Background: Recent studies have shown that gut microbiota have important roles in different human diseases. There has been an ever-increasing application of high-throughput technologies for the characterization of microbial ecosystems. This led to an explosion of various molecular profiling data, and the analysis of such data has shown that machine-learning algorithms have been useful in identifying key molecular signatures. Results: In this review, we first analyze how dysbiosis of the intestinal microbiota relates to human disease and how possible modulation of the gut microbial ecosystem may be used for disease intervention. Further, we introduce categories and the workflows of different machine-learning approaches and how they perform integrative analysis of multi-omics data. Last, we review advances of machine learning in gut microbiome applications and discuss challenges it faces. Conclusions: We conclude that machine learning is indeed well suited for analyzing gut microbiome and that these approaches are beneficial for developing gut microbe-targeted therapies, helping in achieving personalized and precision medicine.

Pulmonary complications are an important yet underappreciated aspect of inflammatory bowel disease (IBD), which includes Crohn’s disease (CD) and ulcerative colitis (UC). These conditions often manifest with extraintestinal symptoms that can significantly influence the clinical trajectory of the disease. Pulmonary involvement in IBD can range from mild symptoms, such as a persistent cough, to severe conditions, including interstitial lung disease or pulmonary embolism. This systematic review aims to assess the prevalence, clinical presentations, and implications of pulmonary involvement in IBD patients. A comprehensive literature search was conducted using PubMed database up to the 1st of May 2024. Inclusion criteria focused on studies involving adult IBD patients with documented pulmonary symptoms, evaluated through clinical, radiological, and histopathological approaches. Of the 463 studies identified, 27 met the inclusion criteria, consisting of 36,264 patients. Pulmonary manifestations were classified into airway diseases and parenchymal involvement. Airway diseases, including bronchiectasis and chronic bronchitis, were the most common, followed by parenchymal conditions such as organizing pneumonia and interstitial lung disease (ILD). Smoking was identified as a significant risk factor for pulmonary involvement. Pulmonary involvement in IBD is diverse and often underdiagnosed. Early recognition and management are crucial to improving patient outcomes.

Background: Chronic ethanol consumption is a major global health concern traditionally associated with liver disease. Ethanol disrupts gut microbial communities, compromises intestinal barrier function, and contributes to hepatic, metabolic, and neurocognitive disorders. Methods: We conducted a systematic PubMed search and meta-analysis of 11 human and 19 animal studies evaluating ethanol-induced gut microbiota alterations. Studies were assessed for microbial diversity, taxonomic shifts, barrier integrity, and systemic effects. Effect sizes were calculated where possible, and interventional outcomes were examined. Results: Across species, ethanol exposure was consistently associated with reduced microbial diversity and depletion of beneficial commensals such as Faecalibacterium, Lactobacillus, Akkermansia, and Bifidobacterium, alongside an expansion of proinflammatory taxa (Proteobacteria, Enterococcus, Veillonella). Our analysis uniquely highlights discrepancies between human and animal studies, including opposite trends in specific genera (e.g., Akkermansia and Bifidobacterium) and the impact of confounders such as antibiotic exposure in human cohorts. We also demonstrate that microbiota-targeted interventions can partially restore diversity and improve clinical or behavioral outcomes. Conclusions: This meta-analysis highlights reproducible patterns of ethanol-induced gut dysbiosis across both human and animal studies.

