Tag: pubmed

BMC Public Health. 2026 Feb 4. doi: 10.1186/s12889-026-26469-3. Online ahead of print.

ABSTRACT

BACKGROUND: A majority of adolescents do not meet the recommended levels of physical activity, while reported levels of mental health problems are increasing, and socioeconomic disparities in academic performance are widening. Many schools are implementing physical activity in different forms, but there is inconclusive evidence on what types of interventions improve mental health, cognitive functions, and academic performance and how to implement such interventions. There is a critical need for integrated, feasible, and equitable interventions. The objective of this study is to develop an effective multi-component school-based intervention that will target both physical activity and homework support during an extended school day and evaluate its effects on mental health, cognitive function and academic performance.

METHODS: The study is designed as a cluster-randomised controlled trial with 54 schools and approximately 2,700 students in grade 8 (age 14-15). The intervention includes three weekly 60-minute sessions: (1) Different types of physical activities (2), Homework support with short activity breaks, and (3) Walking and listening to audiobooks. This study will evaluate both outcome effects and implementation process. The primary outcome is anxiety, assessed using the Spence Children’s Anxiety Scale (SCAS-S). Secondary outcomes include physical activity, sedentary time and behaviours measured by accelerometry and questionnaire, cognitive functions assessed by a computer-based test battery, mental health and sleep with questionnaires, and academic performance by grades. Process evaluation will include fidelity, dose, feasibility, acceptability and context, using structured documentation, interviews, focus groups, and observations. The effectiveness of outcomes between groups will be assessed using mixed-effects regression analysis, adjusting for relevant covariates. Process data will be analysed using descriptive statistics and content, and thematic analysis.

DISCUSSION: This study addresses key knowledge gaps in school-based health promotion by integrating physical activity and homework support within the school structure. The results will yield insights into both effectiveness and implementation, informing future policy and practice in schools to promote health and facilitate students’ learning. The intervention targets youth in diverse socioeconomic contexts and is expected to contribute to reducing health and education inequalities.

TRIAL REGISTRATION: The trial was retrospectively registered on April 27, 2021. ISRCTN78666212.

PMID:41634640 | DOI:10.1186/s12889-026-26469-3

BMC Surg. 2026 Feb 3. doi: 10.1186/s12893-026-03494-y. Online ahead of print.

ABSTRACT

OBJECTIVES: This retrospective cross-sectional study aimed to investigate the differences and influencing factors between the headache patients who achieved complete remission or significant reduction in headache frequency postoperatively and those whose frequency remained unchanged.

METHODS: The study was conducted on 386 patients who underwent bariatric surgery at the four university hospitals between January 2018 and June 2024. Patients were divided two groups as with or without headache and then patients with headache were divided into migraine and tension-type headache groups.

RESULTS: Headache duration, HIT-6 and VAS scores were also significantly reduced after operation. Bariatric surgery was significantly and negatively correlated with headache duration (r=-0.170; p < 0.05), HIT-6 (r=-0.353; p < 0.01) and VAS (r=-0.408; p < 0.01). Bariatric surgery had significant effect on HIT-6 (OR: 7.120; p < 0.01), headache frequency (OR: 13.634; p < 0.01) and VAS (OR: 2.024; p < 0.01). In migraine group; duration, HIT 6 and VAS levels were significantly decreased after operation (p < 0.05). In tension type group; only VAS level was significantly decreased after operation (p < 0.05).

CONCLUSION: After bariatric surgery, a statistically significant decrease in headache in terms of impact and severity was observed. This situation reveals that bariatric surgery has a direct and significant effect on headache. In patients with a BMI value on the borderline for bariatric surgery, these values ​​can be lowered slightly in case of severe headache.

PMID:41634636 | DOI:10.1186/s12893-026-03494-y

Transl Oncol. 2026 Feb 2;65:102670. doi: 10.1016/j.tranon.2026.102670. Online ahead of print.

