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PubMed2026

Post-intervention effectiveness of a computerized personalized cognitive stimulation program adapted according to cognitive reserve in older adults without cognitive impairment in Primary Care: A randomized clinical trial.

BACKGROUND: Cognitive reserve may influence responsiveness to cognitive interventions, yet it is rarely used to tailor computerized stimulation. OBJECTIVE: To evaluate the effectiveness of a computerized cognitive stimulation program personalized according to cognitive reserve on cognition, reserve-related activities, and digital competence in community-dwelling older adults without cognitive impairment in Primary Care. METHODS: In this randomized clinical trial, 102 adults aged ≥65 years with normal cognitive performance were recruited from three primary care centers in Zaragoza, Spain, and stratified by cognitive reserve level before random allocation to intervention or control. The intervention comprised digital literacy sessions followed by 8 weeks of home-based computerized cognitive stimulation tailored to participants' cognitive reserve profiles and life history. Controls received a single group-based health education session focused on maintaining everyday cognitive activity. Outcomes were assessed at baseline and post-intervention using global cognition (MEC-35), the Cognitive Reserve Questionnaire, the Mobile Device Proficiency Questionnaire-16, and domain-specific neuropsychological tests. A total of 100 participants completed the final evaluation and were included in complete-case analyses. RESULTS: Compared with controls, the intervention group showed greater adjusted post-intervention improvements in global cognition (MEC-35 between-group difference: 1.8 points) and several cognitive measures, including temporal orientation, calculation, attention, praxis, verbal fluency, processing speed, executive functions, and verbal learning. CRQ scores and digital competence also improved, with small-to-large effect sizes. CONCLUSIONS: A computerized cognitive stimulation program adapted according to cognitive reserve appears feasible in Primary Care and may improve cognition, engagement in reserve-related activities, and digital competence in older adults without cognitive impairment.

Humans↗

PubMed2026

Analysis of deep learning techniques in computer-aided diagnosis for meniscus injuries: a systematic literature review.

Meniscus informatics is a growing subject of study in the healthcare industry. One of the major hindrances to the healthcare system's transformation is obtaining knowledge and meaningful information from complicated, high-dimensional and diverse sources. Modern biomedical research, for instance, has seen an increase in the use of complex, dissimilar, poorly documented, and generally unstructured electronic health records, imaging, sensor data and text, even after many current techniques have been used to extract more robust and useful elements from the data for analysis. New efficient standards for building end-to-end learning models from complex data are therefore needed. Therefore, the current study aims to examine the most recent research on the use of deep learning techniques for diagnosing meniscus tears and recommend creating comprehensive and meaningful interpretable structures that might benefit the healthcare industry. We also draw attention to shortcomings and the need for better technique development, and we provide new perspectives about this exciting new development in the field.

Humans↗

PubMed2026

Changes in hippocampal functional connectivity and volume associated with cognitive improvement and decline in amnestic mild cognitive impairment following computerized cognitive training.

BACKGROUND: The hippocampus influences the outcomes of amnestic mild cognitive impairment (aMCI) and undergoes different changes during the cognitive decline or recovery of aMCI compared to elderly individuals with normal cognition, which may reveal disease-dependent neurodegeneration or plasticity. We first aimed to investigate the hippocampal changes associated with cognitive changes in aMCI using a combined case-control study design. METHODS: In total, 50 aMCI individuals and 50 healthy controls (HCs) were recruited in Shenyang, China, and separately randomized into training and control groups: aMCI training group, aMCI no training group, HC training group, and HC no training group. The aMCI and HC training groups received computerized cognitive training (CCT) thrice weekly for 12 weeks. Cognitive assessments and MRI data were collected at baseline and follow-up. RESULTS: The primary outcome was significant CCT×diagnosis interaction effect on the change in cognitive performance as measured by clock drawing test (CDT) scores (F = 4.322, P = 0.041); this interaction was driven by CCT specifically in aMCI (F = 4.465, P = 0.038). Significant CCT×diagnosis interaction effects of right-hippocampal FC changes were observed in the bilateral precuneus/cuneus (Pvoxel<0.05) driven by CCT in aMCI (F = 5.429, P = 0.023), and in the left superior temporal gyrus/middle temporal gyrus (STG/MTG, Pvoxel<0.05), driven by CCT of only in HCs (F = 6.587, P = 0.013). A significant interaction effect of left-hippocampal FC changes were observed in the right triangular part of the inferior frontal gyrus (IFGtriang, Pvoxel<0.05), driven by CCT in aMCI and HCs (F = 6.550, P = 0.013; F = 7.097, P = 0.010). No significant interaction effect on the change in hippocampal GMV was noted (P > 0.05). CONCLUSION: CCT can improve the visuospatial ability of aMCI, which is reflected by the CDT scores. CCT can alter hippocampal FC in the bilateral precuneus/cuneus, the right IFGtriang, and the left STG/MTG. The hippocampal GMV is difficult to change in both HCs and aMCI during the cognitive decline. REGISTRATION NUMBER: ChiCTR1900026849. DATE OF REGISTRATION: 24 October 2019 NAME OF TRIAL REGISTRY: Chinese Clinical Trial Registry (ChiCTR).

