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PubMed2026

Orofacial Cleft Disparities in American Indian and Alaska Native Populations: A Systematic Review and Meta-Analysis.

ObjectiveTo evaluate the prevalence, access to care, and health outcomes of orofacial clefts (OFCs) among American Indian and Alaska Native (AI/AN) populations through a systematic review and meta-analysis.DesignSystematic review and meta-analysis performed in accordance with PRISMA 2020 guidelines and registered with PROSPERO (CRD420251035364).SettingUS-based population registries, hospital databases, and institutional or community-level retrospective studies involving AI/AN populations.Patients and ParticipantsAI/AN individuals with OFCs compared with non-Hispanic White patients.InterventionsPrimary cleft lip and palate repair, secondary cleft-related procedures, and multidisciplinary cleft care.Main Outcome Measure(s)Prevalence of OFCs, timing of cleft surgery, discharge disposition, access to specialists, and qualitative determinants of disparities.ResultsEighteen studies including more than 1985 AI/AN patients were identified. Meta-analysis of 5 studies estimated a pooled OFC prevalence of 15 per 10 000 live births (95% confidence interval: 5-49), with substantial heterogeneity (I2 = 99.8%). Individual studies reported significantly higher OFC prevalence in AI/AN populations compared to non-Hispanic Whites (odds ratio range: 1.44-2.68). Geographic maldistribution of craniofacial-trained surgeons, increased odds of nonhome discharge, and delayed cleft palate repair were consistently observed barriers. Qualitative analyses highlighted structural inequities, perceived racism, and lack of culturally responsive care as major contributors to disparities.ConclusionsAI/AN populations face a disproportionately high burden of OFCs alongside structural barriers to timely, culturally competent care. Addressing these disparities requires community-engaged, multidisciplinary interventions that improve geographic access and integrate culturally responsive approaches to care.

Humans↗

PubMed2026

A Dynamic Nomogram to Predict Metabolic Dysfunction-Associated Fatty Liver Disease in Patients with Metabolic Syndrome.

BACKGROUND: Metabolic syndrome (MetS) involves multiple metabolic disorders. This study aimed to identify high-risk populations for metabolic dysfunction-associated fatty liver disease (MAFLD) in patients with MetS and to establish a dynamic predictive nomogram. METHODS: A total of 627 patients with MetS from six regions in Zhejiang Province were enrolled and categorized into MAFLD and non-MAFLD groups, then randomly assigned to training and validation sets at a ratio of 7:3. Independent predictors of MAFLD were identified using least absolute shrinkage and selection operator regression and multivariable logistic regression analyses. These predictors were then used to construct a dynamic nomogram. RESULTS: A total of 627 patients with MetS were included in the final analysis, of whom 77.0% (483/627) were diagnosed with MAFLD. Multivariable logistic regression analysis identified body mass index (BMI), waist circumference (WC), total cholesterol (TC), alanine aminotransferase (ALT), MetS-defined dysglycemia, and education level as independent risk factors for MAFLD. MetS-defined dysglycemia showed the highest odds ratio (OR) for MAFLD development [OR = 1.87, 95% confidence interval (CI): 1.07-3.29]. Although the number of MetS components and the metabolic syndrome score were significantly associated with MAFLD in univariate analysis, they were not independently associated with MAFLD in the multivariate model. A dynamic nomogram for predicting MAFLD risk in patients with MetS was developed and internally validated. The area under the receiver operating characteristic curve was 0.834 (95% CI: 0.787-0.880) in the training set and 0.839 (95% CI: 0.771-0.899) in the validation set, indicating strong predictive performance. Bootstrap internal validation demonstrated good agreement between predicted and observed outcomes in calibration curves. Decision curve analysis further indicated favorable clinical applicability of the nomogram. CONCLUSION: BMI, WC, TC, ALT, MetS-defined dysglycemia, and education level are independent risk factors for MAFLD. A dynamic nomogram for predicting MAFLD risk in patients with MetS was successfully developed and validated.

Humans↗

PubMed2026

Development and Validation of a Predictive Model for Identification of Cognitive Impairment Risk in Older Adults with Subjective Cognitive Decline：A Longitudinal Study.

