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PubMed2025

Functional and Pangenomic Exploration of Roc Two-Component Regulatory Systems Identifies Novel Players Across Pseudomonas Species.

The opportunistic pathogen Pseudomonas aeruginosa relies on a large collection of two-component regulatory systems (TCSs) to sense and adapt to changing environments. Among them, the Roc (regulation of cup) system is a one-of-a-kind network of branched TCSs, composed of two histidine kinases (HKs-RocS1 and RocS2) interacting with three response regulators (RRs-RocA1, RocR, and RocA2), which regulate virulence, antibiotic resistance, and biofilm formation. Based on extensive work on the Roc system, previous data suggested the existence of other key regulators yet to be discovered. In this work, we identified PA4080, renamed RocA3, as a fourth RR that is activated by RocS1 and RocS2 and that positively controls the expression of the cupB operon. Comparative genomic analysis of the locus identified a gene-rocR3-adjacent to rocA3 in a subpopulation of strains that encodes a protein with structural and functional similarity to the c-di-GMP phosphodiesterase RocR. Furthermore, we identified a fourth branch of the Roc system consisting of the PA2583 HK, renamed RocS4, and the Hpt protein HptA. Using a bacterial two-hybrid system, we showed that RocS4 interacts with HptA, which in turn interacts with RocA1, RocA2, and RocR3. Finally, we mapped the pangenomic RRs repertoire, establishing a comprehensive view of the plasticity of such regulators among clades of the species. Overall, our work provides a comprehensive inter-species definition of the Roc system, nearly doubling the number of proteins known to be involved in this interconnected network of TCSs controlling pathogenicity in Pseudomonas species.

Gene Expression Regulation, Bacterial↗

PubMed2026

Identification of a putative RocS homolog through phenotypic profiling of uncharacterized essential genes in Streptococcus mutans.

Genome-wide viability catalogs produced by transposon sequencing (Tn-seq) and CRISPR interference (CRISPRi) have successfully mapped the essential genome of Streptococcus mutans . In this study, we combined predictive bioinformatics, conditional CRISPRi transcriptional silencing, transmission electron microscopy, transcriptomics, and genetic suppressor screens to investigate nine poorly characterized essential genes in S. mutans . From this screen, phenotypic and genetic analyses identified SMU_393 as a functional homolog of the pneumococcal chromosome segregation factor, RocS. Depletion of SMU_393 resulted in abnormal cell widening, hypersensitivity to DNA damage, and a significant subpopulation of anucleate cells. These phenotypes were bypassed by a spontaneous surface-exposed missense mutation ( dnaA Q197E ) within the AAA+ ATPase domain of the replication initiator. Together, this study refines annotations within the S. mutans essential genome and provides genetic insights into streptococcal chromosome segregation and cell cycle control.

Journal Article↗

PubMed2026

ADAM10's combined influence on the diagnostic usefulness of IL 22, IL 10, IL-17 A, and IL-17D in autism spectrum disorders: Predicted role on gut leakiness as co-morbidity.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with increasing global prevalence but a lack of reliable diagnostic biomarkers. Emerging evidence suggests that immune dysregulation, gut-brain axis dysfunction, and increased intestinal permeability play key roles in ASD pathophysiology. This study investigated the combined diagnostic value of ADAM10 and cytokines (IL-10, IL-22, IL-17 A, and IL-17D). Multivariable logistic regression produces an improved ROC curve that improves diagnostic accuracy over individual markers by combining numerous predictors into a single risk score (linear predictor). The technique, which frequently raises individual marker AUCs, entails modelling a binary result, calculating the probability, and visualizing ROC based on the projected probabilities. In this case-control study, plasma levels of ADAM10, IL-10, IL-22, IL-17 A, and IL-17D were measured in 37 male children with ASD and 37 age-matched controls. Group comparisons, correlation analyses, and receiver operating characteristic (ROC) curve analyses, including combined ROC models, were performed. ADAM10, IL-22, and IL-17 A levels were significantly reduced in children with ASD compared to controls, whereas IL-10 and IL-17D showed no significant differences. ADAM10, IL-17 A, and IL-22 demonstrated good diagnostic performance, with AUC values of 0.886, 0.855, and 0.812, respectively. In contrast, IL-10 and IL-17D showed poor discriminatory ability, with AUC values of 0.524 and 0.599, respectively. Combined ROC analysis markedly improved diagnostic accuracy, with all panels including ADAM10 achieving AUC values above 0.90, and some reaching as high as 0.988, with high sensitivity and specificity. The combination of ADAM10 with selected cytokines significantly enhances diagnostic performance compared to individual markers, supporting a link between immune dysregulation, barrier dysfunction, and gut permeability in ASD.

Humans↗

PubMed2026

Long-Term Outcomes in Patients With Recurrent Ovarian Cancer and Exceptional Response to PARP Inhibitors.

