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To investigate the prognostic significance of tumor-associated tertiary lymphoid structures (TLS) in patients with gastrointestinal malignancies and to develop a survival prediction model based on TLS. One hundred and seventy six patients undergoing surgical resection for gastric or colorectal cancer were included. Hematoxylin-eosin staining and immunohistochemistry were used to assess the density and spatial distribution of TLS within tumor tissues. Patients were categorized into TLS-rich group (RG), TLS-poor group (PG), and TLS-negative group (NG). Clinical variables and TLS characteristics were integrated, and Cox proportional hazards regression, along with random forest algorithms, were employed to construct a prognostic prediction model. The median overall survival in the RG group (30 months) was significantly longer than in the PG group (24 months) and the NG group (18 months) (p < 0.05). Patients exhibiting TLS both intratumorally and peritumorally, secondary TLS, TLS within metastatic lesions, or TLS containing germinal center (GC) B cells derived a greater survival benefit. The random forest model demonstrated excellent predictive performance, with a C-index of 0.81 in the training set and 0.80 in the external validation set. The presence and density of TLS serve as independent prognostic biomarkers in patients with gastrointestinal malignancies. The TLS-based prediction model provides a robust tool to support individualized clinical decision-making. Clinical Trial Number: Not applicable.

Biofilms formed by mycobacteria, particularly Mycobacterium tuberculosis (Mtb), represent a major challenge in tuberculosis (TB) treatment due to their highly organized structure and their capacity to induce phenotypic drug tolerance. These three-dimensional bacterial aggregates are embedded in a self-produced extracellular matrix that restricts antibiotic penetration and shields bacilli from host immune responses. The resulting spatial and physiological heterogeneity within biofilms generates microenvironments that favor slow-growing or non-replicating cells, markedly reducing the efficacy of conventional antimicrobial therapies. Increasing experimental and clinical evidence supports the presence of biofilm-like mycobacterial communities in TB lesions, linking this growth mode to disease chronicity, treatment failure, and relapse. This review aims to provide an integrated overview of the biological and physiological states adopted by mycobacteria within biofilm microenvironments, with particular emphasis on the mechanisms underlying biofilm-associated drug tolerance. In addition, it critically discusses therapeutic strategies designed to overcome this tolerance, focusing on synergistic antibiotic combinations and peptide-antibiotic therapies that directly disrupt biofilm architecture, enhance drug penetration, or sensitize biofilm-embedded bacilli to antimicrobial killing.

The increasing prevalence of persistent and difficult-to-treat infections has intensified interest in natural compounds able to act on both planktonic bacteria and biofilm structures. Tithonia diversifolia, a species rich in bioactive metabolites such as tagitinin C, has emerged as a promising source of antimicrobial agents. This study evaluated the antibacterial and antibiofilm activities of a tagitinin C-rich leaf extract and potential mechanisms of action. The extract was obtained by supercritical CO₂ extraction, chemically characterized by HPLC, and assessed against Staphylococcus aureus, Enterococcus faecalis, and Pseudomonas aeruginosa using disk diffusion, broth microdilution, and molecular docking assays. Antibiofilm activity was investigated against a biofilm-forming S. aureus strain using coverslip disruption assays, optical microscopy, and scanning electron microscopy. The extract showed strong antimicrobial activity against S. aureus (MIC/MBC: 0.039 mg/mL), intermediate inhibition of E. faecalis (1.25 mg/mL), and moderate effects on P. aeruginosa (5 mg/mL). It also promoted significant biofilm disruption (66.2% ± 4.1%), with microscopy revealing reduced bacterial density and altered structural organization. Docking results demonstrated favorable binding affinities with MurA, MurE, and MurG, suggesting stable interactions with essential enzymes involved in peptidoglycan synthesis. Overall, the findings highlight the therapeutic potential of T. diversifolia extract against resistant microorganisms and biofilm-associated infections.