ABSTRACT

Nasopharyngeal carcinoma (NPC) is prevalent in Southeast Asia, including Taiwan. It exhibits higher morbidity as well as mortality in males than in females. However, the role of the androgen receptor (AR) in NPC remains unclear. In this study, AR expression was detected in most NPC cell lines and patient-derived xenografts. Treatment with enzalutamide, an antiandrogen, substantially inhibited patient-derived xenografts growth and demonstrated additive antitumor effects when combined with chemotherapy in AR-positive models. Additionally, transcriptome analysis following enzalutamide treatment revealed activation of hypoxia-inducible factor-1, steroid hormone, and AR pathways, alongside suppression of interferon and tumor necrosis factor pathways. Protein analysis further supported these transcriptomic changes. In AR-overexpressing NPC-B13 cells, AR appeared to regulate thyroid transcription factor-1 (TTF-1, encoded by NKX2-1 gene) and its downstream target epidermal growth factor receptor (EGFR), thereby promoting cancer cell proliferation. Furthermore, chromatin immunoprecipitation suggested that AR may directly bind to the NKX2-1 promoter to upregulate its mRNA expression. Under AR overexpression, Epstein-Barr virus (EBV) remained in a latent state, accompanied by suppression of lytic gene expression. Additionally, Epstein-Barr nuclear antigen-1 enhanced AR transactivation in a dose-dependent manner in NPC cell line reporter assays. Among 96 metastatic NPC tumor samples, AR expression was observed in 35 cases (36.5%), predominantly in males (33/83, 39.8%). AR expression correlated with poorer overall survival, with statistical significance noted in the full cohort and particularly in male patients. This study suggests that AR may promote metastatic NPC progression via the TTF-1/EGFR signaling pathway and interact with EBV to influence disease behavior, especially in males.

PMID:41633021 | DOI:10.1016/j.tranon.2026.102670

ESMO Open. 2026 Feb 2;11(2):106065. doi: 10.1016/j.esmoop.2026.106065. Online ahead of print.

ABSTRACT

BACKGROUND: Although patients with Eastern Cooperative Oncology Group performance status (PS) of 2 constitute a significant proportion of the cancer population, they are often excluded from pivotal clinical trials owing to presumed higher risks of treatment effect dilution, toxicity, and lower compliance. Here, we conducted a systematic review and meta-analysis to evaluate the impact of including PS 2 participants on efficacy and safety outcomes in pivotal cancer clinical trials.

MATERIALS AND METHODS: We searched the ‘Oncology/Hematologic Malignancies Approval Notifications’ and ‘Drugs@FDA’ databases for clinical trials supporting ‘Food and Drug Administration’ anticancer drug approvals from 1 January 2009 to 31 December 2024. Eligible studies were randomized phase III clinical trials of systemic therapies for metastatic solid tumors permitting the inclusion of PS 2 participants. We assessed efficacy outcomes [progression-free survival (PFS) and overall survival (OS)] and safety outcomes [occurrence of any-grade adverse events (AEs), high-grade AEs, serious AE (SAEs), AE-related deaths, and treatment modifications] in the included studies.

RESULTS: Thirty-six trials were included. In subgroup analyses, no statistically significant differences were found between PS 2 and PS ≤1 participants for PFS [hazard ratio (HR) 0.45, 95% confidence interval (CI) 0.30-0.69 versus HR 0.52, 95% CI 0.41-0.66, P = 0.59] and OS (HR 0.81, 95% CI 0.68-0.97 versus HR 0.71, 95% CI 0.66-0.77, P = 0.18). In meta-regression analyses, no significant associations were found for efficacy outcomes. However, a higher proportion of PS 2 participants was significantly associated with an increased risk of SAEs, AE-related deaths, and treatment discontinuations.

CONCLUSIONS: Although PS 2 participants showed a greater propensity to serious toxicity, no significant differences in efficacy outcomes were observed compared with those with PS ≤1. Our results support the inclusion of PS 2 participants in clinical trials, as their exclusion limits the generalizability of results.

PMID:41633012 | DOI:10.1016/j.esmoop.2026.106065

Ultrasonics. 2026 Jan 23;163:107973. doi: 10.1016/j.ultras.2026.107973. Online ahead of print.