IMPORTANCE: A subset of patients with platinum-sensitive recurrent ovarian cancer (PS-ROC) treated with maintenance poly(adenosine diphosphate-ribose) polymerase (PARP) inhibitors have exceptional response. Although licensing recommends continuing PARP inhibitors until progression or unacceptable toxic effects, the optimal duration of PARP inhibitors, and the risks of late progression, myelodysplastic syndrome (MDS), or acute myeloid leukemia (AML) in patients with exceptional response are unknown. OBJECTIVE: To determine the long-term outcomes of patients with PS-ROC who have exceptional response to PARP inhibitors, and to explore genotype-phenotype associations. DESIGN, SETTING, AND PARTICIPANTS: This was an international, multicenter, retrospective cohort study of patients with exceptional response to PARP inhibitors, defined as patients with PS-ROC and progression-free survival (PFS) of 5 years or longer from PARP inhibitor commencement. The study was conducted across 41 sites in 14 countries from January 11, 2023, to November 10, 2025. EXPOSURES: Treatment with PARP inhibitors. MAIN OUTCOMES AND MEASURES: The primary end point was PFS, and secondary end points included overall survival, toxic effects, and dose reductions. RESULTS: A total of 320 patients with exceptional response (mean [SD] age, 56.4 [9.4] years) were included, with a median follow-up of 6.8 years (95% CI, 6.6-7.0 years). The median (IQR) PARP inhibitor duration was 75.0 (64.0-91.0) months. Of patients with exceptional response, 211 (65.9%) received continuous PARP inhibitors, but 109 (34.1%) discontinued: 34 (10.6%) due to physician recommendation, 2 (7.5%) had disease progression beyond 5 years, 22 (6.9%) had toxic effects, 17 (5.3%) for patient preference, and 12 (3.8%) for another reason. The 7.5-year and 10-year PFS rates were 88.8% (95% CI, 84.5%-93.3%) and 78.7% (95% CI, 70.5%-87.9%), respectively. Among the patients, 85 (26.6%) discontinued PARP inhibitors for reasons other than disease progression, with a 10-year PFS of 90.1% (95% CI, 80.6%-100%) vs 72.5% (95% CI, 60.3%-87.2%) for those who continued taking PARP inhibitors. Five patients (1.6%) were diagnosed with late-onset MDS/AML. Patients with exceptional response were enriched for variants in the BRCA1 RING domain and the BRCA2 DNA-binding domain. CONCLUSIONS AND RELEVANCE: In this cohort study, most patients with exceptional response to PARP inhibitors remained progression free, including those who discontinued PARP inhibitors without progression. The risk of late-onset MDS/AML was low. These results can guide counseling on the duration of maintenance PARP inhibitors in patients with exceptional response and suggest that functional cure may be possible in patients with PS-ROC and exceptional response to PARP inhibitors.

Humans↗

PubMed2026

Diagnostic performance of intraoperative in vivo hyperspectral imaging for meningioma grading and molecular alterations: results from a prospective feasibility study.

OBJECTIVE: Hyperspectral imaging (HSI) is an emerging intraoperative, noninvasive, contrast agent-free imaging modality that enables quantitative assessment of tissue composition. The present study aimed to investigate whether HSI-derived tissue parameters correlate with WHO grade and molecular markers of aggressiveness in cranial meningiomas. METHODS: In this prospective study, intraoperative in vivo HSI was performed using the TIVITA tissue system, capturing spectral signatures between 500 and 1000 nm. Quantitative tissue parameters included tissue oxygen saturation (StO2), near-infrared perfusion index, organ hemoglobin index (OHI), and tissue water index (TWI). HSI parameters were correlated with histopathological WHO grade and molecular alterations, including CDKN2A/B deletion, TERT promoter mutation, and 1p/22q loss. Group differences were analyzed using one-way ANOVA, and diagnostic performance was assessed using receiver operating characteristic (ROC) analysis. RESULTS: Forty-six meningiomas were included, comprising WHO grade 1 (n = 35) and WHO grade 2-3 (n = 11) tumors. TWI was significantly higher in WHO grade 2-3 meningiomas compared with WHO grade 1 tumors (mean 0.49 [SD 0.12] vs 0.38 [SD 0.17], p = 0.048). ROC analysis demonstrated an area under the ROC curve (AUC) of 0.71 (95% CI 0.56-0.86, p = 0.036) for TWI in discriminating higher-grade disease. A TWI cutoff ≥ 0.367 identified all WHO grade 2-3 meningiomas with 100% sensitivity and 100% negative predictive value. In a molecular subgroup (n = 15), OHI appeared higher in tumors with homozygous CDKN2A/B deletion than in nondeleted tumors (mean 0.77 [SD 0.04] vs 0.62 [SD 0.10]). However, only 3 CDKN2A/B-deleted cases were available, and these findings should be considered descriptive. ROC analysis yielded an AUC of 0.89 (95% CI 0.71-1.00). An OHI cutoff ≥ 0.712 identified all three CDKN2A/B-deleted tumors (100% sensitivity), with 83.3% specificity and 86.7% accuracy. CONCLUSIONS: The present investigation demonstrated that HSI-derived tissue water and hemoglobin metrics provide biologically meaningful information in meningiomas. Low tissue water content appeared to rule out higher-grade diseases in this first subset cohort, while elevated hemoglobin showed a potential association with CDKN2A/B deletion in a small exploratory subgroup. These findings support the potential of HSI as a real-time noninvasive tool for intraoperative risk stratification and should be evaluated in large-scale studies. German Clinical Trials Register no. DRKS00036771 (www.drks.de).

