Colorectal cancer (CRC) is one of the most prevalent and lethal oncological diseases worldwide, with a concerning rise in incidence, particularly in developing countries. Recent advances in genetic sequencing have revealed that the gut microbiome plays a crucial role in CRC development. Mechanisms such as chronic inflammation, metabolic alterations, and oncogenic pathways have demonstrated that dysbiosis, a disruption of the gut microbiome, is linked to CRC. Associations have been found between tumor progression, treatment resistance, and pathogenic microbes such as Fusobacterium nucleatum and Escherichia coli. A promising approach for CRC prevention and treatment is microbiome manipulation through interventions such as probiotics, prebiotics, fecal microbiota transplantation, and selective antibiotics. This article explores how gut microbiome alterations influence CRC pathogenesis and examines microbiome modulation strategies currently used as adjuncts to traditional treatments. Advances in artificial intelligence, single-cell and spatial transcriptomics, and large-scale initiatives such as the ONCOBIOME Project are paving the way for the identification of microbiome-derived biomarkers for early CRC detection and personalized treatment. Despite promising progress, challenges such as interindividual variability, causal inference, and regulatory hurdles must be addressed. Future integration of microbiome analysis into multi-omics frameworks holds great potential to revolutionize precision oncology in CRC management.

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide, with approximately 25-30 % of cases exhibiting a familial component driven by germline mutations in DNA mismatch repair genes (Lynch syndrome) or the APC gene (familial adenomatous polyposis). Despite advances in screening and early detection, significant challenges persist in identifying at-risk individuals, optimizing surveillance strategies and addressing disparities in access to genetic testing and preventive care. This narrative review synthesizes current evidence on the genetic underpinnings, modifiable risk factors and personalized screening approaches for familial CRC. We highlight the critical interplay between hereditary predisposition and environmental exposures including diet, obesity, smoking and gut microbiome alterations, which cumulatively influence disease penetrance and clinical outcomes. Emerging predictive models integrating family history, polygenic risk scores and proteomic biomarkers offer unprecedented opportunities for risk stratification, enabling tailored screening initiation and intervals that balance clinical efficacy with cost-effectiveness. Novel non-invasive biomarkers, such as circulating tumor DNA and stool RNA tests, demonstrate promising sensitivity and specificity, potentially enhancing patient adherence while complementing gold-standard colonoscopy. Furthermore, artificial intelligence-assisted endoscopy and comprehensive genetic panels are reshaping precision oncology by improving adenoma detection rates and guiding targeted therapies. Addressing social determinants of health and implementing structured genetic counseling remain essential to achieving equitable CRC prevention. By transitioning from age-based to individualized, risk-adapted screening paradigms, healthcare systems can significantly reduce CRC incidence and mortality, particularly among genetically predisposed populations.

Brain aging involves progressive declines in neuroplasticity, metabolic flexibility, cerebrovascular integrity and immune homeostasis. Although traditionally viewed as brain-intrinsic, growing evidence indicates that peripheral metabolic organs substantially influence neural aging trajectories. Among these, adipose tissue is increasingly recognized as a dynamic endocrine and immune organ capable of modulating central nervous system (CNS) structure and function across the lifespan. Epidemiological, neuroimaging and experimental studies consistently link adipose tissue dysfunction, particularly the expansion and inflammatory remodeling of visceral fat depots, to accelerated brain aging, cognitive decline and increased susceptibility to neurodegenerative disease. These relationships extend beyond conventional cardiometabolic risk, implicating adipose-derived mechanisms with direct relevance for neural aging. Chronic low-grade inflammation, impaired insulin signaling, dyslipidemia, adipokine imbalance and senescence-associated secretory activity originating in adipose tissue act on the aging brain by promoting microglial dysfunction, cerebrovascular impairment, blood-brain barrier (BBB) disruption and synaptic vulnerability. In parallel, adipose-derived extracellular vesicles and microRNAs have been identified as direct molecular mediators of adipose-brain communication. Importantly, adipose tissue is structurally and functionally heterogeneous, and its impact on brain aging is strongly depot- and context-dependent. While dysfunctional visceral adipose tissue amplifies neuroinflammatory and neurodegenerative processes, preserved subcutaneous and thermogenic depots may support brain resilience by sustaining metabolic homeostasis and neurotrophic signaling. By integrating molecular, translational and human evidence, this review frames adipose tissue as a central and modifiable systemic determinant of brain aging. Framing brain aging within a peripheral metabolic context reconciles findings across disciplines and highlights adipose-targeted interventions as promising strategies for preserving cognitive function and reducing neurodegenerative risk.