ABSTRACT

Reliable Lamb-wave-based Structural Health Monitoring (SHM) depends on accurate baseline selection under varying temperatures. This study presents LambNet-T, a lightweight path-conditional Transformer-based autoencoder for temperature-aware baseline learning across multiple transducer paths. LambNet-T employs Attention Pooling (AP) to generate contextual embeddings and enables robust baseline selection using Cosine Similarity (CS) with a Median-based evaluation strategy, improving diagnostic accuracy and temperature robustness in multi-path Lamb-wave SHM. Experiments on a composite panel over -10 to +50 °C used only four baseline temperatures to reflect practical constraints, with quadratic interpolation for data augmentation. LambNet-T demonstrated significantly higher training efficiency than a convolutional autoencoder (CAE-GAP). During inference, the Median of the highest path-specific CS values identified the optimal temperature-compensated baseline. The method achieved high precision (R² = 0.994 ± 0.001), outperforming both CAE-GAP and conventional Optimal Baseline Selection (OBS). Integration with an existing damage localization framework reduced impact location errors to as low as 4.12 mm. A conservative statistical filter, based on baseline selection variability, was applied to manage uncertainty. All experimental datasets are openly available for reproducibility.

PMID:41633009 | DOI:10.1016/j.ultras.2026.107973

Burns. 2026 Jan 29;52(3):107877. doi: 10.1016/j.burns.2026.107877. Online ahead of print.

ABSTRACT

BACKGROUND: Pediatric burn injuries pose significant health concerns and rank fifth globally in non-fatal injuries. Current evidence associates lower socioeconomic status (SES) with higher incidence of burn injury, greater TBSA, higher need for admission, and greater involvement of child protective services. There is a paucity of Canadian data on the topic, and effects of indices of deprivation on outcomes have not been investigated extensively.

METHODS: A retrospective single-centre study was carried out to examine effects of SES and Ontario Marginalization Index (OMI) on pediatric burn patient outcomes. One-way ANOVA with post hock Bonferroni correction was used for continuous dependent variables (i.e. TBSA, length of stay), and Pearson chi-square analysis was done for categorical variables (i.e. CAS involvement, need for OR, need for admission). P-value of 0.05 was set a priori to determine statistical significance.

RESULTS: No differences in outcomes were found between the four quartiles of SES categories. Analysis of the OMI for Material Resources, Racialized and Newcomer Populations, Age and Labour Force, and Household and Dwellings produced statistically significant findings. Patients with a higher degree of marginalization for most indices tended to have greater TBSA, time to surgery, and length of stay. An unexpected finding was that patients with the lowest Age and Labour Force deprivation indices were likely to have greater TBSA.

CONCLUSION: Identifying the effects of various social determinants of health on pediatric burn patients remains a challenging problem. While this study found no differences in patient outcomes based on income alone, examination of the granularity in deprivation provided notable differences. These effects could be further clarified with a cross-provincial or national study.

PMID:41633001 | DOI:10.1016/j.burns.2026.107877

Knee. 2026 Feb 2;60:104350. doi: 10.1016/j.knee.2026.104350. Online ahead of print.

ABSTRACT

BACKGROUND: Total knee arthroplasty (TKA) and distal femoral replacement (DFR) can be used in limb-salvage after resection of bony tumors, but few reports have examined patient-reported outcome measurements (PROMs) with survival data in young patients. This study analyzed individuals who underwent TKA/DFR for neoplasm at a young (≤40) age, to report outcomes and survival experience.

METHODS: A retrospective study on 12 TKAs/23 DFRs was conducted between January 1990-2020 in 35 patients ≤40 years old. Electronic medical records were reviewed to identify patients with neoplasm, and collect data. Patients were contacted to obtain PROMs.

RESULTS: The median age (interquartile range) at surgery for TKAs and DFRs was 26.7 (22.7-34.0) and 24.6 years (20.9-28.4), respectively. Median follow-up was 3.95 (0.33-8.14) and 3.01 years (1.72-6.07). TKAs were more commonly due to complications after allograft reconstruction (75.0% vs. 0.00%, p < 0.0001), had lower blood loss (250 vs. 800 ml, p = 0.01) and a higher rate of tourniquet use (75.0% vs. 34.8%, p = 0.04). Revision-free survival (8-year) was 54.7% (95% confidence interval (CI): 13.7%-83.3%) for TKAs and 37.9% (95% CI: 10.4%-66.0%, p = 0.12) for DFRs. For TKAs, median KOOS Jr. was 76.3 (76.3-79.9), VR-12-Physical was 50.0 (40.5-51.7), VR-12-Mental was 40.8 (32.6-45.8), LEAS was 12.0 (12.0-13.0), and FJS was 23.0 (19.0-25.0), without statistical difference from the DFR group.