Humans↗

PubMed2025

CS Ratio is an immune-related prognostic biomarker for cervical cancer.

BACKGROUND: The tumor microenvironment (TME) plays a crucial role in cancer progression but its complex structure significant variability among patients present considerable challenges for research. Recent studies have demonstrated that macrophage polarization states defined by the expression levels of CXCL9 SPP1 (CS Ratio) are more prognostically relevant than traditional M1/M2 markers. The CS polarization state reflects a highly coordinated network of pro-tumor anti-tumor variables offering a simplified yet effective immune response indicator for the complex TME. The CS Ratio has been shown to correlate with the abundance of anti-tumor immune cells the gene expression programs of tumor-infiltrating cells responses to immunotherapy. Cervical cancer, one of the most common gynecological malignancies, still faces limited therapeutic options. CXCL9, a member of the CXC chemokine family, plays a critical role in immune regulation, inflammation, tumor growth, angiogenesis, and metastasis. Similarly, SPP1, a cytokine, influences immune-related pathways by regulating molecules such as interferon-γ and interleukin-12. However, no studies have systematically investigated the role of the CS Ratio in cervical cancer or its relationship with immunotherapy characteristics. Research in this area could provide critical insights into the role and clinical potential of the CS Ratio in cervical cancer and related tumors. METHODS: The expression ratio of CXCL9 to SPP1 was analyzed in cervical cancer patients using data from the Gene Expression Omnibus (GEO) database, which revealed significant differences. Data for cervical cancer patients were obtained from The Cancer Genome Atlas (TCGA) database. The optimal cutoff value for the CS Ratio was determined using the maxstat package in R, and Kaplan-Meier (KM) survival curves were constructed. Patients were categorized into High and Low groups based on the median CS Ratio. Immune scores were analyzed, and immune cell infiltration was assessed using CIBERSORT. Differences in the CS Ratio were evaluated across patients with varying pathological T stages and FIGO stages. Additionally, receiver operating characteristic (ROC) analysis was performed using the pROC package in R to calculate the area under the curve (AUC). Univariate and multivariate Cox regression analyses were performed to evaluate the potential of the CS Ratio as an independent prognostic factor in cervical cancer. A Cox regression-based nomogram integrating four key features was subsequently developed for the TCGA-CESC cohort. Nomogram performance was assessed using calibration curves and ROC analysis. RESULTS: The CS Ratio was significantly lower in cervical cancer patients compared to normal controls (P < 0.05). KM survival curves indicated that patients in the CS High group exhibited better prognoses. Immune score analysis revealed significantly higher immune scores (P < 0.05) and lower tumor purity (P < 0.05)in the CS High group compared to the Low group. CIBERSORT analysis revealed significantly higher proportions of CD8+ T cells (P < 0.05) and M1 macrophages (P < 0.05), and a significantly lower proportion of M2 macrophages (P < 0.05), in the CS High group compared to the Low group. The CS Ratio significantly decreased with advancing FIGO stage (P < 0.05). Both univariate (P < 0.05) and multivariate Cox regression analyses (P < 0.05) confirmed the CS Ratio as an independent prognostic factor. ROC analysis demonstrated that the CS Ratio had higher AUC values for predicting 1-year (AUC=0.69), 3-year (AUC=0.66), and 5-year OS (AUC=0.68) than CXCL9 or SPP1 alone. The Cox regression-based nomogram integrating four key features demonstrated predictive capability for 1-, 3-, and 5-year OS in CESC patients (Concordance Index = 0.751; 95% CI: 0.678-0.824; p = 1.50Í10-11). Significant survival differences were observed between the high-risk and low-risk groups based on the nomogram score. ROC analysis yielded high AUC values for survival prediction: 0.85 (95% CI: 0.94-0.75) at 1-year, 0.74 (95% CI:0.84-0.64) at 3-year, and 0.72 (95% CI:0.84-0.61) at 5-year. CONCLUSION: The CS Ratio may serve as a more effective prognostic biomarker for cervical cancer patients.

CXCL9↗

PubMed2025

Assessing individual genetic susceptibility to metabolic syndrome: interpretable machine learning method.

