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PubMed2026

The return of measles: a dangerous comeback.

PURPOSE OF REVIEW: Measles has reemerged as a significant global public health threat, with increasing morbidity and mortality associated with declining vaccination rates. This review summarizes current global outbreaks, history of measles, vaccination and elimination status, vaccine hesitancy, and outbreak response and lessons learned highlighting different novel digital epidemiological tools. RECENT FINDINGS: Measles continues to surge worldwide with an estimated 11 million infections in 2024, which is more than prepandemic levels. Developing and developed countries are both facing measles outbreaks, with the United States at risk of losing measles elimination status. Recent studies have showed that worldwide percentages of two-dose measles vaccination were lower than 95% that is required to interrupt measles transmission in all WHO regions. Novel epidemiological tools such as interactive simulators, real-time use of dynamic models, serosurveillance, and others are transforming measles outbreak response and enable earlier outbreak detection, tracking, and targeted public health interventions. SUMMARY: Vaccine hesitancy is one of the top global health threats and developing a tailored evidence-based approach is necessary to establish and maintain measles elimination.

Humans↗

PubMed2026

Mitigating pH-induced instability in deruxtecan-based ADCs: an onboard-mixing icIEF approach for robust charge heterogeneity characterization.

Accurate charge variant analysis of antibody-drug conjugates (ADCs) is essential for understanding product heterogeneity and ensuring quality control. However, Deruxtecan (DXd)-based ADCs present a unique analytical challenge due to the intrinsic instability of the payload, where the lactone ring readily undergoes hydrolysis under alkaline conditions, resulting in time-dependent shifts in charge distribution during imaged capillary isoelectric focusing (icIEF). In this study, we describe the development of an onboard-mixing icIEF method designed to minimize pH-induced degradation during sample preparation. By separating ADC samples from carrier ampholytes (CAs) prior to injection and enabling real-time mixing within the instrument, this approach effectively suppresses premature lactone ring opening and stabilizes charge variant profiles. Comparative studies between conventional premixing and onboard-mixing approach demonstrated that the latter significantly enhances reproducibility, particularly for acidic variants that are highly sensitive to structural conversion. Comprehensive method validation confirmed excellent precision, linearity, and sensitivity, with consistent performance across run-to-run and intra-day analyses. The results underscore the importance of controlling microenvironmental pH exposure in the analysis of chemically instable ADCs. The proposed onboard-mixing strategy provides a robust and efficient solution for icIEF-based characterization, reducing analytical artifacts while simplifying method development. This approach is broadly applicable to ADCs and other biotherapeutics containing pH-sensitive functional groups.

Hydrogen-Ion Concentration↗

PubMed2026

AI echo INSIGHT study: A prospective blinded randomized trial of artificial intelligence echocardiogram interpretation.

BACKGROUND: Transthoracic echocardiography (TTE) is the most commonly performed cardiac imaging modality with over 30 million studies annually. Demand for timely expert interpretation continues to outpace capacity, creating diagnostic delays and inter-observer variability that impact patient care. Recent research has suggested computer vision artificial intelligence (AI) models can generate accurate preliminary comprehensive TTE reports, however, prospective evaluation is needed to determine whether AI-assisted TTE interpretation can improve clinician efficiency while preserving diagnostic accuracy. METHODS: AI ECHO INSIGHT is a prospective randomized blinded clinical trial conducted at Kaiser Permanente Northern California that will evaluate 1200 historical TTE studies (1000 consecutive unselected studies plus 200 with moderate or greater valvular disease) interpreted using three workflows: (1) AI-generated preliminary report finalized by a blinded cardiologist (AI-assisted); (2) cardiologist-generated preliminary report finalized by a blinded cardiologist (cardiologist-assisted); and (3) sonographer-generated preliminary report finalized by a blinded cardiologist (sonographer-assisted). The primary outcome is the rate of substantial change between preliminary and final reports, comparing the AI-assisted workflow to the pooled cardiologist-assisted and sonographer-assisted workflows. Secondary outcomes include cardiologist interpretation time for report finalization, superiority testing for diagnostic accuracy, and reporting consistency. CONCLUSION: AI ECHO INSIGHT is a prospective randomized blinded clinical trial evaluating the clinical impact of AI-assisted TTE interpretation on diagnostic accuracy, cardiologist efficiency, and reporting consistency in real-world echocardiography workflows. TRIAL REGISTRATION: ClinicalTrials.gov registration number NCT07229300.