Humans↗

PubMed2026

A STORM-based protocol for nanoscale imaging and quantitative analysis of protein-associated and phospholipid-associated structures in natural rubber.

Stochastic Optical Reconstruction Microscopy (STORM) enables nanoscale mapping of molecular components beyond the diffraction limit; however, its reproducible implementation in hydrophobic polymer matrices remains challenging because fluorescence-labeling specificity, fluorophore photoswitching, three-dimensional localization, chromatic registration, and quantitative image analysis must be carefully controlled. This protocol presents a standardized experimental workflow for dual-color labeling, astigmatism-based three-dimensional STORM acquisition, and quantitative analysis of protein-associated and phospholipid-associated structures in natural rubber (NR). The workflow covers sample pretreatment, Cy5 NHS ester labeling of protein-associated primary amines, DiI labeling of phospholipid-rich domains, STORM imaging-buffer preparation, three-dimensional single-molecule localization, dual-channel registration, generation of standardized xy projections, aggregate-size analysis, and projected lateral spatial correlation assessment. Reproducibility is supported by defined acquisition and localization criteria, three independent sample preparations with at least five fields of view analyzed per condition, and unlabeled, single-color, dye-only matrix, and processing-associated Cy5 controls. Mean lateral localization precisions of 11.8 ± 2.3 nm for Cy5 and 13.5 ± 2.9 nm for DiI were obtained, while two-dimensional Fourier ring correlation analysis of the xy projections yielded effective lateral image resolutions of approximately 25 and 28 nm, respectively. Image-based particle segmentation and localization-coordinate-based density-based spatial clustering of applications with noise (DBSCAN) were applied to standardized xy projections as complementary quantitative approaches. Application of the protocol to untreated, centrifuged, and protease-treated NR samples demonstrated treatment-associated changes in the detected abundance and projected size distributions of protein- and phospholipid-associated aggregates, together with a non-monotonic change in their projected lateral spatial correlation. These observations describe alterations in nanoscale organization but do not, by themselves, establish stable protein-phospholipid complex formation. Unlike previous studies that primarily demonstrated the feasibility of STORM imaging in rubber materials, the principal contribution of this work is an end-to-end, step-by-step protocol incorporating defined controls, three-dimensional localization, image-quality metrics, chromatic-registration procedures, and complementary quantitative-analysis pipelines for non-expert users. The workflow may be adaptable to other hydrophobic polymers and soft-material systems after appropriate optimization and validation.

Rubber↗

PubMed2026

Artificial neural network data fusion-mediated dual-mode sensor based on Fe3O4@PdIr for Salmonellatyphimurium detection in food.

Salmonella Typhimurium (S. typhimurium) is a major foodborne pathogen that poses a serious threat to public health. In this study, a colorimetric/electrochemical dual-mode biosensor assisted by artificial neural network (ANN) was developed for the sensitive detection of S. typhimurium. Fe3O4@PdIr nanocomposites with enhanced peroxidase-like activity and electrochemical performance were prepared and conjugated with an aptamer specific to S. typhimurium to obtain Fe3O4@PdIr-Apt. Through the sandwich binding of Fe3O4@PdIr-Apt and Apt to the target, the nanocomposites were attached to microplates or Au electrodes, thereby generating colorimetric and electrochemical signals. The ANN model deeply resolved the complex nonlinear relationship between the dual signals, enabling mutual correction and ultimately performing data fusion to output a single detection result, which significantly reduced the mean square error while improving detection sensitivity and reliability. This sensor exhibited a wide linear range of 2.7-2.7 × 108 CFU/mL and a low detection limit of 1.66 CFU/mL. Additionally, this method was successfully applied to the detection of S. typhimurium in pork and milk, with a recovery rate of 95.19% ∼ 104.07%. It indicated that the constructed sensor holds great practical potential for S. typhimurium detection.