CONCLUSION: Patients ≤40 years old who underwent TKAs/DFRs for neoplastic disease demonstrated a similarly high postoperative complication rate and poor long-term survival. Almost all PROMs were favorable, reflecting a more promising postoperative experience than survival curves might demonstrate.

PMID:41632986 | DOI:10.1016/j.knee.2026.104350

Biomed Phys Eng Express. 2026 Feb 3. doi: 10.1088/2057-1976/ae4107. Online ahead of print.

ABSTRACT

&#xD;Parkinson’s disease (PD) is a neurodegenerative disorder characterized by a range of motor and non-motor symptoms. Despite extensive research, the neural structure of time distortion, remains unclear. This study aimed to determine the neurobiological origins of time distortion by analyzing dynamic features in PD patients compared to control participants.&#xD;Approach.&#xD;We used PD and control electroencephalography (EEG) signals to investigate brain function during time distortion. The EEG signal was recorded during an interval-timing task. Following artifact reduction and EEG signal segmentation, dynamic features were extracted from each frequency band across all the channels. Channels showing significant discrepancies between the two groups were selected by statistical analysis. The features are sent to an Artificial Neural Network (ANN) classifier to evaluate their discriminative potential.&#xD;Main results.&#xD;The results indicated lower values of Lyapunov Exponent and Approximate Entropy along with higher value of Fractal dimension in PD which presented higher level of irregularity and randomness, particularly in the CPz, P5, P6, and C5 channels. The ANN classifier achieved 90% accuracy, 89% sensitivity, 87% F1 score, and 95% specificity in a 10-fold cross-validation. &#xD;Significance.&#xD;Significantly different channels were concentrated in the central and parietal areas of the brain and were linked to decision-making, maintenance, and retrieval of stored information, and working memory. Moreover, based on dynamic EEG analysis, it seems that disrupted connections between the basal ganglia and posterior parietal cortex in PD appear to compromise frontoparietal network dysfunction, which is associated with impaired temporal processing in patients with PD.&#xD.

PMID:41632980 | DOI:10.1088/2057-1976/ae4107

JMIR Form Res. 2026 Feb 3;10:e84023. doi: 10.2196/84023.

ABSTRACT

BACKGROUND: Poor sleep is a concerning public health problem in the United States. Previous sleep interventions often face barriers such as high costs, limited accessibility, and low user engagement. Recent advancements in artificial intelligence (AI) technologies offer a novel approach to overcoming these limitations. In response, our team developed a prototype AI sleep chatbot powered by a large language model to deliver personalized, accessible sleep support.

OBJECTIVE: This study aimed to examine the feasibility, usability, acceptability, and preliminary efficacy of the AI chatbot for sleep promotion.

METHODS: We conducted a quasi-experimental, single-group study with adults in the United States aged 18 to 75 years who self-reported poor sleep. The chatbot was integrated into a commercially available messaging app. Participants were asked to engage with a virtual sleep therapist via texting over 2 weeks. The chatbot provided ongoing, individualized sleep guidance and adapted recommendations based on participants’ prior conversations. Feasibility, usability, and acceptability were descriptively summarized. Sleep was assessed using questionnaires before and after the intervention.

