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PubMed2026

Relationships Between Risky Substance Use and Irritable Bowel Syndrome (IBS) Severity, Mental Health, and Smoking-Related Processes in Adults with IBS Who Smoke.

Objective: Irritable Bowel Syndrome (IBS) is a debilitating chronic pain condition that presents a major and growing public health burden. Combustible cigarette smoking plays a role in the maintenance of IBS, and the co-occurrence of these conditions warrants greater focus. Moreover, given that smoking co-occurs with other substance use behaviors, the impact of these comorbid behaviors on physical and mental health-related outcomes among individuals with IBS who smoke is warranted. The goal of the present cross-sectional study was to assess relationships of risky alcohol, cannabis, and opioid use with IBS severity, anxiety and depression, and smoking-related processes among adults with IBS who smoke. Methods: In total, 263 adults who met Rome IV criteria for IBS and who smoked combustible cigarettes were included in the study. Hierarchical regression analyses were conducted to examine the influence of risky substance uses on IBS symptom severity, IBS-related quality of life, anxiety, depression, perceived barriers for smoking cessation, and cigarette dependence. Results: Results indicated that opioid use was statistically related to all criterion variables, whereas alcohol use was specifically associated with depression and anxiety. Cannabis use showed a statistically significant association only with anxiety symptoms. Conclusions: The present investigation is among the first to explore the role of risky substance use in terms of a wide array of IBS, mental health, and smoking processes among adults with IBS who smoke. The findings suggest that substance use should be a focal point of screening and intervention for the IBS population to optimize outcomes beyond the reach of medical therapies.

Irritable bowel syndrome↗

PubMed2026

Acute Stevia Consumption does not Alter Endocrine Responses in Individuals with Normal Weight, Overweight, and Type 2 Diabetes Mellitus.

BACKGROUND: Stevia is a plant-based non-nutritive sweetener. Acute effects of stevia ingestion on glycemia and hormonal responses have not been fully investigated. OBJECTIVE: This objective of this study was to evaluate the acute effects of beverages containing stevia alone and in combination with glucose on glycemic, hormonal, and appetite responses. METHODS: This study evaluated three cohorts of n=23 individuals with either normal weight (NW), overweight (OW), or type 2 diabetes mellitus (T2DM) for which each individual completed four test conditions in a randomized sequence crossover study design. The four test conditions were beverages containing stevia (75.6 mg steviol equivalents), water, glucose (30 g), and stevia+glucose (30 g glucose+75.6 mg steviol equivalents). Blood samples were collected before and for 180 min after beverage consumption. Assessments included net area under the curve (niAUC) and incremental maximal concentration values for plasma glucose, insulin, glucose-dependent insulinotropic polypeptide (GIP), glucagon-like peptide-1, glucagon, and PYY. Appetite was assessed with visual-analog scale questions and energy consumption during an ad libitum meal. RESULTS: Responses to the stevia beverage did not differ significantly from those for water alone, and stevia + glucose did not differ significantly from glucose alone for any of the three groups. CONCLUSION: Acute stevia consumption did not materially alter responses for glycemia or hormones involved in glucose and appetite regulation, appetite ratings, or energy intake at a subsequent meal. Clinical Trial Registry number and website where it was obtained: Clinical Trials.gov Identifier: NCT05287906. Study Details | NCT05287906 | A Trial to Assess Steviol Glycosides on Acute Appetite Hormone Release | ClinicalTrials.gov.

Appetite↗

PubMed2026

Integrative machine learning and transcriptomic analysis reveals molecular mechanisms underlying low survival rate in larval Chinese Bahaba (Bahaba taipingensis).