Since its initial identification in 2009, Candidozyma auris demonstrates high virulence and multidrug resistance, posing a significant challenge to health management due to its association with nosocomial infections and difficulties in laboratory identification. While Candidozyma auris infections have been reported in Turkey since 2019, data regarding the pediatric population remain exceedingly rare. We present the first two pediatric cases of Candidozyma auris infection at our tertiary care center, with microbiological characteristics and phylogenetic features of the isolates. We documented two cases of a Candidozyma auris infection (urinary tract and bloodstream) in pediatric patients between August 2022 and September 2023. Microbiological features and antifungal susceptibility profiles of the isolates were analyzed. Phylogenetic analysis of the ITS1-5.8S-ITS2 rDNA region was conducted to confirm species-level identification and evaluate the phylogenetic relationship of the isolates with global reference sequences. The isolates were closely related to Clade I reference sequences and isolates were resistant to amphotericin B but susceptible to fluconazole and echinocandins. This is the first report presenting Candidozyma auris infections in pediatric patients with phylogenetic analysis and underscores the urgent need for heightened vigilance and strict infection control measures.

MicroRNAs (miRNAs) have been shown to regulate many cellular processes and to play a role in host-pathogen interactions. However, the role of miRNA in urinary tract infection (UTI) remains unclear. The aim of this study was to analyze and compare miRNAs from supernatants of human bladder epithelial cells infected with ESBL-producing (ESBL019) and non-ESBL-producing (CFT073) uropathogenic E. coli (UPEC) strains and to identify miRNA target genes in human cells and uropathogenic bacteria. In total, 402 unique miRNAs were found. The statistical analysis showed differential expression of 30 miRNAs from bladder cells stimulated with ESBL019, while stimulation with CFT073 did not show any significantly expressed miRNAs when compared to unstimulated controls. The 30 differentially expressed miRNAs in ESBL019 stimulated cells showed 747 predicted individual human gene targets. KEGG and REACTOME pathways showed enrichments in pathways mainly connected to immune regulation and stress responses. Of the 30 differentially expressed host miRNAs, nine miRNAs were found to interact with predictive targets of the whole genome from the multi-resistant, ESBL-producing UPEC strain EC958. This study shows that ESBL019-infected bladder epithelial cells release miRNAs with predictive targets in both human and bacterial genes, although their role in UTI cross-species interactions remains to be clarified.

Clear cell sarcoma overlaps histologically and immunophenotypically with melanoma. Molecular testing for EWSR1 rearrangement aids in their distinction but may not be readily available. We aim to construct machine learning-based classifiers using supervised and deep learning. We digitized hematoxylin-and-eosin-stained slides from clear cell sarcomas and melanomas with confirmatory testing, constructed nuclear morphometric-based and deep learning-based classifiers (using CLAM/ResNet-50, CTransPath, and UNI models), and evaluated their performance using an independent external validation set. Morphometric analysis of 1,954,194 nuclei (1,308,124 from clear cell sarcomas, 646,070 from melanomas; 8700-70,726 [median 32,472] nuclei per slide) yielded two optimal classifiers using single-node decision tree models; both pertained to nuclear perimeter and included interquartile/interdecile range normalized to median. Factors associated with inaccurate predictions included < 10,000 nuclei/sample and altered morphology in clear cell sarcoma due to therapy. In the external validation set, comparable to the prediction accuracies by four pathologists (median 80%; range 60%-100%), the two nuclear morphometric-based classifiers achieved accuracies of 80%-90%, and the optimal deep learning-based classifier CLAM/CTransPath showed an accuracy of 90%. In conclusion, we have derived interpretable nuclear morphometric- and deep learning-based classifiers to distinguish clear cell sarcoma from melanoma. Quantitative morphometric analysis with machine learning holds the potential as a diagnostic adjunct.

Digital pathology provides better access to high-quality diagnostic services and requires validation before moving into routine practice. This study aimed to evaluate and share our experiences in the validation process of digital pathology. A total of 6128 histopathological slides from 846 patients were digitized using two scanners and shared with fifteen pathologists. Digital slides were assessed, and a preliminary report was prepared, and then slides were reviewed by light microscopy before the final report was signed. Data were collected regarding organ systems, diagnostic outcomes, discrepancies between digital and microscopic evaluations, causes of discordance, the need for rescanning or reexamination with a microscope, and perceived advantages and disadvantages of digital diagnostics. Minor diagnostic discordances were detected in 5.7% of cases (48/837), whereas no major discordances affecting treatment decisions were observed in 98% of cases (821/837). Rescanning was required in 3% of cases, and reevaluation by light microscope in 7%. The most frequent discordances involved the detection of microorganisms and the assessment of mitotic figures. Although certain limitations, microscopic diagnoses were not considered to be superior to the diagnoses using whole slide imaging.

