Tag: pubmed

Commun Biol. 2026 Jul 14. doi: 10.1038/s42003-026-10647-5. Online ahead of print.

ABSTRACT

Conserved fecal microbiome signatures of intestinal diseases across domestic mammals offer a non-invasive avenue to monitor animal health and advance One Health, yet systematic meta-analysis with cross-study, cross-disease, and cross-host validation remains lacking. We present a leave-one-dataset-out meta-analysis defining generalizable intestinal disease signatures in mammalian hosts. Analyzing 512 samples from four bovine diarrhea and three canine IBD studies, we identified 12 bovine and 8 canine stable signature genera marked by depleted short-chain fatty acid (SCFA) producers and enriched pathobionts through a compositional random-effects framework with per-study covariate-adjusted effect sizes. A minimal signature set matched full-feature models across five machine learning models, and study-aware transfer learning improved cross-study generalization. Across 367 samples, signatures outperformed for intestinal versus non-intestinal phenotypes in cross-disease prediction. Cross-host validation across equine, feline, caprine, swine, and human datasets (533 animal and 1,182 human samples) revealed canine IBD-associated signatures outperformed in feline intestinal disease prediction, while bovine diarrhea-associated signatures generalized better to herbivorous hosts and human intestinal diseases. These findings may support the existence of conserved microbial signatures across veterinary and human medicine, warranting further investigation toward diagnostic applications.

PMID:42449164 | DOI:10.1038/s42003-026-10647-5

Sci Rep. 2026 Jul 14. doi: 10.1038/s41598-026-61589-1. Online ahead of print.

ABSTRACT

Interprofessional education (IPE) prepares medical and dental students for collaborative, team-based care, yet little is known about how students perceive IPE within integrated academic environments in the Gulf region. A cross-sectional study was conducted between January and April 2025 at RAK Medical & Health Sciences University and RAK College of Dental Sciences in the United Arab Emirates. A printed, structured questionnaire adapted from validated tools was distributed to undergraduate medical and dental students. The survey evaluated interdisciplinary knowledge, teaching content, interprofessional value, and attitudes toward IPE using a five-point Likert scale. Data were analyzed using SPSS version 23, with descriptive statistics, Shapiro-Wilk normality tests, unequal variance t-tests, Cronbach’s alpha, and Spearman’s correlation utilized to evaluate group differences and internal consistency. Ethical approval was obtained (Ref: TAKMHSU-HEC-51-2023/24-F-D). A total of 273 students participated (157 medicals, 116 dentals; 50.2% female). Clinical-phase students reported significantly more favorable perceptions across domains of interdisciplinary knowledge, teaching content, and interprofessional value (p < 0.01). The internal consistency of the questionnaire was high (α > 0.85 for most domains). Strong inter-domain correlations were observed, especially between teaching content and perceived value. No significant differences were found based on gender. Clinical exposure was associated with more favorable perceptions of IPE. These findings support embedding structured, experiential IPE from the preclinical years onward-through shared case-based teaching, interprofessional simulation, and co-facilitated clinical activities-rather than relying on clinical contact alone. For curriculum developers and institutional policymakers, the results highlight the value of integrating IPE across both preclinical and clinical curricula and of targeting attitudinal development specifically. Longitudinal and intervention-based studies are needed to confirm whether such exposure produces durable gains in collaborative competence.

PMID:42449157 | DOI:10.1038/s41598-026-61589-1

Sci Rep. 2026 Jul 14. doi: 10.1038/s41598-026-61846-3. Online ahead of print.

ABSTRACT

This study addressed a critical challenge in higher education informatization, where the evaluation of teaching resource allocation and management process efficiency has traditionally relied on subjective judgment and lacked unified quantitative criteria. To overcome these limitations, a Resource Configuration and Business Coordination (RCBC) model-based evaluation framework was developed. The study utilized data from the National Higher Education Statistics published by the Ministry of Education of China and the University of California, Irvine (UCI) educational resource dataset. An evaluation index system was constructed across four dimensions: resource distribution balance, utilization efficiency, coordination effectiveness, and process bottlenecks. The collected data were cleaned, normalized, and subjected to feature extraction to ensure analytical consistency and reliability. To capture the nonlinear relationships among multidimensional indicators, a multi-objective optimization framework based on the RCBC model was established. Model parameters were determined through a hybrid weighting strategy that integrated the Analytic Hierarchy Process (AHP) and the Entropy Weight Method (EWM), thereby improving the robustness and rationality of parameter assignment. The effectiveness of the proposed framework was assessed through regression analysis and sensitivity testing in teaching resource allocation and process management scenarios. The results demonstrated that the optimized allocation strategy improved overall resource utilization by 14.2%, increased management process efficiency by 10.5%, and enhanced prediction accuracy by 37.3% under cross-validation conditions compared with conventional approaches. These findings indicate that the proposed RCBC model provides superior performance in evaluating and optimizing educational resource allocation and operational processes. Overall, this study offers a data-driven framework for higher education informatization and provides both theoretical support and practical guidance for the development of intelligent teaching management systems.