Chinese Bahaba (Bahaba taipingensis) is a Class I protected marine fish endemic to China. Low larvae survival during artificial breeding severely hinder population recovery. To investigate the molecular mechanism of high mortality in larval fish, this study performed RNA-seq on liver from naturally deceased (ND) and mass-dead (MD) individuals, combined with least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) algorithms to screen for core signature genes. A total of 873 differentially expressed genes (DEGs) were identified, including 112 upregulated and 761 downregulated genes. GO and KEGG enrichment analyses revealed significant enrichment in amino acid metabolism disorders, one‑carbon folate pool impairment, PPAR signaling abnormalities, ECM-receptor interaction, focal adhesion pathway, indicating widespread metabolic suppression accompanied by extracellular matrix remodeling and signaling disturbances in the livers of MD fish. MAD pre-filtering combined with dual machine learning algorithms yielded 18 robust core signature genes, among which SLC38A4, MMP1, FADD, FKBP5, and APOB were consistently identified as high-frequency core genes by both algorithms. SLC38A4 exhibited the highest importance score in the RF model and was significantly downregulated, making it the primary molecule distinguishing ND from MD phenotypes. ROC curve analysis showed that both models achieved an AUC of 1.000 (95% CI lower bound: 0.610), confirming the precise discriminatory ability of the core genes. GSEA further demonstrated significant enrichment of this core gene set in ND samples. This study provides the first systematic elucidation of the molecular mechanisms underlying liver dysfunction in low survival rate B. taipingensis, characterized by amino acid transport impairment, metabolic reprogramming, and structural remodeling, offering theoretical foundations for health assessment, early mortality risk warning, and artificial breeding conservation of this species.

Animals↗

PubMed2026

Shared genetic architecture and cellular convergence between female reproductive disorders and pulmonary function: a genome-wide cross-trait analysis.

Female reproductive disorders (FRDs), including polycystic ovary syndrome, endometriosis, uterine leiomyomata, and infertility, have been epidemiologically associated with impaired pulmonary function. However, it remains unclear whether this cross-organ link reflects shared genetic etiology and, if so, which cellular mechanisms mediate it. We performed a systematic genome-wide cross-trait analysis of three FRDs and lung function traits (FEV₁, FVC, FEV₁/FVC) using GWAS summary statistics from individuals of European ancestry, integrating genetic correlation, bidirectional causal inference, pleiotropy mapping, and single-cell enrichment analyses. We identified significant negative genetic correlations between FRDs and lung volume traits, most prominently for FVC (rg range: - 0.077 to - 0.178). Bidirectional causal analyses indicated that FRDs have a detrimental effect on lung volume, with higher FRD genetic liability associated with reduced lung volume. Cross-trait meta-analysis identified 17 pleiotropic variants across 11 loci, with the 19q13.2 (LTBP4) and 12q13.13 (HOXC6/HOXC9) loci showing strong evidence of shared causal variants. Critically, single-cell analyses revealed that shared genetic risk converged on mesenchymal lineages across organs, specifically alveolar adventitial fibroblasts in the lung and stromal/smooth muscle cells in the endometrium. Transcriptome-wide analyses further nominated the estrogen-responsive gene RERG as a convergent gene linking these conditions with lung function. Our study revealed a shared genetic architecture between female reproductive disorders and lung function traits, providing a basis for further mechanistic investigations and potential clinical evaluation. Furthermore, our findings suggest that shared fibroproliferative and hormone-responsive pathways may offer insights into the biological mechanisms underlying these conditions.

Female↗

PubMed2026

An introductory practical guide to secondary data analysis in pediatric urology.

INTRODUCTION: Secondary data analysis (SDA) has become an increasingly important approach in pediatric urology, enabling the study of long-term outcomes, care variation, and disparities in populations with chronic or congenital urologic conditions. With the growing availability of large datasets, a structured approach to designing and conducting SDA studies is increasingly relevant. OBJECTIVES: To provide an introductory, practical guide to SDA in pediatric urology by (1) summarizing commonly used data sources with representative studies, (2) outlining a stepwise approach to designing and executing SDA studies, and (3) highlighting key methodological considerations, limitations, and opportunities for future work. STUDY DESIGN: Narrative review of existing literature and commonly used datasets relevant to pediatric urology, including administrative claims, hospital encounter databases, clinical registries, electronic health record networks, and population-based surveys. RESULTS: Data sources differ in scope, clinical granularity, longitudinal follow-up, and representativeness, and each is suited to specific research questions. We present a practical workflow for SDA, including dataset selection, cohort definition, and analytic planning. Linkage across datasets can provide a more comprehensive view of care patterns and outcomes, although feasibility is influenced by legal, technical, and data-quality constraints. DISCUSSION: SDA enables population-level analyses and the study of rare conditions that are challenging to evaluate through single-center or prospective designs. However, careful cohort definition, feasibility assessment, and awareness of data limitations are essential to ensure validity and interpretability. CONCLUSION: SDA provides a scalable, cost-efficient framework for generating meaningful evidence in pediatric urology. Continued efforts to harmonize data elements, improve linkage infrastructure, and support cross-institution collaboration will enhance the quality and impact of future research. This article provides a practical framework and examples to support the design and execution of SDA studies.