Humans↗

PubMed2026

Complexity in disguise: a systematic review of fractal analysis in psychiatric neuroimaging.

OBJECTIVES: Psychiatric diagnosis and fractal studies are complex processes that extend beyond clinical evaluation and require careful methodological considerations in neuroimaging. Over the years, fractals have helped reduce these complexities in research, but they still cannot grant clinical diagnoses. Thus, the main objective was a systematic review exploring the potential applications of fractal analysis in characterizing psychiatric conditions through neuroimaging techniques-including both functional and structural MRI. MATERIALS AND METHODS: A systematic literature review was conducted on PubMed, identifying thirty-nine original studies that met the inclusion criteria. Areas showing statistical significance (p < 0.05) were reported. These studies were categorized according to DSM-V classification and examined for the description of psychiatric conditions through the fractal analysis. RESULTS: The review primarily focuses on young adults with psychiatric conditions compared to control groups. Schizophrenia and Autism Spectrum Disorder are major areas of investigation, and fractal dimension (FD) is the primary analysis method used to reflect brain patterns. Studies that calculated whole-brain FD may have underestimated local abnormalities due to the inclusion of a high percentage of tissue, potentially resulting in overlooked findings. Notably, abnormalities in the frontal cortex represent a common neurobiological feature across several psychiatric conditions. CONCLUSIONS: The findings from this systematic review shed light on the use of fractal analysis to quantify complex brain patterns in both psychiatric patients and healthy individuals. However, it is essential to recognize the need for further research to elucidate a fractal analysis protocol that allows for optimal extraction of psychiatric insights. KEY POINTS: Question Fractal analysis applied to structural and functional MRI help characterize brain alterations across psychiatric conditions. Findings This review shows consistent fractal patterns across multiple psychiatric disorders, especially in frontal regions. Despite heterogeneous methodologies, results highlight shared structural and functional abnormalities. Clinical relevance Fractal analysis may offer complementary characterization of subtle brain organization across psychiatric disorders. Its potential clinical utility-such as improving diagnostic characterization, earlier detection, among others-remains limited by the current absence of a standardized protocol.

Humans↗

PubMed2026

PaNDA: Efficient Optimization of Phylogenetic Diversity in Networks.

Phylogenetic diversity (PD) plays an important role in biodiversity, conservation, and evolutionary studies by measuring the diversity of a set of taxa based on their phylogenetic relationships. In phylogenetic trees, a subset of k taxa with maximum PD can be found by a simple and efficient greedy algorithm. However, this algorithmic tractability is lost when considering phylogenetic networks, which incorporate reticulate evolutionary events such as hybridization and horizontal gene transfer. To address this challenge, we introduce PaNDA (Phylogenetic Network Diversity Algorithms), the first software package and interactive graphical user-interface for exploring, visualizing, and maximizing diversity in phylogenetic networks. PaNDA includes a novel algorithm to find a subset of k taxa with maximum diversity, running in polynomial time for networks of bounded scanwidth, a measure of tree-likeness of a network that grows slower than the well-known level measure. This algorithm considers the variant of PD on networks in which the branch lengths of all paths from the root to the selected taxa contribute towards their diversity. We demonstrate the scalability of this algorithm on simulated networks, successfully analyzing level-15 networks with up to 200 taxa in seconds. We also provide a proof-of-concept analysis using a phylogenetic network on Xiphophorus species, illustrating how the tool can support diversity studies based on real genomic data. The software is easily installable and freely available at https://github.com/nholtgrefe/panda. Additionally, we extend the definition of PD to semi-directed phylogenetic networks, which are mixed graphs increasingly used in phylogenetic analysis to model uncertainty of the root location. We prove that finding a subset of k taxa with maximum diversity remains NP-hard on semi-directed networks, but do present a polynomial-time algorithm for networks with bounded level.

network↗

PubMed2026

Thermal analysis techniques for microplastic mass quantification: Methodological challenges and standardization needs.

