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PubMed2026

Effectiveness of passive vs. assistive robotic gait training on functional recovery and neuroplasticity post-stroke: A randomized controlled trial.

OBJECTIVE: This study seeks to compare the impacts of various robotic gait training (RAGT) modes on lower limb motor function recovery in stroke patients while exploring the corresponding neural mechanisms. DESIGN: A single-blind, randomized controlled trial. SETTING: Inpatient Rehabilitation Facility. PARTICIPANTS: Forty-eight patients aged 18-80 who had experienced their first unilateral subacute stroke accompanied by walking impairments were included. INTERVENTIONS: Participants were randomly assigned to: (1) assistive mode training, (2) passive mode training, or (3) control group receiving only traditional rehabilitation. Clinical and neurological outcomes were assessed at pre-intervention (T0), and post-2-week intervention (T1). MAIN OUTCOME MEASURES: Outcomes were evaluated using the Fugl-Meyer Assessment for Lower Extremity, Berg Balance Scale, Modified Barthel Index, the Functional Ambulatory Category, and functional near-infrared spectroscopy. RESULTS: Among the 48 patients recruited, significant time effects were observed across all groups in FMA-LE scores (p < 0.001). Notable improvements were detected in the conventional group (MD = 2.69, p＜0.01) and the passive group (MD = 3.67, p < 0.001), with the assistive mode also demonstrating a significant effect (MD = 1.79, p < 0.05). BBS scores improved across all groups; however, no significant differences were noted between the groups (p = 0.11). Similarly, MBI scores showed a significant time effect (p < 0.001), without notable group differences (p = 0.29). CONCLUSION: All training modalities effectively enhanced motor function, balance, and daily living skills in stroke patients. Distinct cortical activation and connectivity patterns were observed between training modalities, which may reflect different neuroplastic mechanisms. These preliminary neural differences may help inform personalized rehabilitation strategies, although no clinical superiority of one mode over another can be concluded from the present data.

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PubMed2026

Comparison between the thoracoabdominal rebalancing (TAR) method and the slow expiratory flow acceleration (SEFA) technique in preterm newborns: protocol for a randomised controlled clinical trial.

INTRODUCTION: Preterm newborns (PTNB) present respiratory immaturity and increased susceptibility to muscle fatigue. The thoracoabdominal rebalancing (TAR) method is a physiotherapeutic intervention developed in Brazil that aims to reorganise the synergy of the thoracoabdominal muscles and reduce the effort of the respiratory muscles, a benefit that is particularly important for PTNB; however, the evidence regarding its effectiveness in this population remains inconclusive. Therefore, this study aims to compare the short-term effects of the TAR method and the slow expiratory flow acceleration (SEFA) technique in improving respiratory distress and peripheral oxygen saturation (SpO2) in PTNB admitted to neonatal intensive care unit (NICU). METHODS AND ANALYSIS: The study will be a randomised, controlled, two-arm, parallel-group, single-blind clinical trial. 68 participants will be randomly assigned to one of the two treatment groups. Group 1 will receive four handling techniques of the TAR method for 10 min, followed by the rhinopharyngeal retrograde clearance with saline instillation (RRC+I) technique. Group 2 will receive the SEFA technique for 10 min, also followed by RRC+I. Primary outcomes are respiratory distress and SpO2. Secondary outcomes are respiratory rate (RR), heart rate (HR), pain, behaviour and diaphragmatic excursion. Assessments will be conducted by a blinded researcher at baseline (T0), immediately after the intervention (T1) and at the 30-minute follow-up (T2). Data will be described using measures of central tendency and dispersion and absolute and relative frequencies. An intention-to-treat analysis will be performed, and intragroup and intergroup comparisons will be assessed using generalised estimating equations (GEE). ETHICS AND DISSEMINATION: The Research Ethics Committee of the Faculty of Health Sciences of Trairi of the Federal University of Rio Grande do Norte approved this study (number 8,055,786). The results will be disseminated through peer-reviewed journal publications, scientific conferences presentations and knowledge translation to the public. TRIAL REGISTRATION NUMBER: This study was registered on Brazilian Registry of Clinical Trials (ReBEC) on 9 January 2026 (RBR-3gbsyc2).

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PubMed2026

Association of cancer antigen 15-3 with distant recurrence in immunohistochemically defined breast cancer subtypes in Canadian Cancer Trials Group MA.32.