Neural Networks, Computer↗

PubMed2026

Metagenome-scale modeling to assess microbiome metabolic complementarity for precision microbiota transplantation therapies.

Fecal microbiota transplantation (FMT) holds therapeutic promise beyond recurrent Clostridioides difficile infection, but clinical outcomes remain unpredictable and donor-selection strategies remain limited, in part because the role of donor‒recipient metabolic interactions in shaping the post-FMT community remains poorly understood. Here, we leverage metagenome-scale metabolic modeling to quantify metabolic niche complementarity between donor and recipient microbiomes and predict post-FMT community composition. Using MICOM-derived metabolic models, we show that donor genomes whose metabolic flux profiles are more dissimilar from the recipient community colonize at significantly higher rates in a murine FMT model. In a human IBS trial, the same metric predicted post-FMT community composition via leave-one-out cross-validation and captured known disease-associated alterations in short-chain fatty acid, sulfur, and gas metabolism. We then performed 2,548 in silico FMT simulations between IBS-D/M patients and donors from the OpenBiome biobank to evaluate personalized donor screening, identifying super-donors characterized by high taxonomic diversity, broad metabolic niche coverage, and community interaction networks dominated by cross-feeding rather than competition. Together, these results support metabolic niche complementarity as a potential determinant of post-FMT community composition and provide a mechanistic basis for evaluating donor-recipient metabolic compatibility. This framework offers a scalable approach for generating testable hypotheses for personalized donor selection.

Fecal Microbiota Transplantation↗

PubMed2026

The Effect of Robot-Assisted Gait Training on Balance, Gait and Kinesiophobia in Individuals With Post-Stroke Hemiparesis: A Randomized Controlled Trial.

BACKGROUND AND PURPOSE: Robot-assisted gait training (RAGT) is well established for post-stroke gait rehabilitation, but its potential effects on psychological and behavioral outcomes are less clear. This study investigated the effects of adding RAGT to conventional rehabilitation on balance, gait, kinesiophobia, and movement confidence in individuals with post-stroke hemiparesis. METHODS: This single-blind, parallel-group randomized controlled trial included 60 individuals with post-stroke hemiparesis (50-75 years), randomly allocated to an RAGT group (n = 30) or control group (n = 30). Ethical approval was obtained from the Clinical Research Ethics Committee of Istanbul Yeni Yüzyıl University (Approval No. 20.01.2022/05; approval date: 20 January 2022). Both groups received conventional rehabilitation for 8 weeks; the RAGT group additionally received 24 sessions of RAGT. Kinesiophobia was a prespecified study outcome assessed using the Kinesiophobia Causes Scale (KCS); balance, gait, and balance confidence were also assessed. All 60 randomized participants completed follow-up and were analyzed in their assigned groups. RESULTS: Significant group × time interactions were observed for several outcomes, including BBS, TUG duration, 10MWT walking speed, ABC, and KCS total score (p < 0.05). The between-group difference in change for KCS total score was -0.36 (95% CI: -0.51 to -0.21; partial eta squared = 0.292). In post hoc analyses adjusting each outcome for its baseline value, significant group effects remained for BBS, TUG duration, 10MWT walking speed, ABC, KCS biological domain, and KCS total score (p< = 0.031), whereas 10MWT step count and the KCS psychological domain were no longer statistically significant. DISCUSSION: Adding RAGT to conventional rehabilitation was associated with greater improvements in several balance, mobility, walking-speed, balance-confidence, and kinesiophobia outcomes compared with conventional rehabilitation alone. These findings suggest potential additional physical and psychological benefits of incorporating RAGT into post-stroke rehabilitation. However, because the RAGT group received greater overall treatment exposure, the observed between-group differences cannot be attributed solely to the robotic component. The principal contribution of this study is the concurrent evaluation of kinesiophobia and movement confidence alongside physical outcomes.