BACKGROUND: Subjective cognitive decline (SCD) is a transitional state between objective cognitive impairment and cognitively intact mental status, providing a critical window for implementing preventive interventions to delay objective cognitive decline. AIMS: We aimed to develop a predictive model for SCD progression in older adults with mild cognitive impairment (MCI). This model will facilitate the identification of risk factors and establishment of targeted interventions for community-based SCD management. METHODS: Data from the China Health and Retirement Longitudinal Study (CHARLS) was utilized in this study, extracting 18 indicators. Potential predictors selected through univariate Cox regression and LASSO regression analyses were sequentially incorporated into a multivariable Cox regression model. A nomogram was constructed to establish a predictive model. Model validation encompassed Area Under Curve (AUC) metrics for discriminative capacity, complemented by quantitative assessments using calibration curve analysis for precision verification and decision curve analysis (DCA) for clinical utility evaluation. RESULTS: A total of 1099 older adults with SCD were included in the final analysis, of whom 114 (10.3%) developed MCI. Multivariable Cox regression identified residence, marital status, educational level, social participation, gait speed, and baseline cognitive function. The model demonstrated time-dependent AUC values of 0.885, 0.830, 0.839, and 0.836 in the training set when evaluating discriminative capacity at 2-, 4-, 7-, and 9-year, respectively. The predictive model showed excellent predictive ability according to AUC, calibration curve, and DCA. CONCLUSIONS: A predictive model was created to estimate the risk of developing MCI in older individuals with SCD, offering clinician-actionable intervention benchmarks for preventive care.

Humans↗

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

Process evaluation of a nurse-led transitional care model (Cardiolotse) within a randomized controlled trial aiming to improve care coordination for patients with cardiovascular diseases in Germany.

BACKGROUND: Patients with higher age suffering from cardiovascular disease discharged from hospital are at greater risk of readmission within 30 days. We evaluated an innovative care program providing post-discharge support and helping patients to navigate through the healthcare system. This paper reports the findings of the process evaluation of the randomized controlled trial Cardiolotse, a nurse-led transitional care model improving care coordination for patients with cardiovascular diseases in Germany. METHODS: A process evaluation, following the guidelines of the Medical Research Council (MRC) Framework, was performed. Semi-structured interviews with all relevant target groups were conducted to gain more insight about implementation processes. Questionnaires and medical records were used to explore mechanisms of impact and understand how change was produced in the intervention. Qualitative data were analysed using content analysis with deductive and inductive categories. Descriptive statistics and subgroup analyses were utilized to explore quantitative data. RESULTS: Overall, the designed training programme was perceived positively by the study nurses, so called Cardiolotsen (CLs). Patients receiving support by the CLs reported positive satisfaction ratings. Interactions between CLs and patients were reported as trustworthy and reliable. A total of approximately 12,500 contacts were made over the course of the intervention. However, changes in satisfaction scores between intervention and control groups in terms of medical treatment or the interaction between medical health providers involved in the treatment could not be determined. Furthermore, data suggested reach issues with respect to office-based physicians, as regular CL contact could not be achieved with 90% of the participating general practitioners and cardiologists. CONCLUSIONS: The CLs served as an important source of support for the participating patients throughout the intervention. At regular intervals, they checked a patient's health status and their adherence to therapies after discharge. However, the process evaluation identified cross-sectoral communication and information exchange between CLs and office-based physicians as an implementation challenge. TRIAL REGISTRATION: The study was retrospectively registered at German Clinical Trial Register, http://www.drks.de/DRKS00020424 (Trial Registration Number DRKS00020424) on 18 June 2020.

Humans↗

PubMed2026

Meta-PseU: A meta-classifier for robust prediction of RNA pseudouridine modification sites from long sequences.