BACKGROUND: Circulating levels of cancer antigen (CA) 15-3 have been associated with distant breast cancer recurrence; data on breast cancer subtypes are sparse. We examined associations of CA 15-3 with outcomes across immunohistochemically defined breast cancer subtypes in MA.32. METHODS: A total of 3649 participants with T1-3, N0-1, M0 breast cancer were randomly assigned; 2740 (75.1%) provided blood at entry (mean = 278 days postdiagnosis) and 6 months later. Prognostic associations of baseline and 6-month change in CA 15-3 with distant recurrence-free survival (RFS) were examined in luminal (estrogen receptor-positive and/or progesterone receptor-positive, HER2-negative), triple-negative (estrogen receptor, progesterone receptor, HER2 negative) and HER2-positive (any estrogen receptor, progesterone receptor) breast cancer using Cox proportional hazards models. RESULTS: Mean age was 52 years. Breast cancer was luminal in 1589 (58.7%), triple negative in 655 (24.2%), and HER2 positive in 464 (17.1%) participants. Median follow-up was 96 months. CA 15-3 at study entry was not associated with outcome in any subtype. Rising CA 15-3 at 6 months was associated with poor distant RFS in luminal and triple-negative breast cancer (hazard ratio [HR] per 25% increase = 1.41, P < .0001, and HR = 1.35, P < .0001, respectively). New elevations in CA 15-3 at 6 months were adversely associated with distant RFS in those with luminal or triple-negative breast cancer (HR = 4.14, 95% CI = 2.69 to 6.38; P < .001; and HR = 3.57, 95% CI = 1.59 to 7.99; P = .002, respectively). In HER2-positive breast cancer, CA15-3 was not associated with distant RFS. CONCLUSION: Rising CA 15-3 was associated with reduced distant RFS in luminal and triple-negative breast cancer but not in HER2-positive breast cancer. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT01101438.

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PubMed2026

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

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

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PubMed2026

Effectiveness of a Web-Based Educational eHealth Platform on Women's Health Literacy About Phthalate Exposure: Randomized Controlled Trial.

BACKGROUND: Phthalates are environmental endocrine-disrupting chemicals widely used in plastics, cosmetics, food packaging, and personal care products. Women may experience frequent exposure through everyday consumer and household products. Improving phthalate-related health literacy may support informed exposure-reduction decisions; however, conventional health education provides limited opportunities for repeated, interactive, and individually tailored learning. OBJECTIVE: This randomized controlled trial evaluated the effectiveness of an eHealth educational intervention (Phthalates Free) in improving women's overall and domain-specific phthalate-related health literacy and examined the association between platform engagement and health literacy outcomes. METHODS: A double-blind randomized controlled trial was conducted in the outpatient department of a regional teaching hospital in Taipei, Taiwan. A total of 114 women were randomly assigned to an intervention group (n=58) receiving a 6-month eHealth platform-based education program and a control group (n=56) receiving conventional paper-based education. Assessments were conducted at baseline (T0), 3 months (T1), and 6 months (T2). The Phthalate Health Literacy Scale (10 items; α=.90, content validity index=0.93) measured overall and domain-specific literacy (health care, disease prevention, and health promotion). Longitudinal outcomes were analyzed using generalized estimating equations based on all available observations according to participants' original randomized assignments, with adjustment for waist circumference and pregnancy history. Analysis of covariance (ANCOVA) was used to compare 6-month outcomes after adjustment for baseline scores. Platform engagement and perceived usability were assessed using back-end analytics and the System Usability Scale (SUS). RESULTS: At 6 months, the intervention group showed a significantly greater increase in total health literacy than the control group (+9.93 points, Wald χ²1=17.74; P<.001). Domain analyses revealed significant improvements in health care (+1.52; P=.001), disease prevention (+1.32; P=.001), and health promotion (+1.12; P=.001) domains. ANCOVA confirmed the between-group difference at T2 after adjusting for baseline scores (F1,109=11.43; P=.001; adjusted mean difference=7.15, 95% CI 2.96-11.34). Engagement analysis showed that high-engagement users (n=10) scored significantly higher in overall health literacy (t55=-3.00; P=.004) and all domains than general users. The SUS results (mean 84.7, SD 5.2; n=46, 79.3%) indicated high perceived usability. CONCLUSIONS: The Phthalates Free eHealth educational intervention significantly improved women's overall and domain-specific health literacy over 6 months. Higher platform engagement was associated with better health literacy outcomes. The intervention may serve as a practical adjunct to nurse-led education in outpatient and community settings by providing accessible, continuous, and evidence-based guidance on reducing phthalate exposure.

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PubMed2026

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

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