Aged↗

PubMed2026

Hysteroscopic platelet-rich plasma and medically assisted reproduction outcomes: a systematic review and SWOT analysis.

BACKGROUND: Platelet-rich plasma (PRP) has been proposed as an adjuvant treatment in reproductive medicine. While most evidence refers to blind intrauterine instillation, subendometrial administration under hysteroscopic guidance allows targeted delivery under direct visualisation. This systematic review aimed to synthesise the available evidence on hysteroscopic PRP administration and its impact on clinical medically assisted reproduction (MAR) outcomes. METHODS: A systematic search was conducted from inception to December 2025 across major databases. Studies were included if they evaluated hysteroscopic PRP administration in women undergoing MAR, comparing reproductive outcomes between treated and control groups. RESULTS: Out of 142 records, 3 studies met the inclusion criteria. Study populations were heterogeneous and included women with refractory thin endometrium and/or a history of implantation failure. Hysteroscopic PRP administration protocols varied in timing, technique, and dosage. In a prospective case-control study, hysteroscopic intraendometrial PRP injection at a depth of 2-3 mm in the four uterine walls, using an ovum aspiration needle, on days 11-13 of the cycle prior to euploid frozen embryo transfer (ET), was associated with higher implantation (IR), clinical pregnancy (CPR), and live birth rates (LBR) compared with standard therapy. Conversely, no significant differences in CPR, miscarriage rate, or LBR were observed in an observational study evaluating a single intraendometrial PRP injection (35-40 mL, 2-3 mm depth), administered via endoscopic needle on days 6-8 of the menstrual cycle preceding frozen ET, alone or after electrical impulse therapy. A randomised controlled trial in women undergoing intrauterine insemination reported a significant improvement in CPR following hysteroscopic subendometrial PRP instillation in the four uterine walls (1.0 mL each). CONCLUSIONS: Current literature on hysteroscopic PRP administration in reproductive medicine is limited, and robust conclusions cannot yet be drawn. Well-designed randomised controlled trials with standardised protocols are needed to clarify its clinical role.

Humans↗

PubMed2026

Repeated low-level red-light therapy for improving asthenopic symptoms and accommodation in presbyopia.

BACKGROUND: To assess the short-term effectiveness of repeated low-level red light (RLRL) therapy in relieving asthenopia and enhancing accommodation in presbyopia. METHODS: This randomized, parallel-group, double-masked clinical trial enrolled adults with presbyopia and self-reported asthenopia. Participants were allocated using computer-generated randomization and randomly assigned at a 1:1 ratio to RLRL or sham groups. Blinding included participants, examiners, assessors, and statisticians. The primary outcome was the change from baseline in the Computer Vision Syndrome Questionnaire (CVS-Q) score at day 31. Secondary outcomes were the change in accommodative amplitude (AA), Near Activity Visual Questionnaire (NAVQ) score, habitual near visual acuity, near-addition power, accommodative facility, positive and negative relative accommodation, binocular cross-cylinder response, and accommodative convergence-to-accommodation ratio. Continuous outcomes were analyzed using linear mixed-effects models. RESULTS: Sixty-four of 66 randomized participants (aged 41-62 years) completed the 1-month trial. At day 31, RLRL showed greater improvement than sham in CVS-Q score (adjusted mean difference, -1.75 points; 95% CI, -3.10 to -0.39), binocular AA (1.09 D; 95% CI, 0.37 to 1.82), and NAVQ score (-8.07 points; 95% CI, -14.17 to -1.97). The effect on AA was most pronounced in a subgroup of eyes with baseline amplitude >2.0 D (adjusted mean difference 1.33 D; 95% CI 0.32-2.34). Other measures did not differ between groups at each visit. No treatment-related adverse events were reported. Adherence was similar between groups (mean compliance: 98.2% vs 97.5%). CONCLUSIONS: Short-term treatment with RLRL significantly reduced asthenopic symptoms and improved accommodative amplitude in individuals with presbyopia.Trial registration: NCT06745661 (registered December 8, 2024).

Humans↗

PubMed2026

A systematic review of human avoidance learning: Cognition, computation, and methods.