(1) Introduction: One of the most common causes of acute pancreatitis is cholelithiasis, which is considered to be associated with female sex, older age, and recurrence. Our aim was to define a group of patients with B-AP to facilitate their diagnosis and management, while more judiciously using medical resources. (2) Materials and Methods: This retrospective, large cohort study, which was conducted by extracting data from the BUC-API registry, consisted of 1855 cases between 1 June 2015 and 1 April 2022. Each admission of the same patient was considered a separate case if it did not have signs of chronic pancreatitis. Severity and morphology were stratified according to the Revised Atlanta Classification. (3) Results: A total of 732 cases of B-AP were analyzed, with 92.5% occurring at the first attack. The median age was 65 years, with 61.9% of the patients being female. The majority (82.2%) were surgical cases, and the length of stay (LoS) was 7 days. There were 10.2% severe cases, with a mortality rate of 4%. (4) Discussion: We found positive associations between sex, age, recurrence, and morphology and biliary etiology. Compared with the general population, female sex and age over 65 years correlate better with a biliary etiology. In most scenarios, patients suffer from first attacks, with a lower probability of developing local complications. There was a tendency for biliary pancreatitis patients to be admitted to surgical wards.

Recent findings suggest that the gut microbiome significantly influences cancer outcomes, including responses to immune checkpoint inhibitor (ICI) treatments. Although early research focused on gut bacteria, it is now understood that the microbiome includes a bacteriome, virome, and mycobiome, all of which can modulate host immunity. Some commensal bacteria enhance anti-tumor immune responses and improve ICI efficacy, as demonstrated in both mice and patients. Fecal microbiota transplants (FMT) from patients responding to ICI have successfully reversed resistance in certain non-responders. In addition to bacteria, gut fungi and viruses are gaining attention as further factors influencing ICI effectiveness and toxicity. Recent multi-omics studies across cancer cohorts show that fungal and viral populations in the gut vary between ICI responders and non-responders. Commensal fungi may shape anti-cancer immunity by inducing inflammatory or tolerogenic pathways, while viral components can stimulate innate immune sensors that promote tumor surveillance. On the other hand, gut dysbiosis marked by expansion of pathobionts (including opportunistic fungi) and reduction in beneficial microbes is linked to serious immune-related adverse events (irAEs) such as ICI-induced colitis. This review discusses the multi-kingdom gut microbiome–bacteria, fungi, and viruses–and their interactions with the immune system in cancer therapy. We emphasize known mechanisms linking these microbes to anti-tumor immunity, overview human studies associating gut microbiome profiles with ICI outcomes and explore strategies to modulate the microbiome to enhance ICI efficacy while reducing toxicity. Understanding and utilizing the gut mycobiome and virome in conjunction with the bacteriome could pave the way for new biomarkers and therapeutic adjuvants in cancer immunotherapy.

The rapid expansion of next-generation sequencing technologies has generated unprecedented volumes of genomic data; however, translating these data into reliable and clinically actionable insights remains a major challenge in precision medicine. Artificial intelligence (AI) has emerged as a key enabling technology across the genomic medicine pipeline, supporting variant detection, variant interpretation, polygenic risk prediction, disease subtyping, biomarker discovery and treatment–response modelling. This review provides a clinically oriented, pipeline-based synthesis of contemporary AI applications in genomic medicine. Major computational paradigms, including machine learning, deep learning, ensemble methods, multimodal AI, explainable AI frameworks and emerging foundation models, are discussed in the context of their contribution to genomic analysis and clinical decision support. Particular emphasis is placed on the factors that determine model robustness and clinical utility, including dataset composition, class imbalance, label noise, calibration, ancestry representation, distributional shift and external validation. Evidence from rare genetic disorders, cardiovascular genetics and precision oncology is examined to illustrate both successful translational applications and persistent barriers to implementation. The review further analyses common sources of failure in real-world genomic AI systems, including overfitting, limited transportability across populations and sequencing environments, inadequate interpretability, and insufficient prospective validation. Ethical and regulatory challenges are discussed in relation to clinical accountability, genomic privacy, algorithmic bias and equitable implementation. Ultimately, the successful clinical translation of genomic AI will depend not only on methodological innovation, but also on rigorous validation, transparent reporting, continuous calibration, robust governance and sustained expert oversight.