emerging computer-vision applications. The most mature evidence concerns risk prediction before and after surgery. Even in this domain, however, systematic reviews show that improvements over conventional statistical models are often modest and that routine clinical implementation remains limited. In surgical education, simulation, automated video analysis, and objective performance metrics may expand opportunities for deliberate practice and provide feedback that is less dependent on individual observers. Most of this evidence comes from general, laparoscopic, urological, and robotic surgery rather than cardiac-specific training, and its transferability should not be assumed. The same technologies also create risks. Automation bias, cognitive off-loading, reduced exposure to failure management, and displacement of mentor–trainee interaction may weaken the independent judgement on which safe cardiac surgery depends. Opaque models, dataset shift, inequitable performance, and uncertain accountability add further clinical and ethical concerns. This narrative review examines the current and emerging roles of AI across the cardiac surgical pathway and in cardiothoracic training, while distinguishing demonstrated applications from plausible but unproven uses. We propose a human-in-command framework based on external validation, local performance testing, transparent intended use, preserved manual and crisis-management competencies, simulation of technology failure, faculty oversight, competency-based credentialing, and continuous audit. AI should be judged not by technical novelty alone but by whether it improves care while preserving the ability of surgeons and teams to operate safely when the technology is unavailable or wrong.