BACKGROUND: Genome-wide association studies have provided profound insights into the genetic aetiology of metabolic syndrome (MetS). However, there is a lack of machine-learning (ML)-based predictive models to assess individual genetic susceptibility to MetS. This study utilized single-nucleotide polymorphisms (SNPs) as variables and employed ML-based genetic risk score (GRS) models to predict the occurrence of MetS, bringing it closer to clinical application. METHODS: Feature selection was performed using Least Absolute Shrinkage and Selection Operator. Six ML algorithms were employed to construct GRS models. A fivefold cross-validation was utilized to aid in the internal validation of models. The receiver operating characteristic (ROC) curve was used to select the better-performing GRS model. The SHapley Additive exPlanations (SHAP) was then applied to interpret the model. After extracting GRS, stratified analysis of BMI, age and gender was performed. Finally, these conventional risk factors and GRS were integrated through multivariate logistic regression to establish a combined model. RESULTS: A total of 17 SNPs were selected for analysis. Among the GRS models, the extreme gradient boosting (XGBoost) model demonstrated superior discriminative performance (AUC = 0.837). The XGBoost's optimal robustness was also validated through five-fold cross-validation (mean ROC-AUC = 0.706). The XGBoost-based SHAP algorithm not only elucidated the global effects of 17 SNPs across all samples, but also described the interaction between SNPs, providing a visual representation of how SNPs impact the prediction of MetS in an individual. There was a strong correlation between GRS and MetS risk, particularly observed among young individuals, males and overweight individuals. Furthermore, the model combining conventional risk factors and GRS exhibited excellent discriminative performance (AUC = 0.962) and outstanding robustness (mean ROC-AUC = 0.959). CONCLUSION: This study established a reliable XGBoost-based GRS model and a GRS prediction platform (https://metabolicsyndromeapps.shinyapps.io/geneticriskscore/) to assess individual genetic susceptibility to MetS. This model has high interpretability and can provide personalized reference for determining the necessity of primary prevention measures for MetS. Additionally, there may be interactions between traditional risk factors and GRS, and the integration of both in a comprehensive model is useful in the prediction of MetS occurrence.

Humans↗

PubMed2025

Hierarchical integration of mNGS, PCR, and other conventional methods for precision TB diagnostics.

UNLABELLED: This study systematically compared the diagnostic accuracy of seven assays for detecting the Mycobacterium tuberculosis complex, including metagenomic next-generation sequencing (mNGS), droplet digital polymerase chain reaction, real-time quantitative polymerase chain reaction, EasyNAT MTC, GeneXpert MTB/RIF, interferon-gamma release assay (IGRA), and acid‒fast staining (AFS). We try to select appropriate combinations of tuberculosis (TB) detection methods for regions with varying levels of medical resources, based on sensitivity, cost-effectiveness, and operational feasibility. A retrospective analysis was conducted on 141 samples collected from patients with suspected active TB at The First Affiliated Hospital of Sun Yat-sen University between April 2022 and April 2024. Among these samples, there were 100 cases assigned to the case group and 41 cases to the control group, based on the tuberculosis diagnostic criteria. Historical data for Xpert, IGRA, and AFS were collected, and parallel experiments using mNGS, droplet digital PCR (ddPCR), real-time quantitative polymerase chain reaction (RT-qPCR), and EasyNAT were conducted on all samples. Diagnostic performance was evaluated by comparing it with the final clinical diagnoses. Sensitivity, specificity, positive predictive value, negative predictive value, and receiver operating characteristic (ROC) curve analysis were conducted, along with DeLong tests for statistical comparison. Compared with the final clinical diagnosis, mNGS demonstrated the highest sensitivity (100%), followed by IGRA (79.2%), EasyNAT (79.1%), RT-qPCR (78.0%), ddPCR (75.8%), Xpert (75.3%), and AFS (16.7%). The specificity was 100% for both Xpert and AFS, followed by ddPCR (97.6%), RT-qPCR (95.1%), EasyNAT (92.7%), IGRA (72.7%), and mNGS (75.6%). ROC analysis revealed a significantly greater area under the ROC curve for mNGS (0.878) than for ddPCR (0.817, P = 0.031). DeLong tests revealed statistically significant differences in diagnostic performance between mNGS and ddPCR (P < 0.05) and between IGRA and AFS (P < 0.01). mNGS uniquely identified the pathogens involved in co-infection and quantified pathogen-specific sequencing reads. Through a comprehensive evaluation of the diagnostic efficacy, cost-effectiveness, and timeliness of tuberculosis detection methods, we propose corresponding combinations of TB testing approaches for regions with different healthcare resources. For undeveloped regions with limited resources, a combination of AFS +EasyNAT + chest X-ray is recommended. Primary care facilities may additionally employ IGRA + RT-qPCR. Intermediate-level hospitals can incorporate Xpert MTB/RIF for drug resistance testing, while tertiary hospitals or specialized centers should, on the basis of these fundamental tests, utilize mNGS for diagnosis and ddPCR for therapeutic monitoring in patients with complex mixed infections. IMPORTANCE: This study is the first to comprehensively evaluate the diagnostic efficacy, cost-effectiveness, and timeliness of seven TB detection methods in a single-center cohort. Our findings provide actionable solutions for optimizing TB diagnostics in diverse healthcare ecosystems, aligning with the WHO's End TB Strategy to ensure equitable access to rapid diagnostics.

Humans↗

PubMed2026

Machine learning-based analysis of oral rinse samples to identify candidate proteomic signatures for severe periodontitis: a pilot study.

