Search Results (6,152)

Brief campus-based interventions for university students with elevated internet gaming disorder (IGD) symptoms have received little study. This randomized trial evaluated a five-session group program focused on gaming motives, self-regulation, and alternative sources of competence and self-worth. Sixty-three adult students at a Chinese vocational college who scored at least 20 on an adapted Gaming Disorder Scale for Adolescents were randomized to the program (n = 31) or an information-only control condition (n = 32). Assessments were scheduled at baseline, immediately after the intervention, and one month later. Because post-randomization outcome data were unavailable for 19 participants, the comparative analyses were restricted to 44 completers. The originally planned baseline-adjusted ANCOVA showed a lower adjusted T1 IGD score in the intervention group than in the control group (adjusted difference = −4.62, 95% CI −7.33 to −1.91, p = 0.0013). In a post hoc linear mixed-effects model, the between-group difference in change from baseline to post-intervention was −5.16 points (95% CI −7.81 to −2.51; Hedges g = −1.03). At one month, the difference was smaller and not statistically significant (−1.67 points, 95% CI −4.31 to 0.98). None of the secondary outcomes showed a significant interaction. Overall attrition was 30.2%. These preliminary findings concern selected completers rather than an intention-to-treat effect, and the between-group difference was not evident at one month. Retrospective registration, unavailable outcomes for non-completers, and post hoc analyses limit the strength of the inference. The trial was retrospectively registered in UMIN-CTR (UMIN000055209) on 9 August 2024. Full article

Sustainable and demand-adaptive railway operation requires frameworks capable of aligning service capacity with time-varying demand while ensuring safe, operationally feasible, and energy-efficient service. This paper proposes an integrated control-and-planning framework for modular pod-based railway operation based on virtual coupling. The framework combines a convoy control layer, which ensures safe and dynamically feasible virtually coupled operation, with a planning layer formulated as a mixed-integer linear programming (MILP) model for daily service allocation and convoy sizing. This hierarchical framework combines dynamically feasible convoy-control simulations with service-level planning to adapt capacity to passenger demand. The proposed methodology is evaluated through comparative simulations under peak-hour, shoulder-period, and off-peak demand scenarios, as well as over a daily schedule of 20 services. Its performance is compared with a conventional fixed-composition diesel–electric multiple unit (DEMU)-based operation. Results show that the pod-based configuration increases energy consumption under peak-hour conditions, remains comparable during shoulder periods, and substantially reduces energy consumption in off-peak operation, achieving a 57% saving in that regime. At the daily level, total energy consumption decreases from 3864 kWh to 3075 kWh, corresponding to a 20% reduction. These findings indicate that the main value of the proposed framework lies in transforming convoy composition into a demand-adaptive operational variable, thereby improving energy performance at the daily system level while preserving the safe and dynamically feasible operation of virtually coupled pod formations. Full article

AI digital-human livestreaming has become a key format of e-commerce livestreaming due to its low cost and round-the-clock operation. How the technical features of digital humans work together with consumers’ psychological perceptions to drive consumption is an important academic and practical question. Existing studies mostly adopt linear analytical paradigms. They focus on the anthropomorphic appearance features of digital humans. Few studies interpret the synergistic effects of technical–emotional factors from a configurational perspective. Empirical tests on boundary conditions under different platform ecosystems are also scarce. Drawing on the SOR–PAD theoretical framework, this study takes 18,690 livestream bullet-screen comments collected from 40 AI digital-human livestream rooms across Jingdong, Baidu, and Meituan as the research material. It conducts a mixed empirical analysis, combining text mining, machine learning, and fsQCA. The dependent variable, purchase behavior tendency, is obtained from an SVM model trained by matching bullet-screen comments with desensitized background transaction data. This indicator acts as a proxy measure for subjective purchase intention. The SVM model achieves an accuracy of 0.97, recall of 0.94, and an F1-score of 0.95. The findings are as follows. First, four technical features, including professionalism, simulation fidelity, responsiveness, and personalization, together with the three psychological perceptions of pleasure, arousal, and trust, constitute critical antecedents of high purchase behavior tendencies. Second, no single necessary condition can trigger a high purchase behavior tendency. Five equivalent technical–emotional configuration paths are identified, including response-oriented, pleasure-oriented, and multiple-synergy types. Third, the conversion effects of the configuration paths show clear platform boundaries. Different e-commerce formats match differentiated configuration paths. This study introduces configurational causal logic into the existing SOR–PAD framework. It expands the application boundary of this framework for AI digital-human livestreaming scenarios. It supplements the empirical evidence of consumer behavior under human–computer interactions. It also offers practical references for platforms and merchants to operate AI digital-human livestreams. Full article