RESULTS: Of the 107 adults who enrolled in the study, 88 (82.2%) completed chatbot registration. Among these 88 participants, 65 (73.9%) initiated interactions, and 44 (50%) completed the 2-week intervention. The final analysis included 42 adults (mean age 36, SD 11 years; n=12, 28.6% male). On average, participants engaged with the chatbot for 58 (SD 42) minutes, with each chat session lasting approximately 9 (SD 6) minutes. Most reported favorable experiences with the chatbot. The average usability score was 85.2 (SD 10.7) out of 100, which was well above the benchmark of 68. The chatbot was rated as highly acceptable, with a satisfaction score of 27.3 (SD 4.1) out of 32. All participants perceived the chatbot as effective, with ratings ranging from “slightly effective” to “extremely effective.” The preliminary evidence showed improved sleep outcomes after chatbot use: total sleep time increased by 1.4 hours (P<.001); sleep onset latency decreased by 30.9 minutes (P<.001); sleep efficiency increased by 7.8% (P=.007); and scores improved for perceived sleep quality (mean difference [MD] -5.4; P<.001), insomnia severity (MD -7.9; P<.001), daytime sleepiness (MD -4.7; P<.001), and sleep hygiene skills (MD -13.2; P<.001). No significant change was observed in sleep environment (MD -1.1; P=.16).

CONCLUSIONS: Our AI chatbot demonstrated satisfactory feasibility, usability, and acceptability. Improvements were observed following chatbot use, although causality cannot be established. These findings highlight the potential of integrating state-of-the-art large language models into behavioral interventions for sleep promotion. Future research should include objective sleep measurements and conduct randomized controlled trials to validate the study findings. If confirmed, this AI chatbot could be scaled to support sleep health on a broader level.

PMID:41632970 | DOI:10.2196/84023

J Med Internet Res. 2026 Feb 3;28:e82170. doi: 10.2196/82170.

ABSTRACT

BACKGROUND: While artificial intelligence (AI) holds significant promise for health care, excessive trust in these tools may unintentionally delay patients from seeking professional care, particularly among patients with chronic illnesses. However, the behavioral dynamics underlying this phenomenon remain poorly understood.

OBJECTIVE: This study aims to quantify the influence of AI trust on health care delays through integrated survey-based mediation analysis and real-world research, and to simulate intervention efficacy using agent-based modeling (ABM).

METHODS: A cross-sectional online survey was conducted in China from December 2024 to May 2025. Participants were recruited via convenience sampling on social media (WeChat and QQ) and hospital portals. The survey included a 21-item questionnaire measuring AI trust (5-point Likert scale), AI usage frequency (6-point scale), chronic disease status (physician-diagnosed, binary), and self-reported health care delay (binary). Responses with completion time <90 seconds, logical inconsistencies, missing values, or duplicates were excluded. Analyses included descriptive statistics, multivariable logistic regression (α=.05), mediation analysis with nonparametric bootstrapping (500 iterations), and moderation testing. Subsequently, an ABM simulated 2460 agents within a small-world network over 14 days to model behavioral feedback and test 3 interventions: broadcast messaging, behavioral reward, and network rewiring.

RESULTS: The final sample included 2460 adults (mean age 34.46, SD 11.62 years; n=1345, 54.7% female). Higher AI trust was associated with increased odds of delays (odds ratio [OR] 1.09, 95% CI 1.00-1.18; P=.04), with usage frequency partially mediating this relationship (indirect OR 1.24, 95% CI 1.20-1.29; P<.001). Chronic disease status amplified the delay odds (OR 1.42, 95% CI 1.09-1.86; P=.01). The ABM demonstrated a bidirectional trust erosion loop, with population delay rates declining from 10.6% to 9.5% as mean AI trust decreased from 1.91 to 1.52. Interventions simulation found broadcast messaging most effective in reducing delay odds (OR 0.94, 95% CI 0.94-0.95; P<.001), whereas network rewiring increased odds (OR 1.04, 95% CI 1.04-1.05; P<.001), suggesting a “trust polarization” effect.

CONCLUSIONS: This study reveals a nuanced relationship between AI trust and delayed health care-seeking. While trust in AI enhances engagement, it can also lead to delayed care, particularly among patients with chronic conditions or frequent AI users. Integrating survey data with ABM highlights how AI trust and delay behaviors can strengthen one another over time. Our findings indicate that AI health tools should prioritize calibrated decision support rather than full automation to balance autonomy, odds, and decision quality in digital health. Unlike previous studies that focus solely on static associations, this research emphasizes the dynamic interactions between AI trust and delay behaviors.

PMID:41632964 | DOI:10.2196/82170