PMID:42449155 | DOI:10.1038/s41598-026-61846-3

Nat Genet. 2026 Jul 14. doi: 10.1038/s41588-026-02668-x. Online ahead of print.

NO ABSTRACT

PMID:42449151 | DOI:10.1038/s41588-026-02668-x

Sci Rep. 2026 Jul 14. doi: 10.1038/s41598-026-62137-7. Online ahead of print.

ABSTRACT

Cardiometabolic multimorbidity (CMM), defined as the coexistence of two or more cardiometabolic diseases, poses a growing global health burden. However, few studies have jointly evaluated the risk of CMM using indicators of both insulin resistance and frailty. Using data from the China Health and Retirement Longitudinal Study (CHARLS), we constructed a composite index integrating the metabolic score for insulin resistance (METS-IR) and the frailty index (FI) and investigated its association with incident CMM among 2,968 middle-aged and older Chinese adults. During the follow-up period, 230 participants (7.75%) developed CMM. In fully adjusted Cox regression models, each 1-SD increase in baseline and cumulative METSIR-FI was associated with a 35% (HR = 1.35, 95%CI: 1.22-1.49) and 45% (HR = 1.45, 95%CI: 1.31-1.61) higher risk of CMM, respectively. Participants in the highest tertile of baseline METSIR-FI had a significantly higher risk of CMM (HR = 2.78, 95%CI: 1.79-4.30), with even stronger associations observed for cumulative METSIR-FI (HR = 4.29, 95%CI: 2.63-6.98) and the highest-risk cluster (HR = 3.69, 95%CI: 2.46-5.55). Restricted cubic spline analyses revealed significant nonlinear dose-response relationships with threshold effects. Incorporating METSIR-FI into conventional risk models improved the C-statistic from 71.32% to 77.47%, with significant net reclassification improvement and integrated discrimination improvement. These findings suggest that a joint metabolic-frailty burden indicator provides incremental prognostic value beyond conventional risk factors and may serve as a practical composite indicator for CMM risk stratification among middle-aged and older adults.

PMID:42449137 | DOI:10.1038/s41598-026-62137-7

Sci Rep. 2026 Jul 14. doi: 10.1038/s41598-026-61429-2. Online ahead of print.

ABSTRACT

Fluvial terraces preserve critical records of Quaternary tectonic uplift and river incision, yet their regional-scale identification remains hampered by the subjectivity and spatial discontinuity of conventional methods. This study presents a convolutional neural network (CNN) framework, built on a modified U-Net encoder-decoder architecture, for automated, multi-level terrace sequence recognition along the approximately 600-km Yichang-to-Wuhan corridor of the middle Yangtze River. The model ingests six-channel DEM-derived morphometric inputs-elevation, slope, profile curvature, planform curvature, topographic wetness index, and topographic position index-computed from the ALOS AW3D30 DEM, with training labels derived from 46 RTK-GNSS-surveyed terrace cross-sections. Spatial block cross-validation was employed to partition the dataset, ensuring geographic isolation between training and test tiles. Evaluated against independent test data, the CNN achieves an overall accuracy of 92.3%, a Kappa coefficient of 0.896, and a macro-averaged F1 score of 89.0%, outperforming slope-threshold, object-based image analysis, and Random Forest benchmarks-all of which underwent equivalent hyperparameter optimization-particularly for higher, more fragmented terrace levels. Four terrace levels (T1-T4) were mapped across the study corridor, revealing a systematic west-to-east decline in terrace completeness that mirrors the regional tectonic gradient from the Huangling anticline to the subsiding Jianghan Basin. Quantitative analysis of terrace deformation yields tectonic uplift rates ranging from 0.28 mm/year near Yichang to 0.06 mm/year in the basin interior, with localized elevation offsets of 8-15 m across major fault zones. A tectonic activity intensity index (TAI), supported by spatial buffer statistics, highlights the Yichang and Wuhan sub-reaches as the most actively deforming segments. We acknowledge that climatic oscillations modulate terrace formation and that the current framework cannot fully decouple tectonic from climatic signals; nonetheless, the spatially coherent deformation patterns localized along fault traces favor a predominantly tectonic interpretation. These findings demonstrate that CNN-assisted terrace mapping can provide spatially continuous neotectonic insights unattainable by field methods alone.