This pilot study investigated whether candidate protein signatures from oral rinse samples can distinguish patients with severe periodontitis (stage III/IV) and its subtypes, generalized and localized periodontitis, from non-periodontitis controls. Participants rinsed with phosphate-buffered saline, and samples were analyzed using a Proximity Extension Assay targeting 92 inflammatory and 92 immuno-oncology proteins. A machine learning approach using repeated nested cross-validation and SHAP was implemented to identify protein signatures. The study included 38 patients (18 with localized periodontitis and 20 with generalized periodontitis) and 16 controls. After data preprocessing, 54 samples and 141 proteins were retained. Proteins Gal-1, HGF, TNFSF14, CD27, and ARG1 distinguished periodontitis from controls (ROC-AUC = 0.85, 95% CI 0.82, 0.87). For generalized periodontitis, we found a protein signature including TNFSF14, Gal-1, STAMBP, MUC-16, S100A12, HGF, CASP-8, CD27, LAP TGF-β1, TNFRSF9, and uPA (ROC-AUC = 0.92, 95% CI 0.90, 0.94). For localized periodontitis, we identified ARG1 (ROC-AUC = 0.72, 95% CI 0.68, 0.76). No proteomic signature distinguishing generalized periodontitis from localized periodontitis was identified. This pilot study indicated that oral rinses are suitable for proteomic profiling, and there was a putative protein signature that could differentiate periodontitis, generalized periodontitis, and localized periodontitis from controls. These findings warrant validation in larger independent cohorts, including a clearly defined gingivitis group, before real-world non-invasive screening applications can be considered.

Humans↗

PubMed2026

CoMR: an integrative scoring pipeline for comprehensive mitochondrial proteome reconstruction across eukaryotes.

Mitochondrial proteome reconstruction from eukaryotic sequence data typically relies on prediction of mitochondrial targeting signals (MTSs). However, MTS predictors are primarily trained on model organisms and may perform poorly in phylogenetically divergent lineages or in organisms with atypical or reduced targeting sequences. Accurate reconstruction therefore requires integration of complementary sources of evidence beyond targeting prediction alone. We developed Comprehensive Mitochondrial Reconstructor (CoMR), an integrative workflow that combines targeting prediction, curated homology searches, large-scale similarity searches, and automated phylogenetic analysis within a unified scoring framework. Benchmarking on the model yeast Saccharomyces cerevisiae yielded strong discriminatory performance [receiver operating characteristic (ROC)-area under the curve (AUC) = 0.92], exceeding standalone prediction with TargetP2, a predictor of N-terminal targeting peptides (ROC-AUC = 0.72). In the divergent anaerobic protist Paratrimastix pyriformis, CoMR maintained robust performance (ROC-AUC = 0.86) validated with an experimental proteome despite extreme class imbalance, achieving a precision-recall AUC of 0.183 (~78-fold enrichment over random expectation and ~10-fold improvement over TargetP2). Ablation analyses demonstrate that predictive performance is robust to individual evidence-layer removal, while overlap analyses showed that homology-based searches recovered candidates missed by targeting predictors, particularly in P. pyriformis. Overall, CoMR improves mitochondrial proteome reconstruction over targeting prediction alone and provides a reproducible workflow for predicting mitochondrial and mitochondrion-related organelle protein repertoires across eukaryotes to aid investigations of organelle evolution and proteome reduction.

Proteome↗

PubMed2026

Diffusion MRI radiomics in meningiomas: imaging correlates of tumor grade and intraoperative consistency.

OBJECTIVE: Despite advancements in imaging studies, the preoperative prediction of the biological behavior and intraoperative consistency of intracranial meningiomas remains limited. This study evaluated the association of volumetric diffusion-based and texture-derived radiomic features extracted from routine MRI with histopathological aggressiveness and intraoperative tumor consistency. METHODS: Ninety-seven intracranial meningiomas resected at two tertiary centers were retrospectively analyzed. Volumetric segmentation was performed on contrast-enhanced T1-weighted MRI and coregistered to apparent diffusion coefficient (ADC) maps. Data on first-order diffusion metrics and selected texture features were collected. The associations between World Health Organization (WHO) grade and Ki-67 index were assessed using nonparametric tests and Spearman correlation analysis. Independent factors associated with intraoperative tumor consistency (Zada grades 1-5) were evaluated via multivariate ordinal logistic regression analysis that adjusted for tumor volume, skull base location, calcification status, and WHO grade. Secondary receiver operating characteristic (ROC) curve analyses were performed to differentiate solid (Zada grades 4-5) from soft (Zada grades 1-2) tumors. ROC analyses were performed within the study cohort and were intended as exploratory assessments of discriminative performance. RESULTS: The mean ADC (ADCmean) and the 10th percentile of the ADC decreased significantly with increasing WHO grade (p < 0.001). ADCmean had a moderate inverse correlation with the Ki-67 index (r = -0.42, p < 0.001) and intraoperative tumor consistency (r = -0.45, p < 0.001). In the multivariate analysis, the ADCmean remained independently associated with increasing tumor firmness. Each 0.1 × 10-3 mm2/sec increase corresponded to a 38% reduction in the odds of belonging to a higher consistency category (OR 0.62, 95% CI 0.51-0.74, p < 0.001). The ROC analysis showed good discrimination for solid tumors (area under the curve 0.847, 95% CI 0.742-0.953) and soft tumors (area under the curve 0.824, 95% CI 0.714-0.935). Texture features had weaker associations with intraoperative tumor consistency. CONCLUSIONS: Volumetric diffusion-derived metrics, particularly ADCmean, are associated with both histopathological aggressiveness and intraoperative tumor firmness in meningiomas. Diffusion imaging may reflect a graded microstructural continuum rather than a purely dichotomous property, providing complementary preoperative insights into surgical complexity.