Background: Whether routinely available laboratory measures are associated with longitudinal bone mineral density (BMD) change in clinical practice remains uncertain, particularly when treatment exposure and other major skeletal determinants are incompletely recorded. This study examined BMD trajectories and incident osteoporosis in a Saudi dual-energy X-ray absorptiometry (DXA) cohort. Anti-osteoporosis therapy, glucocorticoid exposure and menopausal status were unavailable, limiting causal interpretation. Methods: This retrospective longitudinal cohort included DXA examinations performed at King Saud University Medical City (KSUMC), Riyadh, from 2016 to 2021. The trajectory analysis comprised 2147 patients with at least two scans and a minimum one-year interval. Diagnostic category was based on the lowest T-score across the lumbar spine, bilateral femoral necks and distal radius. Twenty linear mixed-effects (LME) models evaluated time-by-biomarker interactions with Benjamini–Hochberg correction. Cox proportional hazards (PH) regression was the primary analysis of incident osteoporosis among 789 patients without osteoporosis at baseline. Results: During 2045 person-years of observation, 107 patients developed osteoporosis (5.2 events per 100 person-years). No event occurred among 124 patients with normal baseline BMD, compared with 107 events among 665 patients with baseline osteopenia (log-rank p < 0.001). In the complete-case Cox model (n = 384; 53 events; C-index = 0.679), baseline osteopenia had a hazard ratio (HR) of 3.12 (95% Confidence interval (CI) 0.89–10.97; p = 0.076); no modelled covariate reached statistical significance. None of the 20 time-by-biomarker interactions remained significant after multiplicity correction (smallest q = 0.214). Four nominal terms with raw p < 0.10 were below the measurement-based clinical threshold and were compatible with chance variation. Conclusions: No routinely measured biomarker demonstrated clinical utility for identifying BMD trajectory in this cohort. Baseline DXA category separated the observed progression pattern, although this partly reflects the distance from the diagnostic threshold and should not be interpreted as a validated prediction model. The principal contribution is a carefully characterised null result. Prospective studies with explicit treatment tracking and repeated bone-turnover measurements are required for confirmation. Full article

Background: To present perioperative and follow-up outcomes of physician-modified endograft (PMEG) repair for juxtarenal and pararenal abdominal aortic aneurysms. Methods: This PRISMA 2020 systematic review and single-arm meta-analysis was registered with PROSPERO (CRD420261340339). PubMed, Embase, Web of Science, the Cochrane Library, and ClinicalTrials.gov were searched until December 2025. Eligible reports described full-text-confirmed cohorts of at least five patients treated with PMEG. The strict primary analysis required endpoint-separable juxtarenal or pararenal populations and used random-effects generalized linear mixed models for pooled proportions. Methodological quality and evidence certainty were assessed using the Joanna Briggs Institute checklist and GRADE framework. Results: Fifteen eligible reports described 981 patients before overlap adjudication; 10 reports originated from one institution and contained overlapping populations. After pathology and endpoint-level overlap adjudication, one to four independent populations informed each endpoint estimate, and single-source outcomes were not pooled. Technical success was 97.8% (95% CI, 94.8–99.1%; three populations, 228 patients), and 30-day mortality was 2.3% (95% CI, 1.1–4.8%; four populations, 299 patients). Acute kidney injury, stroke, and spinal cord ischemia occurred in 4.5%, 1.6%, and 1.7% of patients, respectively. During available follow-up, the single-source Type III endoleak estimate was 3.4% (7/203), any reintervention was 13.2% (95% CI, 2.9–43.7%; two populations, 217 patients; I² = 89.0%), and patient-level target-vessel occlusion was 2.4% (95% CI, 0.6–9.1%; 2 populations, 83 patients). Follow-up estimates were exploratory report-period proportions. GRADE certainty was very low for all key outcomes. Conclusions: PMEG repair demonstrated a high technical-feasibility signal and low observed early event rates in experienced centers, but clinical effectiveness and durability remain uncertain. The evidence base is dominated by overlapping expert-center reports and should not be interpreted as establishing equivalence or superiority to custom-manufactured FEVAR. Full article