Microplastics (MPs, 1 μm-5 mm) and nanoplastics (NPs, <1 μm) are ubiquitous contaminants requiring standardized quantification methods. This systematic review evaluates thermal analysis techniques for mass-based MP detection, including pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS), thermogravimetry-MS (TGA-MS), thermal extraction desorption-GC-MS (TED-GC-MS), and differential scanning calorimetry (DSC). Database searches (Web of Science, from inception to December 1, 2025) following PRISMA guidelines identified studies across seven environmental matrices (water, soil/sediment, atmosphere, biota, human tissues). We identify critical standardization gaps: inconsistent marker ion selection, unvalidated conversion factors for tire and road wear particles (TRWPs), and the absence of certified reference materials for complex matrices. Py-GC-MS demonstrates versatility but suffers from lipid interference in biological samples; TED-GC-MS offers superior sensitivity (sample capacity ∼200× Py-GC-MS) but lacks real-time chromatographic monitoring. To advance data comparability, we propose: (i) harmonized ion selection hierarchies based on specificity-sensitivity balance, (ii) matrix-specific TRWP quantification protocols, and (iii) inter-laboratory validation using environmental reference materials. This review provides a methodological roadmap for standardizing thermal analysis in MP research.

Humans↗

PubMed2026

Dynamic lysine acetylation and succinylation of platelet proteins regulates platelet storage lesion: mechanistic insights from multi-omics.

OBJECTIVES: Platelet storage lesion (PSL) severely impairs platelet function during storage, presenting a major hurdle in transfusion medicine; however, the dynamic interplay between global proteomic changes and post-translational modifications (PTMs) underlying these functional deteriorations remains insufficiently characterized. Here, we report the first comprehensive multi-omics analysis integrating global proteomics, acetylomics, and succinylomics to dissect the molecular dynamics during platelet storage. METHODS: We performed quantification of global proteomics, acetylome and succinylome based on TMT-labeled LC-MS/MS analysis, combined with antibody-affinity enrichment and purification. Dynamic molecular changes and functional transformation of platelet were also characterized under proper conditions stored for 1, 3, 5, 7 days, respectively. RESULTS: We systematically characterized 3,609 proteins, 1,308 acetylation sites, and 1,947 succinylation sites across multiple storage time points (D1, D3, D5, D7). We distinct temporal patterns of post-translational modifications, with succinylation showing more extensive coverage than acetylation in platelets. Pathway enrichment analysis revealed extensive metabolic reprogramming involving complement activation, energy metabolism, and cellular detoxification processes. The identification of specific motif patterns provided mechanistic insights into the functional specificity of these modifications. Random forest machine learning identified 20 core regulatory proteins representing critical nodes in PSL development. Furthermore, we employed real - time quantitative polymerase chain reaction (RT - QPCR) to measure the expression levels of key genes related to platelet function and PTM - associated pathways. CONCLUSION: By mapping the interplay between proteomic abundance shifts and PTM dynamics, this study provides a multidimensional understanding of PSL, establishing a foundational framework for optimizing storage protocols and enhancing transfusion safety.

Blood Platelets↗

PubMed2026

HPV circulating tumor DNA as a potential prognostic and predictive biomarker in head and neck squamous cell carcinoma: a systematic review.