Humans↗

PubMed2026

CT-Derived pelvic morphometry for preoperative risk assessment of recurrent unilateral inguinal hernia.

BACKGROUND: Recurrent inguinal hernia remains a significant challenge in abdominal wall surgery despite advances in mesh-based repair techniques and minimally invasive approaches. Although pelvic skeletal morphology has been implicated in inguinal hernia development, its association with recurrent disease remains incompletely understood. This study aimed to evaluate computed tomography (CT)-derived pelvic morphometric parameters and investigate their potential value in preoperative recurrence risk assessment. METHODS: This retrospective study included 251 male patients with preoperative abdominal CT examinations and complete clinical records who underwent elective inguinal hernia repair at a tertiary referral center. After applying the predefined eligibility criteria, 188 patients with unilateral inguinal hernias constituted the primary study cohort, including 162 primary and 26 recurrent unilateral hernias. The Radoievitch angle and Ami's line were measured independently by two blinded radiology residents using a standardized CT-based pelvic morphometric measurement protocol, and the mean values were used for analysis. Multivariable logistic regression and receiver operating characteristic (ROC) curve analyses were performed to evaluate the association between pelvic morphometric parameters and recurrent inguinal hernia. RESULTS: Patients with recurrent unilateral inguinal hernias demonstrated significantly greater affected-side Ami's line measurements (8.27 ± 0.63 vs. 7.90 ± 0.71 cm, p = 0.014) and larger Radoievitch angles (40.68 ± 4.02° vs. 38.80 ± 3.68°, p = 0.018) than patients with primary unilateral hernias. Both the Radoievitch angle (OR 1.14, 95% CI 1.01-1.28, p = 0.033) and Ami's line (OR 2.26, 95% CI 1.14-4.49, p = 0.020) remained independently associated with recurrent inguinal hernia after adjustment for age and body mass index. ROC analysis demonstrated modest discriminatory performance (AUC 0.634 for the Radoievitch angle and 0.633 for Ami's line), while the multivariable model incorporating age, body mass index, and Ami's line showed slightly improved discrimination (AUC 0.655). CONCLUSION: CT-derived pelvic morphometric parameters were independently associated with recurrent unilateral inguinal hernia. Although their individual discriminatory performance was modest, standardized CT-based pelvimetry may serve as an objective adjunctive tool for individualized preoperative recurrence risk assessment in patients who already undergo CT imaging for unrelated clinical indications. Prospective multicenter studies are warranted to validate these findings and determine their clinical applicability.

Humans↗

PubMed2025

Verification of biological markers of subacute cutaneous lupus erythematosus via TMT labelling proteomics combined with transcriptome data.

OBJECTIVE: This study aimed to investigate biological markers in subacute cutaneous lupus erythematosus (SCLE). METHODS: The tandem mass tag (TMT)-labelling proteomics method was used to explore differentially expressed proteins between SCLE lesions and normal skin tissues. The differences in transcriptomic data between SCLE tissues and normal skin tissues were analysed from the GEO database (GSE81071, GSE109248 and GSE112943). The differences in transcriptomic data from peripheral blood mononuclear cells (PBMCs) of patients with systemic lupus erythematosus (SLE) and normal controls were analysed (GSE81622 and GSE154851). The 35 healthy controls, 30 SCLE patients, 35 SLE patients and 30 lupus nephritis (LN) patients were diagnosed and enrolled. The serum expression levels of IFI44 and EPSTI1 were detected. Data were presented as the mean ± standard deviation or frequency and were analysed using Student's t-test, Chi-square test and one-way ANOVA between the groups. Receiver operating characteristic (ROC) curves were used to analyse the clinical efficacy of IFI44 and EPSTI1 in distinguishing SCLE from SLE. RESULTS: In a comparative analysis of SCLE lesions and normal skin tissues, proteomics studies identified 376 proteins that exhibited significant differential expression. In GO and KEGG analyses, the enriched terms mainly included the interferon-gamma-mediated signalling pathway (p < .001), immune receptor activity (p < .001) and cell adhesion molecules (p < .001). The top 10 hub genes were screened in SCLE as follows: CD8A, CXCL10, IFI44, CD7, CCL5, TLR4, EPSTI1, ISG15, KLRD1 and SELL using Cytoscape (3.10.1) software. The 15 common proteins/genes between proteomics and three datasets results were found, including CXCL10, OAS1, DDX60L, CFB, IFI6, HERC6, IFI44L, GBP1, EPSTI1, OAS2, CXCL11, TYMP, IFI44, ISG15 and IFIT3. The 61 differentially expressed genes in GSE81622 and the top 100 differentially expressed genes in GSE154851, alongside the 15 identified genes described above through Venn diagram analysis. Four common genes, IFI44L, IFI44, EPSTI1 and OAS1, were identified. Two common genes, IFI44 and EPSTI1, were found in hub genes from the proteomics results. The serum levels of IFI44 and EPSTI1 in LN were significantly higher than those in SLE patients (p < .05). ROC curve analysis demonstrated that serum levels of IFI44 and EPSTI1 could differentiate SCLE from SLE with an area under the curve (AUC) of 0.898 and 0.847, respectively. CONCLUSIONS: The IFI44 and EPSTI1 proved to be closely involved in the progression from SCLE to SLE, and can represent new candidate diagnostic molecular markers of occurrence and progression of SCLE.