Humans↗

PubMed2026

Privacy, security, and reliability risks of artificial intelligence in healthcare: a systematic review of empirical evidence.

BACKGROUND: Artificial intelligence (AI) is increasingly integrated into healthcare information systems, supporting clinical decision-making, imaging analysis, and predictive modeling. While these applications offer operational and clinical benefits, they also introduce emerging risks to patient privacy, data security, and system reliability. OBJECTIVE: To systematically review empirical evidence on privacy breaches, security vulnerabilities, and misuse associated with AI applications in healthcare settings. METHODS: PubMed, Embase, Web of Science, Scopus, IEEE Xplore, and ACM Digital Library were searched for empirical studies published between January 2015 and November 2025 that evaluated AI use or misuse in clinical diagnosis, treatment, or decision-making. Two reviewers independently screened studies and extracted data using a standardized form. Findings were synthesized narratively due to heterogeneity in study designs, AI methods, and reported outcomes. RESULTS: Of 7,285 records identified through database searches and 205 through citation screening, 22 empirical studies met the inclusion criteria, spanning multiple clinical domains and data modalities, predominantly medical imaging applications. Five recurring threat categories were identified: patient re-identification, membership inference, unauthorized access and adversarial exploitation, input manipulation, and misuse or overinterpretation of AI outputs. Across studies, AI models were shown to encode latent biometric signals across diverse data types, limiting the effectiveness of traditional anonymization and synthetic data approaches. Adversarial attacks and input manipulation were also shown to compromise diagnostic performance and system integrity. CONCLUSION: This systematic review provides empirical evidence suggesting that contemporary AI systems in healthcare introduce privacy and security risks that may challenge traditional assumptions about data protection. These findings underscore the need for privacy- and security-by-design approaches and governance frameworks that address risks across the AI lifecycle.

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↗

PubMed2026

Acute Haemodynamic and Perceptual Responses to Graded Intradialytic Exercise in Patients on Maintenance Haemodialysis: A Randomised Crossover Trial.

BACKGROUND: Acute responses to graded intradialytic exercise in people receiving haemodialysis remain incompletely characterised. OBJECTIVES: To examine acute haemodynamic and perceptual responses to graded intradialytic resistance exercise compared with a non-exercise control condition. DESIGN: Randomised crossover trial. PARTICIPANTS: Forty-eight clinically stable adults receiving maintenance haemodialysis. MEASUREMENTS: Participants completed seated control and graded lower-limb resistance exercise targeting Borg category-ratio 10 ratings of 3, 5 and 7. Systolic and diastolic blood pressure, mean arterial pressure, heart rate, peripheral oxygen saturation, rating of perceived exertion and acute fatigue were measured before, immediately after and 30 min after each condition. RESULTS: Responses increased progressively with perceived intensity. Compared with control, higher perceived intensity increased systolic blood pressure by 14.9 mmHg (95% confidence interval = 12.7-17.0), diastolic blood pressure by 8.4 mmHg (6.8-10.0), mean arterial pressure by 10.6 mmHg (9.2-12.0) and heart rate by 15.5 beats per minute (12.9-18.1). Rating of perceived exertion increased by 6.7 points (95% confidence interval = 6.3-7.1). Mean peripheral oxygen saturation remained between 95.1% and 97.5%, with no value below 90%. Recorded symptoms occurred in 13 out of 48 higher perceived-intensity sessions; no serious adverse events occurred. CONCLUSIONS: Graded, rating-guided intradialytic resistance exercise produced clear acute dose-response haemodynamic and perceptual changes. These findings support supervised individualisation of acute exercise dose but do not establish long-term safety or superiority of higher perceived-intensity training. TRIAL REGISTRATION: Pan African Clinical Trial Registry: PACTR202606476360900.

Humans↗

PubMed2026

The Acute Effects of Blood Flow Restriction on Ankle Muscle Reaction Time and Proprioception in Healthy Individuals.