Avoidance behaviour is fundamental for survival but can become maladaptive in clinical conditions. A large body of literature has accumulated on the dynamics of human avoidance learning. However, current theories and overviews do not provide an exhaustive account of this evidence. In this systematic review, we identify N = 116 studies on human avoidance learning. We analyse these studies with the goal of distilling robust empirical phenomena as a basis for theory-building, and examine their diagnostic value in differentiating between competing theories. We find that the evidence is difficult to reconcile with foundational two-factor and classical safety-signal accounts, and most strongly supports expectancy- and inference-based views, in which avoidance responses are selected with respect to represented consequences. At the same time, no current framework provides a complete account of the evidence: several findings point to an additional role for operant valuation, Pavlovian influences, and contextual or latent-state control over the expression of avoidance. Methodologically, we observe that the problem setting in the most common experimental paradigms is radically simpler than real-world avoidance and therefore unlikely to expose the limits of inferential or reflective mechanisms. Consequently, we argue that paradigms with greater computational demands and more realistic action affordances are required to identify the mechanisms underlying avoidance learning. Collectively, these insights provide a foundation for theoretical refinement, computational modelling, and methodological innovation, with implications for advancing interventions targeting maladaptive avoidance.

Humans↗

PubMed2026

Bioactive peptides for meat quality and preservation: Integrating peptidomics and computational screening.

Bioactive peptides generated from meat proteins, fermented meat products, and slaughter by-products have attracted increasing attention as functional molecules for improving meat quality and preservation. In meat systems, peptides can be produced through endogenous postmortem proteolysis, microbial fermentation, gastrointestinal digestion, or controlled enzymatic hydrolysis of underutilized animal by-products. These peptides are closely associated with key meat science endpoints, including postmortem tenderization, oxidative stability, color retention, flavor development, microbial inhibition, and the valorization of processing by-products. However, although high-resolution peptidomics has greatly expanded the identification of meat-derived peptide sequences, their translation into practical meat applications remains limited by matrix interactions, processing stability, sensory constraints, safety concerns, and insufficient validation in real meat systems. This review synthesizes recent advances in meat-related peptidomics and computational screening, including sequence-based prediction, machine learning, molecular docking, molecular dynamics, stability assessment, and safety-oriented filtering. Particular attention is given to how these approaches can prioritize peptides with antioxidant, antimicrobial, flavor-modulating, and preservation-related functions under meat-specific technological constraints. By integrating peptide generation pathways, mass spectrometry-based identification, in silico prioritization, and meat quality endpoints, this review proposes a stage-gated framework for translating meat-derived bioactive peptides from discovery to application. Future research should strengthen matrix-specific validation, standardized peptidomic reporting, and safety assessment to support the use of bioactive peptides in meat quality improvement, clean-label preservation, and circular utilization of meat industry by-products.

Animals↗

PubMed2026

Comparative evaluation of molecular technologies for the identification of prevalent non-tuberculous mycobacteria in pulmonary infections: a systematic review and meta-analysis.

BACKGROUND: The increasing prevalence of non-tuberculous mycobacteria pulmonary disease (NTM PD) is a burden to public health. Successful management of NTM PD critically depends on accurate species identification and reliable drug susceptibility testing to guide appropriate antibiotic therapy. Emerging molecular technologies offer rapid diagnostic solutions compared to conventional methods, but their performance varies. This study aims to provide a comprehensive evaluation of current molecular techniques for NTM identification and to present a global antibiotic resistance profile. METHODS: A systematic literature search was conducted in PubMed and Web of Science for studies published between 2005 and 2024. Studies applying molecular methods for NTM identification and resistance detection in humans were included. Data on study characteristics, diagnostic methods, sample types, sample sizes, identification sensitivity, and drug susceptibility results were extracted. Meta-analysis was performed using R with the meta4diag package. The quality of included studies was assessed using the QUADAS-2 tool. RESULTS: The analysis included 49 studies on NTM identification and 33 studies on antibiotic resistance. For species identification, all evaluated molecular technologies (MALDI-TOF MS, PCR-based methods, Sequencing, DNA chip, and DNA strip) demonstrated high pooled sensitivities (>0.92). Subgroup analysis revealed that sample type significantly affected performance for MALDI-TOF MS. Preliminary analysis of antibiotic resistance rates revealed varying patterns. For slowly growing mycobacteria, a significantly high Ethambutol resistance rate was observed in M. avium (69.20%). Among rapidly growing mycobacteria, resistance to Imipenem was notable (54.22%), and Clarithromycin resistance varied significantly within the Mycobacterium abscessus complex. CONCLUSION: Emerging molecular technologies have revolutionized the methodology for NTM identification with excellent performance. However, their performance can be influenced by sample type, particularly for MALDI-TOF MS. The alarming and heterogeneous antibiotic resistance patterns also highlight the critical need for rapid and accurate species identification and drug susceptibility testing to inform effective therapeutic strategies. Key messagesMolecular technologies demonstrate high accuracy for NTM identification.Antibiotic resistance is a serious concern with variations among NTM species and subspecies.Rapid and accurate species identification and drug susceptibility testing are crucial for guiding effective clinical management of NTM PD.