PURPOSE: Human papillomavirus circulating tumor DNA (HPVctDNA) has emerged as a promising prognostic biomarker in HPV-related head and neck squamous cell carcinoma (HNSCC). This systematic review aimed to synthesize current evidence on the diagnostic accuracy and prognostic value of HPVctDNA in HNSCC management. MATERIAL/METHODS: We systematically reviewed a PubMed-indexed database of studies published between January 2012 and September 2025. Eligible studies were assessed for design, primary tumor site and stage, treatment modality, HPVctDNA detection method, diagnostic accuracy (sensitivity and specificity), and reported clinical endpoints. Descriptive syntheses were performed; sensitivity and specificity were standardized to proportions and summarized as median values per group. RESULTS: A total of 60 studies, including 8,234 patients were analyzed, of which 41 (68.3%) focused exclusively on oropharyngeal squamous cell carcinoma (OPSCC) and 17 (28.3%) included mixed HPV-related HNSCC subsites and HPV-positive cancers of unknown primary. The median follow-up across the included studies was 23 months. Among the included studies, 19 were retrospective (31.7%) and 33 were prospective (55.0%), with a small proportion of cross-sectional and randomized clinical trials. Overall, 40 (66.7%) evaluated the role of HPVctDNA in a curative setting. Plasma was the most common sample type, analyzed in 55 studies (91.7%), while 5 studies also included saliva. Detection methods varied: 40 employed droplet digital PCR (ddPCR), 16 used quantitative PCR (qPCR) and 4 applied NGS-based assays. Most of these studies (38, 63.3%) evaluated the prognostic utility of HPVctDNA, while only 4 (6.7%) assessed HPVctDNA in a screening or diagnostic setting. Regarding diagnostic accuracy, the median sensitivity across evaluable studies was 91.1%, while the median specificity was 99.4%. In OPSCC-only cohorts, the median sensitivity and specificity were 89.4% and 99.4%, respectively. Dynamic changes in HPVctDNA levels during or after treatment were consistently associated with outcomes: clearance or sustained negativity correlated with higher response rates, improved progression-free survival and overall survival, while persistent positivity or increasing levels predicted disease progression and recurrence. CONCLUSIONS: HPVctDNA demonstrates high diagnostic and prognostic accuracy in HPV-related HNSCC, especially OPSCC, supporting its use for prognosis, treatment monitoring and early detection of recurrence. However, prospective interventional studies are still required to demonstrate that HPVctDNA-guided treatment decisions improve clinical outcomes before routine implementation.

Humans↗

PubMed2026

Suppression of HIV-1 replication in CEM-A cell cultures by trans-splicing group I introns targeting PAS/PBS sequences and conditionally expressing ΔN-Bax.

Anti-HIV group I introns containing antisense guide sequences directed against the HIV-1 primer activation signal and primer-binding site (PAS/PBS) were designed and evaluated. Because PAS/PBS sequences are present in the viral RNA species examined, these RNAs can serve as trans-splicing substrates. The introns were active against both artificial target RNAs and viral RNA generated during infection. Cleavage and degradation of targeted viral RNA may have contributed to suppression, whereas inclusion of a 3' exon encoding the proapoptotic protein ΔN-Bax was associated with increased programmed cell death and may have augmented suppression of viral replication. In cultured CEM-A cells, transgene expression of these introns markedly suppressed HIV-1 replication, with p24 levels falling below the assay detection limit in selected clones. RESULTS: RT-PCR and sequence analysis detected splice products containing the expected PAS/PBS junctions. In the dual-luciferase assay, intron expression reduced normalized Gaussia luciferase signal by approximately 70% relative to the negative control. Qualitative Annexin V imaging and caspase-3 assays were consistent with infection-dependent apoptosis after ΔN-Bax splice-product formation. Transient expression of each intron in HEK293T cells followed by infection with VSV-G-pseudotyped HIV-1NL4-3 at an MOI of 2 reduced p24 levels by approximately 50% at 4 days post-infection. Construct 128L produced the strongest RT-PCR band under the tested conditions and was selected for subsequent experiments. A canonical splice product and a low-abundance noncanonical splice product were detected; both involved the intended HIV-derived target RNA, although transcriptome-wide off-target splicing was not assessed. Heterogeneous transformed HEK293T populations showed an approximately 2-log10 reduction in p24. In selected clonal HEK293T and CEM-A lines, p24 was below the assay detection limit at the measured endpoints, including up to 90 days after infection in some CEM-A clones. CONCLUSIONS: PAS/PBS-targeting group I introns suppressed HIV-1-associated p24 production in the tested cell-culture models. Linking the introns to a ΔN-Bax 3' exon was associated with infection-dependent apoptosis and may further limit viral replication and spread. The use of highly conserved, functionally constrained target sequences may reduce the likelihood of escape, but viral evolution and transcriptome-wide off-target effects were not assessed. This conditional death-upon-infection strategy warrants further evaluation in primary-cell and in vivo models.

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

Dengue and chikungunya vaccines past, present and future: implications for travelers.