PMID:42449136 | DOI:10.1038/s41598-026-61429-2

Sci Rep. 2026 Jul 14. doi: 10.1038/s41598-026-61282-3. Online ahead of print.

ABSTRACT

Osteoarthritis is the most common degenerative joint condition, yet its pathogenesis remains incompletely understood. This study aims to identify key differentially expressed genes (DEGs) in osteoarthritis-affected synovial tissues and investigate potential underlying immune mechanisms using bioinformatics approaches. Gene expression datasets GSE12021, GSE55235, and GSE55457 from the Gene Expression Omnibus (GEO) were analyzed, comprising 30 osteoarthritis and 28 normal synovial tissue samples. Differentially expressed genes (DEGs) were identified using the limma R package. Functional enrichment analysis was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Hub genes were screened via protein-protein interaction (PPI) networks and multiple topological network algorithms. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curves. Immune cell infiltration was assessed with CIBERSORT. In situ hybridization validated hub gene expression in an independent cohort of 9 osteoarthritis and 8 control synovial tissue samples. A total of 388 DEGs were identified, including 167 upregulated and 221 downregulated genes. KEGG pathway analysis associated these genes with immune-related pathways such as TNF, IL-17, and NF-κB signaling. Network-based topological analysis using ten cytoHubba algorithms identified CXCL2, JUNB, CX3CR1, and CCL19 as crucial diagnostic genes for osteoarthritis, which were further validated using an expanded testing set (GSE1919, GSE55457, GSE206848; 22 OA vs. 22 controls). The combined 4-gene signature demonstrated high diagnostic accuracy (AUC = 0.988) in the training set and an AUC of 0.938 in the independent testing set. In situ hybridization demonstrated elevated CX3CR1 mRNA levels and reduced CXCL2 and JUNB levels in osteoarthritis synovial tissues; the directional change of CCL19 mRNA was consistent with bioinformatic predictions, but did not reach statistical significance in the clinical validation cohort. Immune cell infiltration analysis revealed significant differences in eight immune cell types between patients and healthy individuals. An associative negative correlation was observed between JUNB and resting mast cells (R = – 0.54, p = 0.0021). Furthermore, computational analyses, presented as a hypothesis-generating resource, predicted potential regulatory networks involving small-molecule drugs, competing endogenous RNAs (ceRNAs), and transcription factors (TFs) targeting the hub genes. CXCL2, JUNB, and CX3CR1 represent potential diagnostic biomarkers for osteoarthritis, with CCL19 identified bioinformatically as a contributing component of the multi-gene signature, though its clinical validation requires further study. Memory B cells, resting memory CD4⁺ T cells, plasma cells, activated NK cells, and especially resting mast cells, may be associated with the disease’s onset and progression.

PMID:42449128 | DOI:10.1038/s41598-026-61282-3

Sci Rep. 2026 Jul 15. doi: 10.1038/s41598-026-52612-6. Online ahead of print.

ABSTRACT

Glioblastoma (GBM) is a highly aggressive brain tumor with limited prognostic markers to predict patient outcomes reliably. This study investigates the perioperative levels of tryptophan, kynurenine, and neopterin in patients with GBM to assess their potential as biomarkers for prognosis. Twenty-four patients with supratentorial GBM and 24 age- and gender-matched healthy controls were included. Blood and urine samples were collected at four time points: preoperatively, three days postoperatively, prior to adjuvant therapy, and post-adjuvant therapy. Analytical measurements of tryptophan, kynurenine, and neopterin levels were conducted using liquid chromatography-tandem mass spectrometry, and statistical analyses were performed to determine their correlation with survival outcomes. The analysis revealed significant perioperative fluctuations in neopterin, kynurenine and tryptophan levels in GBM patients. Moreover, a trend (p = 0.08) of an association between preoperatively obtained blood level of kynurenine and survival probability was observed supporting further validation of kynurenine-pathway biomarkers in larger, molecularly annotated cohorts.