BACKGROUND AND OBJECTIVES: Pseudouridine (Ψ) represents one of the most abundant and conserved RNA modifications. Ψ provides an additional hydrogen-bond donor that enhances RNA structural stability and modulates translation. It participates in diverse biological processes, including RNA-protein interactions, splicing, translational control, and stress responses. Aberrant pseudouridylation is implicated in cancer, neurodegenerative disorders, and autoimmune diseases. Despite its biological importance, experimental identification of Ψ sites remains time-consuming and costly, limiting the feasibility of transcriptome-wide profiling. Computational approaches have therefore become essential complements to experimental techniques. However, state-of-the-art machine-learning and deep-learning predictors often suffer from limited generalizability due to small training datasets. To overcome these issues, we aim at constructing new long-sequence datasets and developing a novel Ψ site predictor. METHODS: New long-sequence datasets were constructed as benchmarks for RNA Ψ-site prediction. The Ψ modification sites in RMBase 3.0 were mapped to the reference genomes across three species of human, mouse, and yeast, and the RNA sequences with a length of 201 were generated by extending the upstream and downstream from the mapped, central sites. To eliminate sequence redundancy, the sequences were clustered using CD-HIT with a 70% sequence identity threshold. We developed Meta-PseU, a logistic regression-based meta-classifier that considered 118 machine learning and deep learning classifiers. The datasets and programs are freely accessible at https://github.com/kuratahiroyuki/MetaPseU. RESULTS: By optimizing model configuration, we proposed the Meta-PseU model stacking 32 machine learning and deep learning classifiers out of 118 classifiers. Meta-PseU substantially improved model generalizability, overcoming a key limitation of existing approaches. It greatly outperformed state-of-the-art predictors and achieved increasing accuracy with increasing sequence length. CONCLUSIONS: Long-sequence datasets were newly constructed as benchmarks for RNA Ψ-site prediction. Meta-PseU offers a new framework for robust Ψ-site identification by using long sequences.

Pseudouridine↗

PubMed2026

Characterizing Submental Neuromuscular Activity of Swallowing Rehabilitation: An Electromyographic Evaluation of Rehabilitative Maneuvers in Healthy Adults.

PURPOSE: The effortful swallow (ES), the Mendelsohn maneuver (MM), and isometric tongue presses (TPs) are widely used swallowing maneuvers/exercises to improve elements of swallowing, such as muscle strength and biomechanics. However, the underlying neuromuscular mechanisms of these exercises remain unclear, potentially limiting our ability to specify treatment targets and improve treatment efficacy. This study aimed to compare submental neuromuscular activation patterns during the ES, MM, TPs, and typical swallows in healthy young and older adults. METHOD: As part of a larger randomized crossover validation study, 60 healthy adults (30 young and 30 older) completed typical swallows and three maneuvers using a wearable submental surface electromyographic (sEMG) system (i-Phagia). Outcome variables included (a) normalized mean sEMG amplitude and (b) time to peak sEMG amplitude. Linear mixed models were used to examine effects of task, age, and sex on both outcomes. RESULTS: Normalized mean amplitude was significantly different across tasks. Post hoc pairwise comparisons confirmed that all three maneuvers produced higher normalized mean sEMG amplitude than typical swallows, with the ES eliciting the highest amplitude across age groups. Time to peak amplitude differed significantly across tasks, with typical swallows requiring the shortest time to reach peak amplitude, followed by the ES, MM, and TP. CONCLUSIONS: The ES required the highest neuromuscular effort with the shortest time to reach peak amplitude, suggesting its potential for targeting submental muscle power. Typical swallows required the least neuromuscular effort with the shortest time to reach peak amplitude, suggesting their potential for training submental muscle speed. The MM and TP may also improve submental muscle strength; however, given their temporal requirements (longer durations), they may be more beneficial for targeting coordination and endurance, though more research in this area is warranted. These findings underscore the importance of task-specific neuromuscular profiling to inform mechanism-based swallowing rehabilitation. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.32948549.

Humans↗

PubMed2026

A systematic approach to standardizing the visual appearance of endometriotic lesions for artificial intelligence recognition.

INTRODUCTION: Numerous studies have shown that the diagnostic performance and reproducibility of visual recognition of endometriosis during laparoscopy are poor. The use of artificial intelligence (AI) seems relevant for exhaustive lesion recognition. Standardization of the visual classification of lesions, in the form of an ontology, is an essential prerequisite to enable medical experts to annotate surgical data consistently and subsequently allow engineers to train and build an artificial intelligence tool for endometriosis recognition. MATERIAL AND METHODS: A systematic search was conducted in the MEDLINE (via PubMed), EMBASE, and the Cochrane Library databases up to May 2022, aiming to identify studies describing the laparoscopic visual appearance of superficial endometriosis, endometriomas, and deep infiltrating endometriosis. The accumulated data in the literature concerning the visual appearance of the different forms of endometriosis were used to create an ontology that could be used for artificial intelligence applications. RESULTS: Out of 932 articles screened, 35 studies were selected based on the inclusion criteria of human subjects with histologically confirmed endometriosis lesions visualized via laparoscopy. The selected studies were reviewed to develop a visual ontology of endometriosis lesions observed via laparoscopy. The lesions were categorized into 4 classes and further subdivided into 11 subclasses: superficial (black, red, white, or subtle), adhesions (dense or filmy), deep (obliteration, retraction, or deformation), and ovarian (endometrioma or chocolate fluid). The positive predictive value (PPV) varied across lesion types: black lesions (PPV 47%-97%), red lesions (PPV 33%-100%), white lesions (PPV 20%-81%), and ovarian endometriosis (PPV 42%-98%). Nonspecific lesions such as adhesions (PPV 16%-50%) and subtle superficial lesions (PPV 0%-67%) presented lower PPVs. Deep endometriosis lesions, often buried within organs, required indirect signs (obliteration, retraction, deformation) for identification. CONCLUSIONS: The visual ontology proposed in this systematic search could facilitate the detection and classification of endometriosis lesions using artificial intelligence. This study highlights the challenges of reaching a consensus on lesion recognition and classification in AI projects due to the diverse visual presentations of endometriosis.