This systematic review examines chronic kidney disease-associated pruritus (CKD-aP) as a complex clinical manifestation in patients undergoing hemodialysis. Traditionally considered a secondary symptom of end-stage renal disease, emerging evidence now positions CKD-aP as a multidimensional disorder with substantial pathogenic influence on patient outcomes. Using the PRISMA 2020 methodology, we critically evaluated 54 peer-reviewed studies published between 2020 and 2025. Our synthesis highlights a convergence of five mechanistic frameworks underpinning CKD-aP: elevated levels of uremic toxins originating from gut microbial dysbiosis, immune activation driven by IL-31 and other pro-inflammatory cytokines, heightened peripheral and central neural sensitization, dysregulation of endogenous opioid receptor pathways favoring μ-receptor activation, and xerosis-related epidermal barrier dysfunction. These mechanisms contribute to a systemic cycle of microinflammation, pruritogenic signaling, and neural hyperexcitability. We also identified and compared validated assessment tools—including the NRS, VAS, Skindex-10, and the UP-Dial scale—that facilitate standardized quantification of disease burden. While available treatments such as gabapentinoids and phototherapy offer partial relief, targeted therapies—including κ-opioid receptor agonists—represent a major advancement, although long-term effectiveness and accessibility remain under investigation. Growing scientific consensus establishes CKD-aP as a priority therapeutic target in hemodialysis care, underscoring the need for integrated, mechanism-based management strategies to improve quality of life and clinical outcomes. This work represents a narrative systematic review, integrating evidence from mechanistic, translational, and clinical studies to critically examine the biological pathways underlying CKD-associated pruritus.

Background: Psychological distress is a common comorbidity in chronic obstructive pulmonary disease (COPD), yet its relationship with disease severity remains incompletely understood. This study aimed to assess depression, anxiety, and stress using the Depression Anxiety Stress Scales–21 (DASS-21) and to examine their distribution across COPD severity stages. Methods: This multicenter, cross-sectional observational study included 285 clinically stable COPD patients enrolled between 2023 and 2025. COPD severity was classified according to Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria. Multinomial and binary logistic regression models were constructed to identify independent predictors of COPD severity and clinically significant psychological distress, adjusting for demographic and clinical covariates. Bayesian independent sample analyses and ANOVA effect size estimates were additionally performed. Results: Smoking exposure was independently associated with advanced COPD stages (GOLD 4 vs. GOLD 1–3: aOR 1.05, p < 0.001), as was dyspnea severity (mMRC: aOR 14.66, p < 0.001). In multivariable models examining psychological outcomes, COPD severity was not independently associated with clinically significant depression (p = 0.899), anxiety (p = 0.460), or stress (p = 0.843). In contrast, symptom burden measured using the COPD Assessment Test (CAT) score was consistently associated with depression (aOR 1.133, p < 0.001), anxiety (aOR 1.179, p < 0.001), and stress (aOR 1.144, p < 0.001). ANOVA effect sizes across GOLD stages were small (η² ≤ 0.047), and Bayesian analyses provided moderate to strong evidence supporting minimal differences in DASS-21-R scores between severity groups. Conclusions: Psychological distress is prevalent across all COPD severity stages and is not independently determined by airflow limitation. Symptom burden rather than spirometric severity appears to be more closely associated with emotional outcomes.

Background: Chronic obstructive pulmonary disease (COPD) is frequently complicated by psychological distress and suboptimal treatment adherence, both of which adversely affect clinical outcomes. However, the relationship between disease severity, emotional well-being, and adherence behavior remains insufficiently characterized. Methods: This multicenter observational study included 285 patients with COPD recruited from two primary care clinics. COPD severity was classified according to GOLD criteria. Psychological well-being was assessed using the World Health Organization–Five Well-Being Index (WHO-5), and treatment adherence was evaluated using the Medication Adherence Report Scale (MARS). Multidimensional relationships between clinical variables, WHO-5, and MARS were explored using correspondence analysis with symmetrical normalization. Results: Most patients had severe or very severe COPD (GOLD 3–4, 65.6%). WHO-5 scores showed marked heterogeneity across all GOLD stages, with very low values (20–26%) contributing disproportionately to the overall data structure (total contributions up to 0.97), indicating substantial anxiety and depression-related burden. Non-adherent patients represented 28.4% of the cohort but accounted for 71.6% of the inertia in the adherence-related correspondence analysis, forming a distinct psychological and behavioral profile. Mean GOLD stage was comparable between adherent and non-adherent patients (approximately 2.8–3.0). Conclusions: Correspondence analysis demonstrated substantial heterogeneity in WHO-5 and MARS profiles across all GOLD stages. Notably, mean GOLD severity was comparable between adherent and non-adherent patients (approximately 2.8–3.0), indicating that differences in adherence behavior were not primarily driven by spirometric disease severity.