Humans↗

PubMed2026

Applications of quantum AI in brain disorder diagnosis: A systematic review.

BACKGROUND AND OBJECTIVE: Brain disorder diagnosis and prediction remain challenging because neuroimaging, electrophysiological, behavioral, and multimodal data are high-dimensional, noisy, heterogeneous, and limited by small clinical cohorts. This systematic review synthesised applications of quantum artificial intelligence (QAI) for brain disorder diagnosis, prediction, detection, and monitoring. METHODS: Following PRISMA guidelines, studies published from 2016 to 13 January 2026 were retrieved from Scopus, Web of Science, and IEEE Xplore. After screening, 36 studies met the eligibility criteria and were qualitatively analysed according to disorder category, data modality, QAI method, implementation setting, validation strategy, and performance. RESULTS: At the broader disease-group level, neurodegenerative disorders were the most frequently investigated, followed by mental health and psychiatric disorders. At the individual level, Parkinson's disease and schizophrenia were the leading applications, followed by depression, anxiety, Alzheimer's disease, and stress-related tasks. MRI-based modalities were the most frequently used data source, followed by multimodal data and EEG. Methodologically, primary QAI approaches were dominated by quantum neural and QDL architectures, followed by quantum-inspired optimization or feature-selection methods and quantum-kernel/conventional QML classifiers. Qiskit/IBM Quantum and PennyLane were the most frequently reported quantum software frameworks. However, most studies relied on simulators, classical quantum-inspired implementations, or unclear implementation settings, with limited real-hardware evaluation. CONCLUSIONS: QAI shows emerging potential for brain disorder analysis, particularly through hybrid quantum-classical learning, quantum neural architectures, quantum-kernel methods, and quantum-inspired optimization. Nevertheless, current evidence remains preliminary and requires larger datasets, subject-level and external validation, fair classical benchmarking, noise-resilient circuits, real quantum hardware evaluation, explainability, and clinical validation.

Humans↗

PubMed2026

Affective reactivity to a remote computer-based Trier Social Stress Test during a planned quit attempt: associations with short-term cigarette smoking lapse risk.

BACKGROUND: The Trier Social Stress Test (TSST) elicits affective responses and has been linked to smoking behavior. However, its remote use during a planned quit attempt-when stress reactivity may influence early lapse-remains understudied. OBJECTIVE: To quantify affective reactivity to a remotely administered TSST on a planned quit date following overnight abstinence and evaluate associations with cigarette use and lapse within 48 h. METHODS: This secondary analysis used data from a randomized controlled trial of adult smokers completing a remotely administered TSST following overnight nicotine abstinence. Urge, anxiety, and stress were assessed using visual analog scales and summarized using area under the curve (AUC) metrics. Smoking outcomes included cigarette count and lapse within 48 h. Associations were estimated using generalized estimating equations. RESULTS: In adjusted models, anxiety reactivity-but not urge or stress-was associated with cigarette count and lapse. Greater anxiety exposure (AUCtot) and change above baseline (AUCab) were associated with higher cigarette count (IRR=1.0004, 95%CI:1.0002-1.001, p=.002; IRR=1.01, 95%CI: 1.002-1.01, p=.002) and increased odds of lapse (OR=1.001, 95%CI: 1.0001-1.002, p=.03; OR=1.02, 95%CI: 1.001-1.03, p=.03). Effect sizes were small. CONCLUSIONS: Anxiety reactivity under nicotine deprivation was associated with increased cigarette use and lapse 48 h post quit attempt, suggesting individual differences in stress-evoked anxiety may serve as a behavioral marker for early lapse. Remote TSST administration appears feasible for eliciting affective responses on a quit date.