Background/Objectives: Thread-embedding acupuncture (TEA) involves the implantation of suture threads into therapeutic points for sustained stimulation; however, its safety evidence remains limited. This systematic review and meta-analysis evaluated adverse events (AEs) associated with TEA to establish its safety profile. Methods: Ten databases were searched up to April 5, 2026 for randomized controlled trials (RCTs) of TEA. Reported AEs were standardized using MedDRA terminology, WHO-UMC causality criteria, and CTCAE version 5.0. Pooled incidence proportions were estimated using generalized linear mixed models, and risk ratios (RRs) were pooled using random-effects models with 95% confidence intervals (CIs). Results: Of the 90 RCTs included, most were conducted in China (81, 90.0%). For TEA monotherapy, pooled AE incidence proportion was 3% (95% CI: 2–7%; I² = 53.7%). Local AEs were most common (111, 5.9%), followed by systemic (5, 0.3%) and other AEs (2, 0.1%). Among 118 participants with AEs, most were classified as Grade 1 (95, 80.5%), with Grade 2 (8, 6.8%) and unassessable cases (15, 12.7%). In comparative analyses, TEA showed no significant increase in AE risk versus sham TEA (RR: 1.15, 95% CI: 0.83–1.60), acupuncture (RR: 0.97, 95% CI: 0.64–1.49), or conventional medicine (RR: 0.28, 95% CI: 0.18–0.45). Only one serious TEA-related AE was reported among 1697 participants (0.06%); the withdrawal rate due to TEA-related AEs was 0.36% (9/2524). Conclusions: TEA demonstrated a favorable safety profile when used alone or as an add-on therapy, with most AEs mild and transient. However, inconsistencies in AE definitions and reporting highlight the need for standardized terminology and more rigorous safety evaluation in future studies. Full article

Evaluating the in vivo systemic tolerance of phytogenic feed additives is a crucial prerequisite before their widespread application in vulnerable newborn ruminants. This study aimed to investigate the systemic effects of orally administered cold-pressed Nigella sativa oil on the hematological and biochemical profiles of neonatal lambs (0–45 days of age) fed exclusively on colostrum and maternal milk. The pre-specified primary endpoint was the absence of clinically meaningful change in hepatorenal markers and complete blood count between groups over 45 days. Thirty-two single-born Merino lambs were divided into a treatment group that received 1.5 mL/day of the oil for the first 15 days of life and an untreated control group. Blood samples were collected on days 0, 7, 21, and 45 to evaluate both immediate and carry-over physiological effects. Using a covariate-adjusted linear mixed-effects model to account for baseline variances, the results demonstrated that the oil was physiologically well-tolerated. The supplementation exerted no significant adverse effects (p > 0.05) on hepatorenal markers or the measured acute-phase protein. The supplementation maintained neonatal energy metabolism stability without inducing artificial lipid suppression in serum triglycerides or total cholesterol levels. Furthermore, the oil preserved hematological homeostasis without negatively impacting red blood cell indices and modulated platelet distribution width indices without causing pathological thrombocytosis. In conclusion, the early direct oral administration of N. sativa oil is a physiologically well-tolerated supplement that supports basal metabolic and hematological stability in pre-ruminant lambs without inducing systemic disruptions within the parameters measured. Full article