PURPOSE OF REVIEW: Novel vaccines for dengue and chikungunya viruses offer new prevention options against two globally important arboviral diseases. This review summarizes recent developments in vaccine licensure, implementation, real-world experience and research priorities, with emphasis on implications for both endemic populations and travelers. RECENT FINDINGS: Of the three live-attenuated dengue vaccines licensed to date, TAK-003 is authorized in >40 countries and Butantan-DV in Brazil, while manufacturing of CYD-TDV is discontinued. Long-term and postmarketing data continue to refine understanding of serotype-specific protection, waning immunity, and rare adverse events.For chikungunya, two single-dose vaccines are licensed-a live-attenuated vaccine (VLA1553) and virus-like particle vaccine (PXVX0317). Uptake is guided by emerging safety and effectiveness data, with each platform offering potential advantages in different settings.Further data on long-term protection, safety, effectiveness, use in vulnerable populations and integration into outbreak management and immunization systems is anticipated. SUMMARY: Dengue and chikungunya vaccines are increasingly being used in immunization programs and pretravel consultations. Further real-world data are needed-particularly for seronegative dengue vaccine recipients and older, immunocompromised or medically at-risk adults. Research priorities include developing single-dose, nonlive dengue vaccines suitable for high-risk groups, understanding long-term chikungunya vaccine performance, and exploring broader flaviviral or pan-arboviral platforms.

Humans↗

PubMed2026

Influenza A virus in Swiss pig herds with respiratory disease: Seasonality and age dependence.

Influenza A virus (IAV) is an important respiratory pathogen in pigs and poses a zoonotic risk to humans in close contact. While IAV epidemiology has been extensively studied in large-scale production systems, data from Switzerland - characterized by small herds and limited live pig imports - remain scarce. This exploratory nationwide cross-sectional study aimed to assess the association between herd-level IAV detection and reported respiratory disease in pig herds, and to explore associations with husbandry-, animal-, and human health-related factors. Between November 2023 and April 2025, 25 Swiss pig herds with caretaker-suspected respiratory symptoms were investigated. In each herd, five nasal swabs were collected and analyzed by quantitative PCR. Herd managers completed an interview, and clinical examinations were performed. Overall, 56 % (95 % CI: 37,1 - 73,3) of herds tested positive for IAV, comparable to reports from other European countries. The estimated intra-herd detection rate was 49,6 % (95 % CI: 31,2 - 68,0). Respiratory disease outbreaks associated with IAV detection showed indications of seasonal variation, with no positive herds identified during summer. Across age groups, pigs aged 11-14 weeks had a higher likelihood of IAV detection, with 15,79-fold increased odds (95 % CI: 1,50 - 860,4), although with considerable uncertainty. The interpretation is limited by the small sample size, heterogeneous data, and reliance on single time-point qPCR detection. The results suggest that IAV detection in clinically apparent respiratory outbreaks may follow seasonal patterns in Swiss pig herds. Weaners and newly introduced fattening pigs may play a role in such respiratory outbreaks and could represent relevant targets for IAV surveillance in Switzerland. Continued monitoring and the implemen tation of appropriate control measures remain important given the virus's zoonotic potential and impact on pig health.

Animals↗

PubMed2026

Investigation of ACE gene polymorphism and serum ACE activity in relation to alopecia areata among Iraqi patients.

BACKGROUND: Alopecia areata (AA) is a multifactorial disorder with immune dysregulation and genetic susceptibility, affecting 0.5-2% globally. OBJECTIVE: This study investigated angiotensin converting enzyme (ACE) gene insertion /deletion (I/D) polymorphism and serum ACE activity in Iraqi AA patients and their association with inflammatory cytokines (interleukin [IL]-17) and nutritional markers to understand disease progression. METHODS: This case-control study included 50 AA patients (Male and Female) and 35 healthy controls. ACE gene polymorphism (rs1799752) was analyzed using real-time polymerase chain reaction (qPCR) with high-resolution melting (HRM) analysis. Serum IL-17 levels were determined by enzyme-linked immunosorbent assay (ELISA), and biochemical markers were measured using an automated analyzer. RESULTS: ACE gene polymorphism (rs1799752) showed non-significant genotype distribution between patient and control groups (p > 0.05), though a trend toward DD genotype enrichment was observed in patients. Serum ACE levels were significantly higher in patients versus controls (p < 0.0001) with high diagnostic performance. ACE correlated positively with IL-17 (P < 0.0001) and negatively with vitamin D3 and zinc (P < 0.0001). Female patients had significantly higher ACE levels than males (P < 0.01). CONCLUSIONS: ACE emerges as an immunometabolic hub in AA pathogenesis, integrating inflammation with nutritional deficits, suggesting its potential as a biomarker and therapeutic target.