Humans↗

PubMed2026

Risk factors and management strategies for needle disengagement from the visual field in pediatric robot-assisted laparoscopic pyeloplasty.

OBJECTIVE: This study aimed to identify risk factors for suture needle disengagement from the visual field during pediatric robot-assisted laparoscopic pyeloplasty (RALP) and propose effective strategies for prevention and management. METHODS: A retrospective cohort study analyzed clinical data from 339 pediatric patients who underwent RALP for ureteropelvic junction obstruction (UPJO) at a single institution between August 2017 and December 2020. Patients were categorized based on the occurrence of needle disengagement from the visual field. Various patient demographics and surgical procedural factors were evaluated. Univariate and multivariate logistic regression, along with LASSO regression, identified independent risk and protective factors. RESULTS: Needle disengagement occurred in 38 (11.21%) of 339 cases. Multivariate logistic regression identified five independent risk factors for needle disengagement: use of a 3-mm auxiliary trocar (OR = 4.69, 95% CI: 1.98-12.53, P < 0.001), non-standard needle holder use (OR = 2.32, 95% CI: 1.04-5.18, P = 0.038), unshaped suture needles (OR = 3.16, 95% CI: 1.44-7.19, P = 0.005), simultaneous use of ≥2 intra-abdominal sutures (OR = 2.46, 95% CI: 1.15-5.48, P = 0.023), and clamping the needle shank during withdrawal (OR = 3.42, 95% CI: 1.40-8.21, P = 0.006). Conversely, sufficient assistant experience (>10 cases) was identified as a protective factor (OR = 0.39, 95% CI: 0.18-0.88, P = 0.021). CONCLUSION: Suture needle disengagement from the visual field during pediatric RALP is associated with specific technical and instrumental factors. Implementing targeted strategies-such as mandating specialized needle holders, preoperative needle shaping, a single-needle workflow, prioritizing clamping the suture thread over the needle shank during withdrawal, and ensuring adequate assistant training-has the potential to significantly reduce significantly mitigate the risk of needle loss and enhance overall surgical safety in pediatric RALP.

Humans↗

PubMed2026

Deimplementation of inappropriate feeding practices in early care and education: a Hybrid Type 3 cluster-randomized trial.

BACKGROUND: The science of deimplementation-reducing harmful or ineffective practices-has focused almost exclusively on clinical prescribing, with no studies conducted in community or educational settings. Early care and education (ECE) settings offer a strategic venue for shaping eating behaviors, with children consuming up to 500 meals annually in these environments. However, ECE educators routinely use feeding practices that undermine self-regulation, including pressuring children to eat, rushing mealtimes, and offering food as reward. These practices contribute to food aversions, diminished self-regulation, and obesity risk. METHODS: We will conduct a Hybrid Type 3 cluster-randomized trial evaluating a co-designed deimplementation strategy package (WISE Words) across 88 ECE sites in Arkansas and Louisiana. Sites will be randomized 1:1 to WISE Words or usual practice, with usual practice sites receiving the intervention after two years (waitlist design). WISE Words includes six strategies: dynamic training using improvisation methods, peer learning collaboratives with goal setting, external facilitation, audit and feedback, environmental reminders, and tailored educational materials. The primary outcome is de-adoption of inappropriate feeding practices measured via direct mealtime observation (Table Talk). Secondary outcomes include adoption of evidence-based practices, acceptability, appropriateness, and sustainability at 12- and 24-months post-intervention. Child outcomes include Body Mass Index, skin carotenoid levels (Veggie Meter) willingness to try new foods (observed) and food neophobia (teacher and caregiver report). An explanatory sequential mixed methods design will test mechanisms of change derived from the Implementation Trust Building Theory of Change examining whether trust mediates strategy effects on outcomes. DISCUSSION: This trial extends deimplementation science into community settings by targeting culturally embedded behavioral practices rather than clinical prescribing behaviors. Results will inform approaches to shifting entrenched practices in ECE and similar settings while testing trust as a deimplementation mechanism. Sustainability assessments will address a notable gap, as few studies have examined whether deimplementation effects persist. TRIAL REGISTRATION: NCT07101321, July 20, 2025.