Uranium is a critical strategic resource. However, uranium mining can cause severe contamination of surrounding soils by potentially toxic elements (PTEs). Conventional approaches that separately perform source apportionment and risk assessment fail to establish a direct linkage between pollution sources and their associated environmental and health risks. Herein, we develop an integrated framework that combines the absolute principal component score–multiple linear regression (APCS-MLR) model, the potential ecological risk index, and Monte Carlo simulation. The established framework was used to try quantifying the potential sources of soil PTEs and their corresponding ecological and human risks in a uranium mining area. The results showed that the concentrations of U, Th, Cd, and Cr significantly exceeded local background levels, with Cd and U exhibiting higher spatial variability than the other PTEs. The APCS-MLR model identified three potential sources of soil PTE contamination: mining activities, mixed anthropogenic-natural, and natural sources. Mining and mixed sources were the dominant contributors to ecological risk, jointly accounting for 88.7% of the total ecological risk, with Cd identified as the primary ecological risk pollutant. The mixed sources also contributed the largest proportions of non-carcinogenic and carcinogenic health risks, accounting for 52.56% and 67.5%, respectively. Furthermore, children were found to face greater health risks than adults due to higher exposure levels. Priority factor analysis indicated that pollution management should continuously monitor Cd derived from mining activities based on statistical inference. Overall, the proposed integrated framework successfully established a quantitative linkage between pollution sources and associated risks, providing a scientific basis for source-specific and zone-specific soil pollution management in uranium mining areas. Full article

This study develops and empirically evaluates a multilevel analytical framework linking AI-generated mathematical reasoning, students’ diagnostic reasoning, and mathematics achievement in AI-supported mathematical problem solving. A classroom intervention with 76 undergraduate Calculus A students generated 380 repeated student–problem observations across five mathematical tasks and three instructional formulations. Students evaluated AI-generated solutions for final-answer correctness, methodological correctness, and procedural completeness, identified mathematical errors, and proposed corrections before completing an individual posttest. Hierarchical mixed-effects models and student-level achievement analyses were used to examine successive stages of the learning process. Instructional formulation was not significantly associated with the quality of AI-generated mathematical reasoning. Final-answer correctness, methodological correctness, and procedural completeness showed substantial task-specific variation. Instructional formulation was significantly associated with students’ error detection, with higher detection performance under Instruction Types B and C than under Type A, while AI-generated response quality remained comparable across instructional formulations. Baseline mathematical proficiency was the strongest predictor of posttest performance. Students’ Mean Error-Detection Event Rate was positively associated with posttest achievement. No robust overall independent association between instructional formulation and posttest achievement was identified after baseline adjustment. Students’ diagnostic engagement with AI-generated mathematical reasoning was associated with subsequent mathematics achievement, supporting the analysis of diagnostic reasoning as a distinct component of AI-supported mathematics learning. Full article

Background: This study aimed to assess the effects of a combined vitamin D₃ (VD₃) and docosahexaenoic acid (DHA) intervention on cognitive function and blood pyroptotic biomarkers in older adults with mild cognitive impairment (MCI). Methods: In total, 360 participants with MCI were recruited, and randomly assigned into four groups: VD₃ (800 IU/day), DHA (1 g/day), VD₃+DHA (VD₃ 800 IU/day+DHA 1 g/day), and placebo. Cognitive function was evaluated by the Wechsler Adult Intelligence Scale-Revised in China (WAIS-RC), and blood biomarkers were measured by ELISA and Western blot at baseline, 6 months and 12 months. Linear mixed-effects models (LMMs) were employed to analyze longitudinal interaction effects on cognitive function and blood biomarkers. Structural equation modeling (SEM) was conducted to evaluate the parallel mediation effects of blood biomarkers on cognitive improvements. Results: A total of 355 participants completed the trial. Over the 12-month intervention, all intervention groups demonstrated significant improvements in cognitive function and reductions in five blood biomarkers (IL-1β, IL-18, NLRP3, Gasdermin D (GSDMD), cleaved caspase-1) compared to the placebo group (p < 0.05). Compared to each single intervention, the combined VD₃ and DHA intervention yielded superior cognitive improvements in scores for full-scale IQ (FIQ), performance IQ (PIQ), verbal IQ (VIQ) and several subtests (information, comprehension, digit span, vocabulary, picture completion, block design, and picture arrangement), and significantly reduced five blood pyroptotic biomarkers (all p < 0.05). Path analysis revealed that longitudinal GSDMD reduction mediated the improvements in FIQ. Conclusions: A 12-month intervention with VD₃, DHA, or their combination significantly improves cognitive function and mitigates pyroptosis, and the combined intervention showed superior benefits, potentially mediated by downregulating the protein GSDMD. Full article