Humans↗

PubMed2026

Intraoperative indocyanine green near-infrared fluorescence imaging for assessing testicular viability in pediatric testicular torsion: A retrospective study.

OBJECTIVE: To evaluate the clinical efficacy of indocyanine green near-infrared fluorescence (ICG-NIRF) imaging versus conventional surgery for assessing testicular viability and guiding decision-making in pediatric testicular torsion (TT). METHODS: A retrospective analysis was performed on 225 pediatric patients undergoing emergency scrotal exploration for TT between January 2019 and January 2025. Patients were categorized into a conventional surgery group (n = 118) relying on visual grading and an ICG-NIRF imaging group (n = 107). Primary outcomes included intraoperative testicular preservation rates and postoperative success rates. Multivariate Cox regression was utilized to identify factors influencing testicular preservation. RESULTS: Baseline characteristics were comparable between groups. The ICG-NIRF group demonstrated a significantly higher intraoperative preservation rate (74.77% vs. 61.02%, p = 0.028) and postoperative success rate (88.75% vs. 69.44%, p = 0.003) compared to the conventional group. Additionally, the ICG-NIRF group exhibited significantly lower rates of secondary orchiectomy (1.25% vs. 9.72%, p = 0.027) and 6-month testicular atrophy (7.59% vs. 23.08%, p = 0.02). Multivariate analysis confirmed ICG-NIRF application as an independent protective factor for testicular preservation (HR = 0.556, p < 0.001). CONCLUSION: ICG-NIRF imaging provides an objective, real-time assessment of testicular perfusion, significantly improving testicular preservation rates and postoperative outcomes. This technique overcomes the subjectivity of conventional visual methods, offering substantial clinical value for fertility preservation in pediatric TT.

Humans↗

PubMed2026

Teacher- Versus Video-Delivered Classroom Activity Breaks and Student Physical Activity: The PAAC-3 Trial.

BACKGROUND: Classroom activity breaks may increase moderate-to-vigorous physical activity (MVPA); however, few studies have compared teacher and video-delivered approaches under real-world conditions. METHODS: In this cluster randomized trial, 11 elementary schools were assigned to teacher-delivered (PAAC-T; 5 schools, 192 students) or video-delivered (PAAC-V; 6 schools, 276 students) classroom activity breaks across one academic year. Teachers were trained to deliver two 10-min breaks daily. Intervention delivery was tracked via a web-based platform, and classroom MVPA was assessed using accelerometers at baseline and follow-up. RESULTS: Implementation fidelity was low and highly variable, but comparable between PAAC-T (42.3 ± 57.1 activity breaks/teacher/year) and PAAC-V (39.2 ± 33.9; p = 0.96), with teachers delivering ∼50% of the intended daily activity. Classroom MVPA increased significantly in both groups (PAAC-T: 9.8 ± 15.9; PAAC-V: 9.1 ± 15.3 min/day; p < 0.001), with no intervention arm-by-time interaction (p = 0.43). IMPLICATIONS FOR SCHOOL HEALTH POLICY, PRACTICE, AND EQUITY: Classroom physical activity breaks may increase student MVPA, but effectiveness in elementary schools appears to depend on implementation fidelity, administrative support, and equitable system-level infrastructure. CONCLUSIONS: Modest increases in classroom MVPA were observed across both delivery formats, although low and variable implementation fidelity limited conclusions regarding effectiveness and highlighted the need for stronger implementation supports. TRIAL REGISTRATION: NCT03493139.

Humans↗

PubMed2026

Development and validation of a comprehensive prognostic model for 28-day ICU mortality in non-traumatic subarachnoid hemorrhage: an analysis based on the MIMIC-IV database.