Humans↗

PubMed2026

Effectiveness of Mobile-Delivered Exercise and Yoga Programs on Depressive Symptom Reduction in Employees: Randomized Controlled Trial.

BACKGROUND: Mental health challenges such as stress and depression are prevalent among employees. Mobile health platforms that deliver exercise or yoga interventions offer a promising approach to improve mental health outcomes in this population. OBJECTIVE: This study aimed to assess the effectiveness of 12-session adaptive moderate-intensity exercise and yoga programs delivered via a motion-detecting digital platform in reducing stress and depressive symptoms among employees. METHODS: This was an unblinded, 3-arm, parallel-group, randomized controlled trial conducted at Seoul National University Bundang Hospital and Boramae Medical Center between November 2023 and January 2024. Eligible participants were full-time employees. Seventy-five participants were randomly assigned to an exercise, a yoga, or a cognitive behavioral therapy-based self-care control group using computer-generated randomization. The exercise and yoga groups engaged in motion-detecting, adaptive physical activity training, whereas the control group accessed mobile-based, self-directed stress management educational materials. The intervention was largely automated, with no individualized therapeutic guidance provided. Allocation was concealed until trial entry. All recruitment and outcome assessments were conducted in person at the hospitals. The primary outcomes were perceived stress and depressive symptoms, whereas the secondary outcomes included posttraumatic stress, insomnia severity, cognitive stress response, occupational stress, and burnout. Physiological outcomes were assessed using heart rate variability and electroencephalography. Measurements were collected at baseline, immediately after the intervention, and at 4-week follow-up. Data were analyzed using a multivariate linear model to evaluate the main effects of time, group, and time×group interactions. RESULTS: Of the 75 randomized participants (exercise: n=24, 32%; yoga: n=25, 33.3%; and control: n=26, 34.7%), 71 (94.7%) who completed at least 9 of the 12 sessions (≥40 min each) were included in the outcome analysis (exercise: n=21, 29.5%; yoga: n=24, 33.8%; and control: n=26, 36.6%). For the coprimary outcomes, the group×time interaction for depressive symptoms (Patient Health Questionnaire-9) approached but did not reach the Bonferroni-corrected threshold (F4,136=2.71; P=.03; adjusted α=.025); however, planned pairwise comparisons revealed significantly greater improvement in the yoga group compared to the control group at 4-week follow-up (β=-3.67; adjusted P<.001). For the Perceived Stress Scale, the interaction was not significant (P=.29), although a significant main effect of time (P<.001) indicated overall stress reduction across all groups. For secondary outcomes, a significant group×time interaction was found for the Cognitive Stress Responses Scale (P=.003), indicating differential trajectories of improvement. The yoga group showed a consistent linear decrease, whereas the exercise group showed immediate but less sustained gains. CONCLUSIONS: Digitally delivered adaptive yoga programs demonstrated superior and sustained improvements in depressive symptoms and Cognitive Stress Responses Scale scores compared with the active cognitive behavioral therapy-based self-care control group. However, the exercise program showed more modest and less sustained effects, warranting further investigation using larger samples.

Adult↗

PubMed2026

Multimodal alignment improves generalizability of genomic biomarker prediction in computational pathology.

Computational pathology models that use digitized histopathology whole-slide images have the potential to become a cost-effective and scalable alternative to molecular assays for the prediction of genomic biomarkers, a key task in precision oncology. However, as new genomic biomarkers are discovered or quantified, large, labeled datasets must be prospectively collected to train new models. To address this challenge, we developed multimodal alignment for biomarker learning and generalization (MARBLE), a multimodal contrastive pretraining strategy that integrates structured biomarker knowledge into representation learning of histopathology images. MARBLE aligns histopathology-derived representations with representations of genomic biomarkers generated by a large language model (LLM) and a protein language model (PLM). This biologically informed alignment enables data-efficient generalization to novel, out-of-distribution biomarkers. Using the MSK-IMPACT cohort of over 40,000 patients across multiple biomarker panel versions, we design experiments grounded in real-world data to demonstrate the value of our proposed approach.