Humans↗

PubMed2026

RR-interval-based atrial fibrillation detection and burden estimation: cross-dataset validation and calibration-aware probability analysis.

Objective.Atrial fibrillation (AF) burden has become an increasingly important endpoint in long-duration rhythm monitoring, but reliable burden estimation requires more than accurate AF detection alone. In particular, when burden is derived by aggregating predicted AF probabilities over time, probability calibration may directly affect burden validity under external dataset shift.Approach.This study developed an interpretable-interval feature model for AF detection and evaluated it using record-wise cross-validation on a development cohort and independent cross-dataset external validation on public Holter electrocardiographic databases. Window-level performance was assessed using the area under the receiver operating characteristic curve (ROC-AUC), area under the precision-recall curve (PR-AUC), Brier score, expected calibration error (ECE), and calibration intercept and calibration slope. Recording-level AF burden was estimated using both probability-based and hard-label aggregation and evaluated using mean absolute error (MAE) and agreement analyses.Main results.The model showed high discrimination in both development and external evaluation, with external ROC-AUC ofand PR-AUC of. However, external calibration deteriorated despite preserved ranking performance, with Brier score of, ECE(15) of, calibration intercept of, and calibration slope of. In the external cohort, probability-based burden estimation preserved strong association with reference burden but showed weaker raw agreement than hard-label aggregation, with MAE ofversus, consistent with systematic probability underprediction. Repeated external recalibration across record-level splits substantially improved probability quality and probability-based burden estimation. Median probability-burden MAE decreased fromwithout recalibration toafter Platt recalibration andafter isotonic recalibration, while median ECE(15) decreased fromtoand, respectively.Significance.These findings indicate that-interval-based AF detection maintained strong ranking performance in the tested external cohort, but probability calibration should be evaluated explicitly when predicted probabilities are aggregated into AF-burden estimates.

Atrial Fibrillation↗

PubMed2025

2,3-Pyridinedicarboxylate Is Associated with Shorter Recurrence-Free Survival in Patients with Hypopharyngeal Squamous Cell Carcinoma.

UNLABELLED: Introduction: Metabolites are associated with the biology of cancer; however, no metabolites related to prognosis have been identified in head and neck cancer. This study aimed to identify metabolites associated with prognosis in patients with hypopharyngeal squamous cell carcinoma (HPSCC). METHODS: Fifty-two patients who underwent surgery for HPSCC were included and randomly divided into test and validation cohorts of 26 patients each for further metabolome analysis using capillary electrophoresis/mass spectrometry on tumor and non-tumor tissues of the hypopharynx. Twenty-two patients who received adjuvant therapy after surgery were included. The receiver operating characteristic (ROC) and univariate and multivariate analyses were used to explore the relationship between recurrence-free survival (RFS), clinicopathological factors, and differentiated metabolites. RESULTS: ROC analysis revealed six metabolites significantly associated with RFS in both cohorts, and multivariate analysis indicated that 2,3-pyridinedicarboxylate was a significantly independent poorer prognostic factor in the cohorts including patients with HPSCC without any adjuvant therapies (p = 0.017). CONCLUSION: 2,3-Pyridinedicarboxylate, involved in NAD+ metabolism and genomic stability, suggests the possibility of developing molecular-targeted drugs for the production of metabolites related to prognosis. This study identifies novel prognostic metabolites and their associated metabolic pathways in HPSCC, highlighting potential therapeutic targets for treatment. .

Humans↗

PubMed2026

Predicting diagnostic gene biomarkers associated with immune infiltration in patients with diabetes.

Diabetes is a global public health problem with various complications, which can lead to disability and mortality. This study identified potential diagnostic markers for diabetes and explored the immunometabolic mechanisms in the pathological process. The gene expression of 17 diabetes cases and 16 normal controls were obtained from the Gene Expression Omnibus (GEO) database. The "limma" package was employed for screening differentially expressed genes (DEGs). Gene functions and enriched pathways of DEGs were analyzed via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Candidate key genes were screened using the least absolute shrinkage and selection operator (LASSO) regression model and support vector machine recursive feature elimination (SVM-RFE) analysis. The diagnostic effectiveness of identified markers was further verified via the receiver operating characteristic (ROC) curve. The compositional patterns of immune cell infiltration and signaling pathway enrichment associated with key genes were explored via single sample Gene Set Enrichment Analysis (ssGSEA) and GSEA analysis, respectively. Possible miRNAs interacting with key genes were predicted via miRcode database. B2M, FTL, SH3BGRL3, and SOD2 were recognized as diagnostic markers for diabetes based on LASSO regression and the support vector machine recursive feature elimination (SVM-RFE) feature selection algorithm. Analysis of immune cell infiltration demonstrated that the four key genes were related to B cells, neutrophils, macrophages, and CD8+ T cells. The diagnostic value of B2M, FTL, and SOD2 for diabetes was higher than that of SH3BGRL3 according to the ROC curve. Validation experiments indicated that the mRNA expression of B2M and FTL was increased in liver tissues of diabetic mice. B2M and FTL can act as diagnostic markers for diabetes and contribute to new understandings of the disease's molecular mechanisms.