Climate change is increasing the frequency of heat stress events in dairy farming, adversely affecting milk production, milk composition, cow behavior, and animal health. However, many previous studies relied on distant weather-station data and low-frequency milk recording systems, limiting the assessment of short-term and delayed heat stress responses. Therefore, the aim of this study was to combine dense longitudinal data from automatic milking systems (AMS) with continuously recorded on-farm meteorological measurements to investigate the immediate and lagged effects of heat stress on Holstein dairy cows. The study included 386,587 AMS visit records from 790 cows on three commercial dairy farms in Germany, corresponding to up to 127,310 cow-day records collected between August 2022 and August 2025. Temperature–humidity index (THI) values were calculated based on dense on-farm temperature and relative humidity records and were evaluated for multiple lag periods prior to AMS recordings. Linear mixed models were applied to infer the effects of THI on production, physiological, behavioral, and milking process traits. Increasing THI was associated with reduced daily milk yield, altered milk fat and protein percentages, decreased AMS visit frequency, prolonged milking intervals, and increased milk temperature. For contemporaneous THI, an increase from THI 50 to THI 70 corresponded to model-estimated declines of −0.86 kg in daily milk yield, −0.20% in milk fat content and −0.06% in milk protein content, −0.12 daily AMS visits, and +1.14 °C in milk temperature. The strongest associations were generally observed for prompt and short-term lagged THI windows. In contrast, longer lag periods were associated with weaker and less distinct trait responses. Rather than merely confirming the established decline in milk yield under heat stress, the integrated and temporally resolved analysis revealed trait-specific response patterns across production, behavioral, physiological, health-related, and milking-process traits. In particular, milk temperature and voluntary AMS attendance showed pronounced associations with contemporaneous and short-term THI, demonstrating the value of combining AMS-derived phenotypes with high-resolution on-farm climate data for heat stress monitoring. Full article

Introduction: Chemotherapy-induced peripheral neuropathy (CIPN) is a common and dose-limiting toxicity in child, adolescent, and young adult (CAYA) oncology populations. Despite its clinical impact, objective biomarkers for early detection and monitoring remain limited. Neurofilament light chain (NfL), a marker of axonal injury, has emerged as a potential circulating biomarker of CIPN in adults and potentially for CAYAs. This pilot study evaluates the association between NfL and patient-reported CIPN severity in CAYAs. Methods: We conducted a prospective pilot study of 26 patients with acute lymphoblastic leukemia or lymphoma. CIPN was assessed using FACT-GOG/NTx scores. Linear mixed-effects models evaluated associations between NfL and neuropathy over time, adjusting for age and time from baseline. Logistic mixed models assessed the relationship between NfL and clinically significant neuropathy (FACT-GOG/NTx ≤ 40). Results: NfL was significantly associated with worsening neuropathy. A 50-unit increase in NfL corresponded to a 1.1-point decrease in FACT-GOG/NTx score (p < 0.001). Each doubling of NfL was associated with a 0.61-point decrease in FACT-GOG/NTx (p < 0.001). Higher NfL levels increased odds of neuropathy (OR 4.62, p < 0.001). Associations were strongest in leukemia patients and not observed in Hodgkin lymphoma when separately analyzed. Conclusions: This pilot study demonstrates that circulating NfL correlates with patient-reported neuropathy severity, supporting its role as a potential biomarker for CIPN in CAYAs. Differences between leukemia and lymphoma cohorts may reflect treatment-specific neurotoxicity patterns and should be validated in larger prospective studies. Limitations include small sample size, heterogeneity, and limited power for subgroup analyses. If validated, NfL could be incorporated into routine toxicity monitoring to identify patients at highest risk for progressive CIPN, enabling earlier supportive care interventions, referral to rehabilitation services, or enrollment in biomarker-guided prevention and treatment trials before irreversible nerve injury occurs. Full article