PMID:42449127 | DOI:10.1038/s41598-026-52612-6

Nutr Diabetes. 2026 Jul 14. doi: 10.1038/s41387-026-00454-6. Online ahead of print.

ABSTRACT

BACKGROUND: The ketogenic diet (KD) is a widely used nutritional intervention for weight loss. The beneficial effects of the KD are intrinsically linked to the state of physiological ketosis, where ketone bodies (KBs) raise, even though minimal effective threshold of blood ketone concentration that correlates with significant weight loss remains unclear. Therefore, the main purpose of this study was to identify the optimal β-hydroxybutyrate (βHB) threshold associated with weight loss in individuals with overweight or obesity undergoing a KD.

METHODS: This secondary analysis included 217 participants (111 males and 106 females) with overweight or obesity, who followed a KD for 14 days. Time to Ketosis (TtK)-defined as the number of days needed to reach and maintain a given ketone concentration-was calculated for each threshold.

RESULTS: Regression analysis showed that a βHB concentration of ≥0.5 mmol/L was the most associated with significant weight loss. Moreover, body weight and gender significantly influenced TtK, suggesting interindividual variability in achieving effective ketosis.

CONCLUSIONS: Achieving and maintaining a ketonemia of at least 0.5 mmol/L may represent a clinically meaningful threshold to optimize weight loss in individuals undergoing a KD. Monitoring βHB levels and reducing TtK may improve individual responsiveness to KD-based interventions.

PMID:42449121 | DOI:10.1038/s41387-026-00454-6

Clin Drug Investig. 2026 Jul 14. doi: 10.1007/s40261-026-01583-7. Online ahead of print.

ABSTRACT

BACKGROUND: Janus kinase (JAK) inhibitors are a new class of medications that are changing how we treat inflammatory skin diseases. Even though these drugs are increasingly being approved for various skin conditions, there is still limited detailed comparison of their effectiveness, safety, and long-term effects across different diseases.

OBJECTIVE: In this study, we systematically evaluated the use of JAK inhibitors in atopic dermatitis, psoriasis, vitiligo, alopecia areata, and hidradenitis suppurativa across both trial and real-world settings.

METHODS: We conducted a systematic review following PRISMA 2020 guidelines and searched major databases for randomized controlled trials (RCTs), open-label extensions, and real-world cohort studies published through May 2025. The main effectiveness outcomes included disease-specific measures: Eczema Area and Severity Index (EASI) for atopic dermatitis, Psoriasis Area and Severity Index (PASI) for psoriasis, Severity of Alopecia Tool (SALT) for alopecia areata, Vitiligo Area Scoring Index (VASI) for vitiligo, and Hidradenitis Suppurativa Clinical Response (HiSCR) for hidradenitis suppurativa. Safety outcomes included rates of adverse events, infections, thromboembolism, and cancer. Patient-centered outcomes included quality of life (DLQI) and pruritus reduction. Risk of bias was assessed using the Cochrane Risk of Bias tool 2.0 (RoB 2).

RESULTS: We included 68 studies (42 RCTs, 14 open-label extensions, and 12 real-world cohorts) with 15,427 patients across five inflammatory skin diseases. Oral JAK inhibitors demonstrated efficacy across multiple conditions compared with placebo, with EASI-75 response rates ranging from 38 to 73% in atopic dermatitis, PASI-75 rates ranging from 33 to 67% in psoriasis, and SALT-50 rates from 30 to 62% in alopecia areata. Topical JAK inhibitors have proven effective for atopic dermatitis and vitiligo but have shown limited benefit in alopecia areata. Safety profiles were generally similar across drugs, with higher rates of upper respiratory infections (5-14%) and herpes zoster reactivation (1-3%) compared with placebo. Serious adverse events, such as major cardiovascular events, venous thromboembolism, and cancers, were rare but did occur.

CONCLUSIONS: JAK inhibitors demonstrate significant efficacy across several inflammatory skin diseases, with a safety profile that warrants ongoing monitoring, particularly in patients with cardiovascular risk factors. Comparative data suggest that selective JAK1 inhibitors appear to offer the most favorable balance between efficacy and safety for atopic dermatitis, whereas JAK1/2 inhibitors showed numerically higher efficacy for alopecia areata, though this difference did not reach statistical significance. However, the interpretation of long-term safety and comparative effectiveness is constrained by the limited duration of controlled trials, under-representation of diverse populations, and reliance on indirect comparisons. PROSPERO registration: CRD420251045477.

PMID:42449091 | DOI:10.1007/s40261-026-01583-7