The study investigates the prevalence and antimicrobial resistance of Acinetobacter baumannii in healthy ruminants and poultry from rural Guntur, Andhra Pradesh, India. The objective is to understand its distribution across body systems and assess antibiotic resistance patterns to aid in surveillance and control strategies. A total of 104 samples were collected from healthy livestock (ruminants and poultry) across digestive, respiratory, excretory, reproductive, udder and urogenital systems. Microbiological identification and MALDI-TOF MS confirmed A. baumannii isolates. Antibiotic susceptibility testing was performed using the Kirby Bauer disc diffusion method against multiple antibiotic classes, including penicillin, aminoglycosides, cephalosporins, fluoroquinolones, carbapenems, and tetracyclines. A prevalence rate of 66% (69/104) was observed. The highest prevalence was in the udder system (~43%), followed by the excretory (~17%), reproductive (~17%), urogenital (8.7%), digestive (~7%) and respiratory (5.8%) systems. Isolates were resistant to aminoglycosides, cephalosporins, and lincosamides, with intermediate to fluoroquinolones, meropenem, and vancomycin and susceptible to tetracyclines according to CLSI guidelines. The detection of multi-drug resistance A. baumannii in healthy livestock is alarming to human health highlights its zoonotic potential and the urgent need for antimicrobial surveillance. This pioneering study emphasizes the importance of monitoring animal populations to mitigate the risk of transmission to humans and the environment.

Sudden arrhythmic death syndrome (SADS) is a major cause of sudden cardiac death in young individuals, characterized by structurally normal hearts and negative toxicology. Although guidelines recommend family screening, phenotyping remains challenging. This study applied quantitative histology and deep-learning-based cell segmentation to investigate morphological features in SADS compared to controls. We conducted a retrospective autopsy study of 77 SADS cases and 41 age- and sex-matched controls (aged 1-49 years) who died from trauma or suicide. Cardiac tissue was analyzed using QuPath and deep learning-based image processing (Quan10). Random Forest classification and recursive feature elimination were used to identify discriminating features. Quantitative analysis found subtle but significant morphological differences. SADS cases had reduced residual myocardium in overall tissue (53% vs. 56%, p = 0.02) and endocardial regions (49% vs. 54%, p < 0.001). Endocardial and epicardial adipocyte density were key discriminators in the model. Genetic analysis identified pathogenic variants in six cases and three controls. AI-driven histology detected differences in hearts previously considered normal, suggesting subgroups within SADS. These findings support the use of quantitative tools in postmortem phenotyping, with potential to refine diagnosis, guide family screening, and improve understanding of arrhythmic mechanisms.

Biofilm-associated infections pose significant challenges due to the increased antibiotic resistance of microorganisms within these structures. This study involved isolating and characterizing the biosurfactant produced by Bacillus subtilis RSL-2 using molasses to develop a sustainable antibiofilm agent. The biosurfactant was identified as a surfactin-like lipopeptide (molecular weight: 1037 g/mol) based on FTIR, ¹H NMR, and HRMS analyses. It demonstrated a low critical micelle concentration (CMC) of 70 mg/L and markedly decreased surface and interfacial tensions to 24.46 and 0.46 mN/m, respectively. Functional experiments revealed significant surface activity, as evidenced by a 2.2 cm oil-displacement zone and an emulsification index of 91% in toluene. The surfactin demonstrated concentration-dependent antibacterial and antibiofilm efficacy against Staphylococcus aureus, Enterococcus hirae, Bacillus subtilis, Escherichia coli, Agrobacterium, Pseudomonas aeruginosa, Aspergillus, and Candida at their respective IC₉₀ values. The producer strains exhibited high IC₉₀ values, likely reflecting their inherent tolerance to surfactants. Surfactin's eco-friendliness, antibiofilm activity, and functional adaptability make it a promising agent for managing biofilms in both medicinal and industrial applications. This work highlights the strategic potential of molasses-derived biosurfactants as environmentally friendly and sustainable options for antibacterial and antifungal applications, particularly for addressing biofilm-associated infections.