CP: computational biology↗

PubMed2026

Exercise Snacks Are Feasible to Perform in the Real World and Improve Physical Capacity for Adults Living With Non-Insulin Treated Type 2 Diabetes: A Randomised Trial.

AIMS: To investigate the feasibility and preliminary efficacy of a 12-week remotely-delivered exercise snacks (ES) intervention in adults with type 2 diabetes. MATERIAL AND METHODS: Insufficiently active adults with type 2 diabetes (N = 69; 46 females; mean age ± SD: 58 ± 11 years) were randomised to an ES or mobility/stretching comparator group (CON), which involved 4 × 1-min bouts of either vigorous or low intensity exercise, respectively, on ≥ 5 days/week. The primary outcome was feasibility based on adherence. Secondary outcomes included exercise enjoyment (1-7 scale), rating of perceived exertion (RPE; 0-10 scale), heart rate (HR), haemoglobin A1c (HbA1c), blood biomarkers of cardiometabolic health, 30-s sit-to-stand capacity, grip strength, estimated maximal oxygen uptake, and anthropometrics. RESULTS: Weekly adherence (estimated marginal mean [95% confidence interval]: 18 bouts [16-21] for both groups; p = 0.99) and total enjoyment (ES: 4.5 [4.1-4.8] vs. CON: 4.3 [4.0-4.7]; p = 0.64) were high and not different between groups. Despite higher RPE (5.7 [5.4-6.1]) and peak HR (73 [70-77] % of age-predicted HR maximum) in ES versus CON (2.0 [1.7-2.4] and 61 [58-64] % of age-predicted HR maximum, respectively) (all p < 0.001), there were no between-group differences in the change in any secondary outcome (all p > 0.05) except for greater sit-to-stand capacity in ES after training (between-group effect estimate [95% confidence interval]: 1.9 repetitions [0.3-3.4]; p = 0.02). CONCLUSIONS: Exercise snacks were feasible to perform in the real world and improved sit-to-stand capacity to a greater extent than CON in adults living with type 2 diabetes. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT06407245.

Aged↗

PubMed2026

A Meta-learning-driven strategy for adulteration detection in sweet potato starch and vermicelli using Raman spectroscopy.

To address the widespread adulteration of sweet potato starch and its vermicelli with cheaper starches and overcome conventional supervised learning's dependency on large labeled datasets, this study developed a few-shot discrimination method integrating Raman spectroscopy with meta-learning. We constructed a meta-learning framework using cassava- and wheat-adulterated sweet potato starch as the source domain for training, with potato-adulterated sweet potato starch and cassava-adulterated sweet potato vermicelli as two target domains for testing. Raman spectra showed high consistency between sweet potato vermicelli and its raw starch, laying the foundation for cross-domain detection. Testing yielded comprehensive classification accuracies of 95.33% and 98.00% for the two target domains, significantly outperforming SVM, RF, and CNN (max. 85.24%). This approach effectively identifies subtle starch variety differences in complex adulteration, providing novel food quality inspection solutions and verifying the feasibility of raw material-to-finished product cross-domain detection.

Ipomoea batatas↗

PubMed2026

Effects of exercise on aerobic capacity in people with prehypertension or hypertension: a systematic review and meta-analysis of randomized controlled trials.

This study aimed to quantify the effects of exercise on aerobic capacity in people with prehypertension or hypertension and to identify exercise prescription parameters that optimize improvements. A comprehensive search was conducted in PubMed, Web of Science, Embase, Cochrane Library, and Scopus from inception to 24 October 2025. Data were pooled using standardized mean differences (SMDs) with 95% confidence intervals (CI). Fifteen studies met the inclusion criteria. Exercise significantly improved aerobic capacity in people with prehypertension or hypertension (SMD = 0.88; 95% CI: 0.61-1.15; P  < 0.00001), with multicomponent training demonstrating superior efficacy. Exploratory subgroup analyses suggest that longer programs (≥12 weeks), lower frequency (<3 sessions/week), 60-min sessions or longer, total weekly exercise less than 180 min, and professional supervision may be associated with better outcomes.