Humans↗

PubMed2026

Artificial intelligence-assisted histopathological diagnosis of endocervical gastric-type adenocarcinoma: a multicenter model development and validation study.

Endocervical gastric-type adenocarcinoma (GAS) is one of the most aggressive subtypes of cervical cancer and is frequently underdiagnosed due to morphological ambiguity, leading to delayed diagnosis. Despite the availability of molecular and genomic assays, their high cost, complexity, and limited reproducibility restrict clinical use. This study therefore proposes a highly sensitive artificial intelligence (AI)-assisted diagnostic system for GAS based exclusively on H&E-stained histopathological images. We included 309 slides from 96 GAS cases collected at Peking University Third Hospital from January 2018 to January 2025, representing the largest GAS cohort reported to date for AI research. In addition, we incorporated other morphologically analogous diseases, encompassing a total of 1,320 slides sourced from four categories: normal cervical mucosa (NORM), benign endocervical lesion entities (BELE), HPV-associated adenocarcinoma (HPVA), and endometrioid carcinoma with mucinous differentiation (ECMD). We developed GASPath, based on a novel multiple instance learning framework that efficiently captures fine-grained morphological variations from H&E-stained images. Beyond internal validation, GASPath was evaluated across 12 independent retrospective cohorts and further subjected to large-scale real-world validation on more than 7,000 samples from March 2024 to April 2025. Across three stages, GASPath demonstrated high performance. In internal validation (Stage I), it achieved an accuracy of 0.980 (95% CI 0.977-0.983) and an ROC-AUC of 0.995 (95% CI 0.994-0.997). In external validation (Stage II), the sensitivity reached 0.902 and improved to 0.968 with proposed strategies. For biopsy samples, GASPath achieved an ROC-AUC of 0.990 (95% CI 0.984-0.997). In large-scale real-world deployment (Stage III, n = 7,056), GASPath achieved a balanced accuracy of 0.953, with 100% sensitivity for GAS (45/45 cases correctly identified). The heatmaps highlight morphological features of GAS that are easily underestimated, such as irregular, angulated glands, subtle loss of nuclear polarity, and mild cytologic atypia, which show substantial morphological overlap with other diagnostic categories. GASPath enables high-sensitivity detection of GAS in routine H&E-stained slides, obviating the need for extensive auxiliary testing while preventing underdiagnosis and misdiagnosis. This advancement addresses a critical gap by streamlining diagnostic workflows without compromising accuracy. Its implementation could enable cost-effective, scalable AI-assisted diagnostics, potentially transforming the early detection and management of this aggressive cancer subtype.

Female↗

PubMed2026

Lymphocyte-C-Reactive Protein Ratio as Promising New Marker for Predicting Surgical Site Infection in Children With Ulcerative Colitis.

BACKGROUND: Surgical site infection (SSI) is a major complication after ileal pouch-anal anastomosis (IPAA) in pediatric ulcerative colitis (UC), significantly impairing quality of life. The lymphocyte-to-C-reactive protein ratio (LCR), a composite marker of systemic inflammation and immune/nutritional status, has emerged as a potential predictor of postoperative outcomes. This study assessed the utility of preoperative LCR in predicting SSI in pediatric UC. METHODS: We retrospectively reviewed pediatric UC patients who underwent IPAA at Mie University Hospital between 2000 and 2024. Preoperative LCR values were analyzed, and the optimal cutoff for SSI prediction was determined using receiver operating characteristic (ROC) analysis. Multivariate logistic regression was performed to identify independent risk factors. SSI was defined according to CDC criteria within 30 days postoperatively. RESULTS: Among 57 patients, 11 (19.3%) developed SSI. The incidence was higher in three-stage procedures than in two-stage procedures (22.7% vs. 17.1%). In both groups, preoperative LCR was significantly lower in SSI-positive patients. ROC analysis demonstrated good discrimination (AUC: 0.80), with an optimal cutoff of LCR < 5000 (sensitivity: 90.9%, specificity: 71.7%). Multivariate analysis confirmed LCR < 5000 as an independent predictor of SSI (odds ratio [OR]: 6.34, 95% CI: 1.23-48.2, p = 0.027). CONCLUSION: Preoperative LCR is a simple, objective biomarker that reliably predicts SSI risk in pediatric UC patients undergoing IPAA. Incorporating LCR into preoperative risk stratification may enable personalized interventions, including nutritional optimization and tailored prophylaxis, to improve surgical outcomes.

inflammatory bowel disease↗