BACKGROUND: Due to the complex pathophysiology of non-traumatic subarachnoid hemorrhage (SAH), accurate risk prediction remains a challenge. Our aim is to develop and validate a comprehensive prognostic model that integrates demographic characteristics, vital signs, laboratory parameters, and more, to provide clinical decision-making support in real-world practice. METHODS: We conducted a retrospective cohort study of 785 Non-traumatic subarachnoid hemorrhage patients. The cohort was randomly divided into a training set (n = 549) and a validation set (n = 236). Feature selection was performed using LASSO regression, followed by backward stepwise Cox regression for optimization. A nomogram was constructed based on independent predictive factors, and model performance was assessed using discrimination, calibration, and decision curve analysis. To prevent immortal-time bias, all predictors were anchored to a fixed early (first-24-hour) measurement window, treatment variables were modelled as binary indicators rather than cumulative exposures, and a five-model sensitivity analysis with baseline-severity adjustment was performed. RESULTS: The development of our model followed a systematic approach: first, 15 potential predictive factors were selected via LASSO regression, which were then refined to 12 independent predictors using backward stepwise Cox regression. The final predictive factors included: Ventilation, AHT, Nimodipine 60 mg, Age, SAPS.II, Input amount, Calcium total, Platelet count, White blood cells, Anion gap, pH, and Chloride. The integrated model demonstrated excellent predictive ability for 7-day, 14-day, and 21-day mortality in both the training set (AUC: 0.972, 0.934, 0.898) and the validation set (AUC: 0.968, 0.948, 0.911). Calibration curves and decision curve analysis confirmed the model's reliability and clinical utility across different time points. We constructed a nomogram for individualized risk prediction. Univariate Kaplan-Meier survival analysis demonstrated significant stratification of survival outcomes by each predictor, while restricted cubic spline analysis revealed non-linear relationships between continuous variables and mortality risk. Random survival forest analysis identified the top three predictive factors (Nimodipine 60 mg, Ventilation, AHT) and compared them with our full 12-variable model, confirming superior performance of the integrated model at all time points. At the 28-day primary endpoint, the model achieved a time-dependent AUC of 0.898 (training) and 0.904 (validation); after restricting predictors to the early baseline window, the leakage-controlled model retained good discrimination (validation C-index 0.803). CONCLUSIONS: Our ICU 28-day mortality prognosis model demonstrated robust performance in predicting ICU 28-day mortality in non-traumatic subarachnoid hemorrhage. The model, through the nomogram, provides individualized risk assessment, aiding clinical decision-making and patient stratification.

Humans↗

PubMed2026

Assessing the public health impact of routinely collected electronic healthcare record data in NICE guidelines: A systematic review of CPRD research.

OBJECTIVES: Evidence used in NICE guidance has traditionally prioritised randomised controlled trials, but increasing availability of electronic health record (EHR) data has expanded opportunities for real-world evidence. The Clinical Practice Research Datalink (CPRD) is a commonly used UK primary care EHR resource, yet the extent to which CPRD studies have informed NICE guidelines in the past decade is unclear. STUDY DESIGN: The systematic review was conducted in accordance with PRISMA guidelines. METHODS: We conducted a systematic review of CPRD studies in PubMed, MEDLINE, and Embase published between 04/16-09/25. For each eligible CPRD study, targeted searches of NICE guidelines were performed to identify explicit citations in NICE guidelines. Two reviewers screened and extracted data independently, resolving disagreements by consensus or third reviewer. Guideline information, number of guidelines over time, type of guidelines, and disease area guidelines (using British National Formulary (BNF) chapters) were described. RESULTS: 7181 records were identified. After de-duplication, 2704 unique CPRD studies were screened against NICE guidelines. Of these, 92 CPRD-based studies met inclusion criteria and were cited across 67 NICE documents. The annual number of NICE guidelines citing CPRD studies increased between 2016 and 2025; 1.5% of identified guidelines published in 2016 and 27.7% in 2025. The guideline citing the most CPRD studies was cancer related. The most common types of guidelines included clinical guidelines (49.3%) and technology appraisals (32.8%). Guidelines made up 12 different BNF categories, most frequently central nervous system related (23.9%; n = 16). CONCLUSION: Observational CPRD studies are increasingly referenced in NICE guidelines across multiple disease areas, supporting the growing role of EHR data in national guideline development.

Clinical studies↗

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↗