Humans↗

PubMed2026

Impact of a multimodal prehabilitation program on postoperative cognitive dysfunction: a single-center randomized controlled trial.

BACKGROUND: Postoperative cognitive dysfunction (POCD) is a frequent complication after cardiac surgery. Exercise-based prehabilitation may enhance functional reserve and reduce vulnerability to perioperative cerebral insults. We hypothesized that multimodal prehabilitation reduces POCD 3 months after cardiac surgery. METHODS: This prespecified substudy of a single-center randomized controlled trial (NCT03466606) included patients aged ≥50 years undergoing elective coronary artery bypass grafting and/or valve surgery. Participants were randomized 1:1 to 4-6 weeks of multimodal prehabilitation (exercise training, nutritional support, and psychological support) or standard preoperative care. Cognitive function was assessed at baseline and 3 months postoperatively using an age- and education-adjusted neuropsychological battery. POCD was defined as performance ≥1.5 standard deviations below normative values in at least 2 cognitive tests, excluding the Mini-Mental State Examination. Logistic regression analyses were performed to evaluate factors associated with POCD. RESULTS: Of 160 participants screened from the parent trial, 134 met eligibility criteria for the substudy and were randomized; 116 completed 3-month follow-up (prehabilitation n = 53; control n = 63). POCD occurred in 29 patients (25%), including 15/53 (28%) in the prehabilitation group and 14/63 (22%) in controls (odds ratio [OR] 1.37, 95% confidence interval [CI] 0.54-3.50, P = 0.52). In multivariable analysis, preoperative cognitive impairment was independently associated with POCD (OR 13.28, 95% CI 4.06-43.41, P < 0.001), whereas prehabilitation was not (OR 1.09, 95% CI 0.35-3.45, P = 0.877). Higher physical activity levels at 3 months were associated with lower odds of POCD (OR 0.97, 95% CI 0.95-1.00, P = 0.047). CONCLUSIONS: In this randomized controlled trial, a 4-6-week multimodal prehabilitation program did not reduce postoperative cognitive dysfunction 3 months after cardiac surgery. Although the intervention did not achieve measurable cognitive protection, the observed association between postoperative physical activity levels and postoperative cognitive dysfunction warrants further investigation.

Humans↗

PubMed2026

Final-year nursing students' clinical practice experiences: a reflection study.

OBJECTIVES: This study aimed to explore the most impactful clinical practice experiences of final-year nursing students and the future-oriented actions developed in response to these experiences. METHODS: A retrospective descriptive qualitative design was used. Following reflection training in the internship practice course, 134 final-year nursing students were asked to describe the experience that affected them most during clinical practice. A total of 123 written reflections were analyzed using content analysis. RESULTS: Three themes emerged: near-miss events, incivility behaviors, and positive preceptoring roles. Negative experiences were mainly related to patients, relatives, and nurses and often led students to feel fear and inadequacy. Students reported action plans focused on effective communication, safe patient care, and becoming positive role models. CONCLUSIONS: These findings highlight the importance of supportive clinical learning environments and positive professional socialization during the transition from student to nurse. IMPLICATIONS FOR INTERNATIONAL AUDIENCE: Nursing students worldwide may encounter incivility and near-miss events during clinical practice, potentially adversely affecting their learning experiences and professional development.

Humans↗

PubMed2026

Determinants of Nonspecific Response to Treatment in Randomized Controlled Trials of Major Depressive Disorder: A Narrative Review.

The design, conduct, and interpretation of double-blind randomized placebo-controlled clinical trials in major depressive disorder (MDD) are complicated by determinants of nonspecific response to treatment (NSRT). This narrative review provides a comprehensive overview of the determinants of NSRT in randomized controlled trials (RCTs) for MDD, including the placebo effect, factors related to measurement of the primary endpoint, the inclusion of misdiagnosed patients, the relapsing-remitting course of MDD, and factors related to functional unblinding. Potential strategies to reduce the impact of the determinants of NSRT and to improve the interpretation of RCT outcomes in MDD are also summarized. These strategies include use of centralized rating and standardized rater training, independent diagnostic confirmation, optimized site selection, minimizing financial incentives, exclusion of subjects participating in multiple clinical trials, exclusion of patients with unstable major depressive episode trajectories, and use of active placebo and alternative trial designs. Uniformity among experts in the definitions of determinants of NSRT and related concepts, as well as in strategies to address them, may facilitate progress in the development of novel treatments for MDD.

Humans↗