Blood flow restriction (BFR) induces hypoxic and metabolic stress, which may alter afferent feedback and neuromuscular control. However, its acute effects on ankle sensorimotor function remain unclear. The aim of the study was to investigate the acute effects of lower-limb BFR on multidimensional ankle sensorimotor function in healthy adults. Twenty-four participants (12 females, 12 males) completed two conditions in randomized order and a crossover design: BFR at 60% arterial occlusion pressure (AOP) and a control condition (20 mmHg). All measurements were performed during occlusion. Outcomes included joint position sense (active and passive), kinesthesia, static and dynamic balance, lower-limb muscle activation (surface electromyography), and muscle reaction time during sudden ankle inversion. BFR impaired active joint position sense at 20 degrees of inversion (p = 0.011), with no changes at other angles or in kinesthesia. Static balance deteriorated, with increases in sway area (p = 0.017), sway distance (p = 0.029), and sway velocity (p < 0.001), particularly under eyes-closed single-leg stance. Posterolateral reach distance decreased (p = 0.023), accompanied by reduced lower-limb muscle activation. Tibialis anterior muscle reaction time during 30 degrees of inversion in the ankle neutral position was shortened (p < 0.001), whereas peroneus longus muscle responses were unchanged. Acute lower-limb BFR impairs ankle sensorimotor control by reducing proprioceptive accuracy, balance performance, and muscle activation, while shortening reaction time. These findings suggest caution when applying BFR during tasks that require high postural demands or end-range control. Registration number and date: NCT07307339, 12/26/2025.

Humans↗

PubMed2026

Assay-dependent variability in peptide biomarker quantification: experimental evidence from renalase in chronic kidney disease.

BACKGROUND: Renalase is a promising biomarker for kidney disease, but published levels vary widely between studies. We hypothesised that variability in commercial enzyme-linked immunosorbent assays (ELISAs) kits and matrix effects (serum vs plasma) drive these inconsistencies. METHODS: Paired serum and plasma samples from 56 participants (28 chronic kidney disease (CKD) stages 2-5, 28 healthy controls) were tested using three commercial renalase ELISAs (BTLAB, Cloud-Clone, EIAab). We assessed intra-assay precision, inter-assay agreement (Spearman's rank correlation and Bland-Altman analysis on log10-transformed values), matrix effects, and associations with estimated glomerular filtration rate (eGFR). Diagnostic performance was evaluated by Receiver operating characteristic (ROC) analysis. RESULTS: Inter-assay renalase concentrations differed markedly (up to orders of magnitude), with weak inter-assay correlations (r ≤ 0.25). Bland-Altman analyses revealed large, systematic biases between kits. Only the BTLAB assay showed consistent serum/plasma agreement, a significant correlation with eGFR (ρ ≈ 0.32-0.42, p < 0.05), and moderate discriminatory performance for CKD in serum (AUC = 0.70) and plasma (AUC = 0.68). Cloud-Clone and EIAab produced divergent results and strong matrix-dependent biases. CONCLUSIONS: Observed variability among commercial ELISA platforms may compromise comparability between studies. Harmonisation, standardised reference materials, and cross-validation are necessary before renalase assays can be used reliably in clinical practice.

Humans↗

PubMed2026

Mapping the Molecular Evolution and Role of Wild Rice GLYIII Protein-Encoding Genes in Abiotic Stress Response.

To address the need for sustainable food production amid rapid global climate change, developing rice varieties that grow optimally even under harsh conditions is essential. An effective approach in this direction would be to harness the stress resilience traits of the crop wild relatives (CWRs) of rice. Among the various crucial stress-responsive genes, the Glyoxalase III (GLYIII) gene family is of utmost importance for its ability to detoxify the toxic glycolytic byproduct, methylglyoxal (MG), in a less energy-intensive, single-step process, as well as for its multifaceted cytoprotective role. In our study, a comprehensive genome-wide search across the Oryza genus revealed that GLYIII genes are conserved across wild rice genotypes. Their number has expanded during domestication, driven by gene duplications. Interestingly, only a few orthologous pairs showed positive selection, suggesting that the functions of most others need to be constrained and or conserved.We found that higher GLYIII activity, Total Antioxidant Capacity, endogenous glutathione (GSH) levels, and free radical scavenging activity contributes to the stress resilience of wild rices O. punctata, O. meridionalis, and O. nivara, in addition to other factors. , , . , . Our qRT-PCR analysis revealed differential expression of the OpGLYIII, OmGLYIII, and OnGLYIII genes across different developmental stages and in response to various abiotic stresses. Furthermore, we report that wild rice GLYIII proteins, specifically OpGLYIII-3, OmGLYIII-3, and OnGLYIII-5, exhibit high catalytic efficiency over a broad pH range and at higher temperatures under in vitro assay conditions. Overexpression of these proteins was found to impart substantial stress resilience to the transformed E. coli cells. These findings collectively suggest that GLYIII proteins constitute a key component of the abiotic stress response machinery in wild rice.

