Serratia marcescens is a Gram-negative opportunistic pathogen renowned for its extensive ecological versatility and clinical significance. Once considered a benign saprophyte, it has now been recognized as a notable etiological agent in nosocomial infections, predominantly affecting immunocompromised hosts. Its pathogenicity is mediated by an array of virulence determinants, including hemolysins, proteolytic enzymes, siderophores, and the biosynthesis of the pigmented secondary metabolite prodigiosin, which exhibits notable anticancer and immunomodulatory activities. S. marcescens exhibits proficient biofilm-forming capabilities that underpin persistent device colonization and confer resilience against antimicrobial therapies. Beyond its clinical impact, S. marcescens is of interest in industrial biotechnology and environmental bioremediation applications. This comprehensive review delineates current insights into its taxonomy, virulence pathways, antimicrobial resistance mechanisms, and emerging biotechnological utilities, emphasizing the dual challenges and opportunities it presents to microbiology and therapeutic development.

Background: The most common cause of chronic liver disease is now known to be non-alcoholic fatty liver disease (NAFLD), recently redefined as metabolic-associated fatty liver disease (MAFLD). This review aims to synthesize current evidence on the pathophysiology and clinical implications of nephrological, pulmonary, and dermatological manifestations among NAFLD/MAFLD patients. In order to find safe and efficient treatments, NAFLD/MAFLD has emerged as a primary concern for hepatologists worldwide. Methods: We conducted a comprehensive review of the literature from major databases, focusing on studies that evaluated the extrahepatic manifestations of NAFLD/MAFLD. Emphasis was placed on identifying pathophysiological mechanisms and assessing their clinical impact on renal, pulmonary, and dermatological systems. Results: Recent developments in the management of chronic viral hepatitis have lowered the mortality rate associated with chronic liver disease. However, the prevalence of NAFLD/MAFLD continues to rise, making chronic liver disease a significant health concern for the future. An increasing percentage of patients on liver transplant waiting lists now have cirrhosis and hepatocellular carcinoma due to non-alcoholic liver disease. Furthermore, the incidence and prevalence of chronic kidney disease have surged, linking NAFLD/MAFLD to higher morbidity, mortality, and healthcare costs. Conclusions: NAFLD/MAFLD is underdiagnosed and underappreciated, yet its incidence is rapidly increasing, raising concerns about a potential global epidemic. Given its multisystemic impact—extending to renal, pulmonary, and dermatological complications—it is crucial to develop interdisciplinary strategies for early detection and effective management of the disease.

Chronic wounds, diabetic foot ulcers, venous leg ulcers, and pressure injuries affect millions of patients worldwide and cost healthcare systems in the order of $150 billion annually, yet treatment options have changed less than the scale of the problem would suggest. Biofilm formation, documented in up to 78% of chronic wounds, is a central cause: bacteria embedded in extracellular polymeric matrices tolerate antimicrobial concentrations up to 1000-fold higher than planktonic cells and sustain a chronic inflammatory state that actively prevents tissue repair. Hydrogels, crosslinked polymer networks with high water content and tunable physicochemical properties, have been widely studied as platforms for addressing these challenges, though the distance between laboratory results and clinical practice remains considerable. While recent reviews have summarized hydrogel materials or antimicrobial strategies in isolation, this review takes a different approach: we treat infection, biofilm persistence, and impaired regeneration as interconnected processes that must be addressed simultaneously, and we examine biofilm management as a distinct therapeutic target rather than merely a subset of antimicrobial delivery. We analyze hydrogel-based wound care across three integrated domains: design principles (natural, synthetic, and hybrid polymer systems; crosslinking strategies; and stimuli-responsive architectures), antimicrobial delivery (silver, antibiotics, antimicrobial peptides, natural agents, and controlled-release systems), and biofilm management (nanoparticle-mediated disruption, enzymatic EPS degradation, photodynamic approaches, quorum-sensing inhibition, and anti-adhesive surface engineering). For each area, we critically evaluate what the preclinical evidence supports, where it falls short, and what would be needed to bridge the gap to clinical application. Translation remains uneven. Among the many FDA- and EMA-cleared hydrogel dressings currently in clinical use, most are simple moisture-retaining or silver-containing formulations, while the multifunctional systems that dominate the research literature are at earlier stages of development. We discuss the main translational priorities, including more predictive preclinical models, long-term nanomaterial safety, harmonized outcome reporting, manufacturing scalability, and health economic evidence, as areas where further work can meaningfully accelerate clinical adoption.