Humans↗

PubMed2026

Effectiveness and usability of artificial intelligence-powered assistive technologies in Supporting daily activities of children with cerebral palsy: a systematic review.

BACKGROUND: Cerebral Palsy (CP) is the main cause of motor disabilities in childhood, necessitating innovative approaches to rehabilitation and assistive technology (AT). Simultaneously, artificial intelligence (AI) is increasingly being integrated into devices to create more adaptive, personalized, and effective AT. This systematic review aimed to evaluate the effectiveness and usability of AI-powered assistive technologies designed to support daily activities and rehabilitation in children with CP. MATERIALS AND METHODS: Five databases, including Scopus, Web of Science, PubMed, Embase, and IEEE Xplore, were systematically searched, and 23 articles were included in the final analysis. Articles were identified, selected, and categorized into emerging thematic areas based on the primary function and application of the technology. RESULTS: Five key thematic topics were identified: 1) AI-driven motor rehabilitation and gait training for functional mobility; 2) intelligent assessment and monitoring systems for clinical decision support; 3) AI-supported communication, social interaction, and intention recognition tools; 4) gamified and virtual reality-based interventions to enhance engagement and usability; and 5) smart assistive systems supporting daily living and independent mobility. The findings demonstrate a strong trend toward the application of AI technologies in personalized, engaging, and data-driven interventions for children with CP. However, the field is predominantly in the proof-of-concept stage, with limitations including small sample sizes, lack of long-term clinical validation, challenges in user-centered design, and usability for children with CP. CONCLUSION: AI-powered assistive technologies hold significant potential for transforming the care of children with CP by enabling highly personalized and engaging interventions. To actualize this potential, future work must realize that practical application remains challenging owing to limited clinical validation, technological integration, and usability barriers for children with CP. Future research must prioritize user-centered design and multidisciplinary collaboration to ensure that AI and robotic advancements improve the usability and quality of life for children with CP.

Humans↗

PubMed2025

Enhanced fracture detection on radiographs with AI assistance for clinicians: a systematic review and meta-analysis.

BACKGROUND: Emergency radiographic interpretation for fractures is prone to missed or misdiagnoses. Artificial intelligence (AI) is expected to become a powerful tool to assist clinicians in fracture detection. PURPOSE: A systematic review and meta-analysis was performed to assess whether AI improves clinicians' ability to detect fractures on radiographs. MATERIALS AND METHODS: A literature search was conducted in PubMed, Web of Science, and Cochrane Library for studies published between January 1, 2010, and October 10, 2025. A meta-analysis of diagnostic accuracy studies was performed using a Summary Receiver Operating Characteristic (SROC) curve. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Subgroup analysis and meta-regression were conducted to explore potential sources of heterogeneity. RESULTS: A total of 26 studies were included . The pooled sensitivity of clinicians increased from 77% (95% CI: 72-81) to 87% (95% CI: 83-90) with AI assistance, while the pooled specificity improved from 88% (95% CI: 85-90) to 92% (95% CI: 89-94). The corresponding AUC values were 0.90 (95% CI: 0.87-0.92) before and 0.95 (95% CI: 0.93-0.97) after AI assistance. Eight studies were rated as high risk of bias. Subgroup analysis and meta-regression identified potential sources of heterogeneity, including fracture location, AI model type, high risk of bias, and reference standards. CONCLUSION: AI assistance significantly improves clinicians' diagnostic performance in detecting fractures on radiographs for extremity and trunk fractures.

Humans↗

PubMed2026

Dexamethasone as an adjuvant to continuous erector spinae plane block for postoperative analgesia after video-assisted thoracoscopic surgery for pulmonary nodule surgery: a randomized controlled trial.