Oryza↗

PubMed2026

Meta-analysis of growth and inactivation kinetics of Legionella.

Quantitative risk assessments intended to inform evidence-based water management plans and public health targets for Legionella in engineered water systems are constrained by fragmented and heterogeneous growth and inactivation kinetics. We conducted a meta-analysis of 25 growth and 39 thermal- and chemical-inactivation studies, fitting microbial persistence models to harmonize parameters. Nonlinear models outperformed first-order formulations, indicating that lag phases and resistant or protected subpopulations are central to Legionella persistence. Random forest analysis identified environmental and methodological drivers of variability based on 226 growth rates and reduction times for thermal (209) and chemical (135) inactivation. Growth was primarily governed by temperature, nutrient availability, and compatible Legionella-host pairings; thermal inactivation by quantification method, temperature, and turbidity; and chemical inactivation by inoculum size, disinfectant type, concentration, and host-associations. Accordingly, temperature-dependent growth parameters and exposure metrics for heat, free-chlorine, and monochloramine, expressed as TT (Temperature×time) and CT (Concentration×time), were derived as condition-specific inputs for predictive models. Growth optima around 37-40 °C, together with lag-time estimates, indicate that hot-water temperature setbacks and energy-saving practices may favor Legionella proliferation under repeated or prolonged lukewarm exposure. Culture- and viability-based TT differences highlight the need to consider viable‑but-non-culturable persistence in monitoring programs. CT comparisons suggest monochloramine may be advantageous because of its lower apparent sensitivity to host-associated protection. Although limited by restricted experimental conditions, the findings show that predictive models should account for microbial ecology, water matrix effects, and quantification endpoints. Future kinetic studies should prioritize realistic multi-host systems, strain pre-adaptation, complementary viability measurements, and standardized protocols and reporting to ensure reproducibility and enable robust system-level predictive modeling.

Legionella↗

PubMed2026

Efficacy of prescription-eligible digital health applications for depression and generalized anxiety disorder in Germany: a systematic review and meta-analysis.

In Germany, prescription-eligible digital mental health applications (DiGA) were introduced in 2020 as promising interventions to address, among others, depression and anxiety disorders, two of the most prevalent mental health conditions worldwide. Despite growing interest in DiGAs, their overall efficacy remains uncertain. This study aimed to systematically evaluate and quantify the efficacy of prescription-eligible digital interventions for depression and generalized anxiety disorder by synthesizing evidence from randomized controlled trials (19 trials; total N = 4,078; pooled mean age = 38.7 years, SD = 12.1). Here we show that prescription-eligible digital applications for depression and generalized anxiety disorder reduce symptom severity compared with control conditions. For depression, effects were observed both immediately after the intervention (number of apps = 5; k = 17; SMD = - 0.49; 95% CI - 0.65 to - 0.32) and at follow-up (number of apps = 1; k = 4; SMD = - 0.35; 95% CI - 0.46 to - 0.29), while evidence for generalized anxiety disorder was limited due to a small number of available studies (number of studies = 2). These findings support the integration of evidence-based digital tools into mental health treatment strategies in Germany. However, the available evidence is currently dominated by a small number of applications, particularly Deprexis, and should therefore not be interpreted as equally representative of all DiGAs currently listed for depression in Germany. The findings also highlight methodological limitations of current research and underscore the need for real-world evaluations, which address not only efficacy but also the effectiveness, content, quality and implementation.

Generalized Anxiety Disorder↗

PubMed2026

Hemotropic mono- and coinfections in Colombian ruminants: descriptive occurrence and host-related factors associated with coinfection in cattle.