Background/Objectives: Speech-language treatment improves recovery in chronic post-stroke aphasia, but whether individuals continue to benefit from repeated treatment exposure remains unclear. We tested whether successive treatment episodes were associated with continued naming improvement and whether gains were reduced in later episodes relative to earlier episodes. Methods: We analyzed retrospective longitudinal data from 35 participants with post-stroke aphasia who completed at least two aphasia treatment studies. Philadelphia Naming Test scores were obtained before and after each treatment study. The primary analysis used a linear mixed-effects model with fixed effects for timepoint, treatment study, and their interaction, with random intercepts for participants and participant-specific treatment studies. Secondary analyses examined candidate predictors and compared within-treatment with between-treatment change while accounting for elapsed time. Results: Naming improved significantly from pre- to post-treatment across studies 1–3 (estimated mean gain = 5.56 points, 95% CI [3.44, 7.67], p < 0.001). The timepoint-by-treatment-study interaction was not significant (p = 0.384), providing no evidence that gains were attenuated across successive studies. Naming improved faster during treatment than between treatments (adjusted difference = 2.18 points per 30 days, p = 0.013). Conclusions: Repeated treatment opportunities were associated with continued naming improvement in chronic post-stroke aphasia, supporting a longitudinal view of aphasia rehabilitation. Full article

This study investigates the network-level traffic and safety effects of increasing Market Penetration Rate (MPR) of SAE Level 2 and Level 3 automated vehicles under take-over conditions. A calibrated microsimulation model of a real-world 50 km highway corridor in Greece (Nea Odos) was used to develop 18 scenarios combining two take-over contexts (Lane Closure and ODD Exit), two Time Budget (TB) configurations, and four MPR levels (25–100%), complemented by two baselines. Traffic performance was assessed through five network-level indicators (speed, delay, lane-changing frequency, travel time, and density). Safety was evaluated through 674 conflict events extracted via the Surrogate Safety Assessment Model (SSAM), using Time-to-Collision (TTC) as the primary indicator. MPR is the dominant feature of both dimensions. Increasing MPR produces a monotonic reduction in speed (−19.2% at 100% MPR), a sharp decline in lane-changing (−59.8%), and increases in density (+21.1%) and travel time (+22.4%), delay peaks non-monotonically at 50% MPR (+107.9%). Spearman correlations between MPR and the traffic indicators are very strong for speed, lane changes, travel time, and density, while delay time yields a weaker correlation reflecting its non-monotonic response. All operating points remain within free-flow conditions throughout the MPR range. The MPR effect on TTC is marginal (p = 0.065) but non-monotonic, with 75% MPR yielding significantly higher mean TTC than 50% and 100% MPR. Neither TB duration nor TOR context produces a statistically significant effect on traffic indicators or TTC distributions, with negligible effect sizes in both cases. Traffic costs of mixed-traffic automation appear at partial penetration, while network-level safety benefits remain limited and non-linear. Full article

Background: Household poverty may shape physical activity (PA), screen time, and sleep during early childhood, but longitudinal evidence among preschool-aged children remains limited. This study examined longitudinal associations between household poverty status and these movement behaviors over 1 year. Methods: Data from 66 children aged 3–4.9 years were analyzed at baseline and 1-year follow-up. Parents reported sociodemographic characteristics and screen time, with poverty defined using household income and size. ActiGraph accelerometers (GT3X+) were worn for 7 days to estimate MVPA and nighttime sleep. Mixed-effects models examined associations between poverty status and each behavior, adjusting for child age, sex, race, and BMI percentile. Poverty status was assessed at each time point and treated as a time-varying exposure, and Time × Poverty interactions were included to test whether changes differed by poverty status. Results: At baseline, children living at/below the poverty level had higher screen time than children living above the poverty level (8.3 vs. 3.2 h/day, p < 0.05), and this descriptive difference remained at follow-up (7.0 vs. 3.1 h/day; p < 0.05). In adjusted linear mixed-effects models, children living at/below the poverty level had 2.8 additional hours/day of screen time at baseline (β = 2.84, 95% CI: 1.19–4.49, p = 0.001). The Time × Poverty interaction for screen time was not statistically significant (p = 0.64), suggesting no detectable difference in changes over time by poverty status. Poverty status was not significantly associated with MVPA or nighttime sleep, and their interactions with time were also not significant. Conclusion: Screen time was the only movement behavior independently associated with household poverty in this cohort. The non-significant findings for MVPA and nighttime sleep should be interpreted cautiously because of a small poverty subgroup and limited precision. Future studies should examine factors contributing to elevated screen use and evaluate strategies to reduce screen exposure among children from low-income households. Full article