BACKGROUND: While dexamethasone is proven to enhance single-shot erector spinae plane block (ESPB), its role as an adjuvant in continuous ESPB catheters is unclear. This randomised controlled trial evaluated whether adding dexamethasone to ropivacaine improves analgesia after video-assisted thoracoscopic surgery (VATS). METHODS: 85 patients undergoing VATS with continuous ESPB were randomised to receive postoperative infusion of either 0.2% ropivacaine(C-ESPB group) or ropivacaine with 10 mg dexamethasone(D + C-ESPB group). The primary outcome was resting pain visual analog scale (VAS)at 12 h postoperatively, while secondary outcomes included QoR-15 scores, tramadol consumption, time to first analgesic requirement, postoperative adverse events, 3-month incidence of chronic pain, catheter-related complications, pain intensity at other times, and hospital stay. RESULTS: The D + C-ESPB group had significantly lower resting pain at 12 h [2.56 (1.03) vs 3.24 (1.21), mean difference -0.680, p = 0.006]; and lower coughing pain at 12 h [4.60 (1.48) vs 5.69 (1.35), mean difference 1.086, p < 0.001], with analgesic superiority sustained through 72 h. Quality of Recovery-15 scores were higher at 12 h [124.70 (12.48) vs 117.26 (12.24); mean difference -7.436, p = 0.007] and 48 h [141.60 (5.51) vs 138.98 (6.64); mean difference -2.628, p = 0.050]; Total tramadol consumption over 72 h was markedly reduce [0 (0,100) vs 100 (75,100), z = -3.807, p < 0.001], and hospital stay was shorter [Mean (SD) 6.09 (1.34) d vs 6.93 (1.55)d, p < 0.001]. The intervention did not, however, alter the 3-month incidence of chronic postsurgical pain (31% vs 34%, p = 0.756). CONCLUSION: Dexamethasone significantly enhances the analgesic efficacy of continuous ESPB, improving early pain control, recovery quality, and opioid-sparing after VATS, but does not reduce the incidence of chronic persistent surgical pain.

Humans↗

PubMed2026

Prothrombin complex concentrate (PCC) vs. non-PCC strategies for warfarin reversal in left ventricular assist device recipients: A systematic review and meta-analysis.

BACKGROUND: Left ventricular assist devices (LVADs) prolong survival in end-stage heart failure, and warfarin thromboprophylaxis is recommended to prevent device thrombosis and thromboembolic complications. When bleeding occurs or emergency surgery is required, rapid anticoagulation reversal is critical. Prothrombin complex concentrate (PCC) provides rapid reversal; however, its risk-benefit profile in LVAD recipients remains unclear. We conducted a systematic review and meta-analysis comparing PCC with non-PCC strategies for warfarin reversal in LVAD recipients. METHODS: MEDLINE, Embase, and Scopus were searched through June 2025 for studies of PCC versus non-PCC strategies for warfarin reversal in LVAD recipients. Two reviewers independently extracted data. Random-effects models were used to pool arm-level estimates and to pool head-to-head comparisons using mean differences or risk ratios (RRs). RESULTS: Eighteen studies involving 779 patients were included. Arm-level pooled estimates for PCC versus non-PCC comparators were 24.0% versus 15.8% for mortality, 16.5% versus 12.1% for thrombotic events, and 3.1 versus 5.7 for FFP units. Arm-level time to INR correction was longer with PCC overall (16.5 versus 13.6 h), driven by one elective cohort, but faster within the ICH subgroup (6.0 versus 13.7 h). In head-to-head comparisons, PCC achieved faster INR correction than non-PCC comparators (mean difference - 7.6 h; p = 0.001) and required fewer FFP units (-2.6 units; p = 0.019), with no significant difference in all-cause mortality (RR 1.14; p = 0.490) or thrombotic events (RR 1.43; p = 0.176). CONCLUSIONS: In head-to-head studies, PCC was associated with faster INR correction and lower FFP requirements than non-PCC strategies, whereas mortality and thrombotic events did not differ significantly. Given the observational evidence, wide confidence intervals, and heterogeneity, equivalent safety cannot be established, and prospective studies are needed to define the relative safety and effectiveness of the two approaches. IMPLICATIONS FOR CLINICAL PRACTICE: PCC-based strategies may be considered for urgent warfarin reversal in LVAD recipients, particularly when rapid INR reduction or avoidance of large-volume plasma transfusion is clinically important. Treatment decisions should account for the indication, bleeding severity, and underlying thrombotic risk. TRIAL REGISTRATION: CRD42024573925.

Humans↗