Hemotropic pathogens such as Anaplasma, Babesia, Mycoplasma, and Trypanosoma are endemic to cattle and can cause coinfections, complicating disease dynamics and control. However, the host-related factors influencing these infections under tropical conditions remain poorly understood. This study aimed to investigate the occurrence of hemotropic monoinfections and coinfections in ruminants tested for hemotropic pathogens and to identify host-related factors associated with coinfection in cattle under field conditions in Colombia. A total of 104 animals were included: 91 cattle, 10 buffaloes, and 3 goats. Among the cattle, 34 (37.4%) exhibited monoinfections, 47 (51.6%) had coinfections, and 10 tested negative. In buffaloes, seven (70%) presented monoinfections, and two (20%) presented coinfections; in goats, one had a monoinfection, and one had a coinfection, most frequently involving Mycoplasma spp. The predominant coinfection patterns were Anaplasma + Mycoplasma and Mycoplasma + Trypanosoma, particularly in Bos indicus cattle. Bivariate and multivariable analyses revealed that breed was the strongest predictor of coinfection, with animals of less common breeds showing 93% lower odds (aOR = 0.07; 95% CI: 0.02-0.30; p < 0.001). Bos taurus individuals also tended toward lower odds of coinfection in the multivariable model, although this trend did not reach statistical significance. Our findings demonstrate a high frequency of hemotropic coinfections in cattle, particularly those involving Mycoplasma spp., and highlight the influence of host-related factors on infection dynamics. These results underscore the importance of integrating demographic and genetic information into surveillance and prevention strategies to improve the management of hemotropic infections in tropical livestock systems.

Animals↗

PubMed2026

Urinary Small Extracellular Vesicle DNA as a Biomarker for the Non-Invasive Diagnosis of Bladder Cancer.

Existing diagnostic technologies for bladder cancer (BC) suffer from low sensitivity, low specificity, or a lack of validation. Therefore, validated, non-invasive diagnostic biomarkers with high sensitivity and specificity for early detection of BC are needed to complement and improve upon the limitations of existing diagnostic methods. We used low-pass whole genome sequencing (LP-WGS) technology to detect copy number variations (CNVs) in small extracellular vesicle (sEV) DNA isolated from urine samples of patients. Based on these results, we constructed and validated a diagnostic model to differentiate between benign and malignant bladder lesions. We conducted a receiver operating characteristic analysis and calculated the area under the curve (AUC) to evaluate the performance of the diagnostic model. The urine sEV-DNA LP-WGS data revealed CNV differences between benign and malignant samples. The diagnostic model achieved an AUC of 0.953, a sensitivity of 86.7%, and a specificity of 100% in the training cohort and an AUC of 0.985, a sensitivity of 90%, and a specificity of 100% in the validation cohort. Even at the lowest coverage depth of 0.01X, the performance of the diagnostic model remained relatively robust. Notably, the performance of this diagnostic model surpassed that of the biomarker neuron-specific enolase (sensitivity: 85.7% vs. 64.3%; specificity: 100% vs. 87.5%) and urinary cytology (sensitivity: 100% vs. 66.7%; specificity: 100% vs. 94.1%). Our study demonstrates that urine sEV-DNA exhibits high discriminatory power in distinguishing between benign and malignant bladder lesions, making it a promising tool for auxiliary diagnosis of BC.

Humans↗

PubMed2026

Comparative effects of 12-week resistance training on unstable and stable surfaces on muscle stiffness, muscle co-activation, and balance in older patients with knee osteoarthritis.

OBJECTIVE: This randomized trial compared the effects of unstable resistance training (URT), involving resistance exercises on unstable surfaces, and stable resistance training (SRT), performed on stable surfaces, on muscle stiffness, co-activation, and balance in older adults with knee osteoarthritis (KOA). We hypothesized that URT would yield greater improvements by enhancing neuromuscular adaptability. METHODS: Fifty patients with KOA were randomly assigned to the URT group (n = 25) or the SRT group (n = 25). After attrition, 46 participants (URT: n = 23; SRT: n = 23) completed the intervention and were included in the final analysis. Both groups completed a 12-week supervised lower-limb resistance training program (3 sessions/week) consisting of 10 exercises performed under either unstable or stable support conditions. RESULTS: After 12 weeks of intervention, both groups showed significant reductions in pain intensity (p < 0.001). However, compared with the SRT group, the URT group demonstrated significantly greater reductions in quadriceps stiffness (p < 0.05), selected hamstring stiffness outcomes (p < 0.05), and quadriceps-hamstring co-activation (p < 0.001), alongside superior improvements in both dynamic balance and static balance (all p < 0.05). CONCLUSION: While both training modalities are effective for pain relief, URT elicited greater improvements in balance-related performance and neuromuscular-mechanical outcomes than SRT in older adults with KOA. These findings suggest that incorporating unstable support conditions into resistance training may provide additional rehabilitation benefits for this population.