Measles remains one of the most contagious infectious diseases globally and continues to pose substantial public health risks despite decades of effective vaccination. This narrative review examines both classical and contemporary computational approaches used for measles monitoring, prediction, and control, with particular attention given to the emerging role of artificial intelligence (AI). We synthesized findings from 46 studies; 31 focused directly on measles and 15 on methodologically relevant studies from related infectious diseases (COVID-19, influenza, malaria), selected through searches of PubMed, Scopus, Web of Science, IEEE Xplore, and preprint servers, conducted between June and December 2025. Traditional compartmental models (SIR, SEIR, MSEIR), statistical tools (ARIMA, SARIMA), and seroepidemiological analysis provide transparent, well-characterized frameworks for estimating transmission dynamics and simulating intervention scenarios. Spatial modeling, network analysis, and Monte Carlo simulations have added geographic granularity to outbreak characterization. More recently, AI and machine learning (ML) methods, including supervised algorithms (Random Forest, XGBoost, SVM), deep learning architectures (CNN, LSTM), and hybrid mechanistic ML models, have shown improved predictive performance by integrating multiple data sources: epidemiological records, demographic profiles, mobility patterns, and behavioral indicators. AI-based approaches appear most valuable for high-dimensional risk prediction and image-based diagnostic tasks, while classical models retain clear advantages for policy-oriented scenario analysis. However, no AI-based or hybrid model identified in this review has been adopted into routine national measles surveillance or used for vaccination policy decisions at scale. Important challenges remain: data quality varies across settings, model generalizability cannot be assumed, and computational infrastructure disparities limit deployment in high-burden regions. Explainable AI, federated learning, workforce training for model interpretation, and integration of vaccination registries with mobility and genomic surveillance data represent concrete future directions for strengthening computational support for measles elimination.

Urinary tract infections (UTIs) are among the most common bacterial infections worldwide and are traditionally considered acute and self-limited conditions. However, growing evidence suggests that recurrent or persistent UTIs may contribute to chronic kidney disease (CKD) progression through complex interactions between uropathogens and host responses. This review examines the pathophysiological links of UTIs caused by uropathogenic Escherichia coli, Klebsiella spp., and Enterococcus spp. and the development of chronic renal injury. Pathogen-specific persistence mechanisms, including intracellular survival, biofilm formation, and chronic colonization, may promote sustained inflammation, oxidative stress, and maladaptive repair responses. These processes are associated with tubular injury and progressive fibrotic remodeling. In addition, host-related factors such as diabetes, immune dysfunction, and antimicrobial resistance may further influence disease progression. Emerging biomarkers of inflammation, tubular injury, and fibrosis may improve early detection and risk stratification in patients with recurrent or complicated UTIs. Collectively, these findings support the concept that recurrent UTIs may represent potential contributors to CKD progression in susceptible individuals and highlight the importance of early recognition, pathogen-oriented management, and improved diagnostic strategies.

Background. Hematological inflammatory indices from the complete blood count have been proposed as inexpensive prognostic markers in sepsis. The systemic immune-inflammation index (SII) and neutrophil-to-lymphocyte ratio (NLR) are the most studied, but the performance of monocyte-containing alternatives (SIRI, AISI) in the elderly, in whom immunosenescence may alter the leukocyte phenotype, remains poorly characterized. Methods. In a single-center retrospective cohort of patients aged ≥65 years admitted to a tertiary ICU with Sepsis-3-defined sepsis (n = 127, 33 deaths), we compared the discrimination of six indices (NLR, PLR, MLR, SII, SIRI, AISI) for 30-day all-cause mortality using AUROC with bootstrap confidence intervals and pairwise DeLong tests. Independent associations were assessed by logistic regression adjusted for APACHE II and age; incremental value over APACHE II was explored using IDI, cNRI, calibration and decision curve analysis, with bootstrap optimism correction. Results. Thirty-day mortality was 26.0%. The monocyte-containing indices (AISI, SIRI, MLR) discriminated better than SII and NLR, and AISI was significantly superior to SII, NLR and PLR on DeLong testing, though not to SIRI, MLR or APACHE II. After adjustment for APACHE II and age, AISI, SIRI and MLR remained independently associated with mortality, whereas SII and PLR did not. Adding AISI to APACHE II improved reclassification and calibration and yielded higher net clinical benefit across clinically relevant thresholds. Conclusions. In this exploratory, single-center analysis, monocyte-containing indices, particularly AISI, were more strongly associated with 30-day mortality in elderly ICU sepsis than SII or NLR. AISI, SIRI and MLR were strongly intercorrelated and near-equivalent, and AISI did not significantly exceed APACHE II in discrimination. These hypothesis-generating findings require prospective external validation before clinical use.