Humans↗

PubMed2026

A multi-scale fusion model based on multi-phase contrast-enhanced CT for predicting pancreatic cancer resectability.

Purpose.Develop a multi-scale fusion model (MSFM) based on multi-phase contrast-enhanced computed tomography (CECT) to predict pancreatic cancer (PC) resectability, thereby assisting expert decision-making.Methods.This retrospective study enrolled 280 patients with PC from four institutions, which were randomly divided into a training cohort (202 patients) and an independent test cohort (78 patients). Three-phase CECT images (arterial, venous, and delayed phases) were used for modeling. The MSFM comprises two sub-networks: (1) a multi-phase fusion network for extracting cross-phase shared fusion features, (2) a phase-specific branch network for capturing phase-specific features; and a post-fusion strategy to generate the final predictive score by integrating the shared fusion features and three groups of phase-specific features. Additionally, a human-machine fusion deep learning model (HMfDL) was constructed by fusing the predictive score of the MSFM with expert assessments.Results.In the independent test, the MSFM achieved an AUC (area under the receiver operating characteristic curve) of 0.8385 (95% CI: 0.7521-0.9249), accuracy of 84.62%, sensitivity of 72.00%, and specificity of 90.57%. This performance outperformed single-phase models (AUC range: 0.7638-0.7781), two-phase models (AUC range: 0.7826-0.7864), and ten states-of-the-art classifiers (AUC range: 0.7404-0.7796). The HMfDL further improved the performance, reaching an AUC of 0.8626 (95% CI: 0.7853-0.9400), accuracy of 91.03%, sensitivity of 80.00%, and specificity of 96.23%. Notably, the HMfDL corrected 58.82% of misdiagnosis made by experts.Conclusions. The MSFM effectively fuses multi-phase CECT to enable highly accurate predictions of PC resectability, and provides valuable support for expert decision-making through HMfDL.

Humans↗

PubMed2026

Non-motor symptoms and healthcare utilization before diagnosis of myasthenia gravis: a nationwide cohort study.

BACKGROUND: Non-motor symptoms have been reported prior to myasthenia gravis (MG) diagnosis. However, the temporal patterns of non-motor symptoms and healthcare utilization before MG diagnosis remain unclear. METHODS: We conducted a retrospective, population-based cohort study using the Korean National Health Insurance Service (KNHIS) database from 2011 to 2021. Incident MG cases were identified using the International Classification of Diseases, Tenth and Rare Intractable Disease codes. Individuals younger than 20  years or with missing health screening data were excluded. Each MG case was matched 1:10 by age, sex, and index date to controls. Non-motor symptoms and healthcare utilization were defined using operational criteria derived from KNHIS claims data. Rate ratios (RRs) and 95 % confidence intervals (CIs) were estimated across four prespecified intervals (0-1, 1-2, 2-5, and 5-10  years) before MG diagnosis. RESULTS: We included 8,355 MG patients and 83,550 controls (mean age, 53.7  years; male, 44 %). MG patients had higher rates of any non-motor symptoms over 10  years(RR 1.34; 95 % CI 1.30-1.39), with the sharpest increase in the year before diagnosis. Depression, anxiety, migraine, constipation, and insomnia consistently showed higher RRs across all intervals. Hospitalizations (RR 1.66; 95 % CI 1.61-1.71) and outpatient clinic visits (RR 1.10; 95 % CI 1.04-1.17) were consistently higher across 10  years, peaking during the 0-1 year before MG diagnosis. CONCLUSION: Non-motor symptoms and healthcare utilization increased years before MG diagnosis. Earlier recognition of these symptom patterns may facilitate timelier evaluation for MG and improve diagnostic pathways.

Humans↗