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PubMed2026

Phase 3 Trial of Oral Infigratinib in Children with Achondroplasia.

BACKGROUND: Achondroplasia is a genetic skeletal condition caused by FGFR3 pathogenic variants. Infigratinib, an oral FGFR1-3 tyrosine kinase inhibitor, down-regulates key pathways in the pathogenesis of achondroplasia. METHODS: In this phase 3, multicenter, double-blind, placebo-controlled trial, we randomly assigned children with achondroplasia (3 to 17 years of age) in a 2:1 ratio to receive infigratinib (at a dose of 0.25 mg per kilogram of body weight) or placebo once daily for 52 weeks. The primary end point was the change from baseline in the annualized height velocity in the infigratinib group as compared with the placebo group at week 52. Key secondary end points were the change from baseline in the height z score and in the upper-to-lower body segment ratio at week 52. The primary analysis evaluated the treatment effect at week 52 in the full analysis population, with missing data handled with a prespecified imputation approach. RESULTS: In all, 114 patients underwent randomization: 75 patients to receive infigratinib (with 1 withdrawal before treatment) and 39 patients to receive placebo. The difference between infigratinib and placebo in the least-squares mean change from baseline to week 52 was 1.74 cm per year (95% confidence interval [CI], 1.31 to 2.17; P<0.001) for the annualized height velocity, 0.32 (96% CI, 0.23 to 0.41; P<0.001) for the height z score, and -0.02 (96% CI, -0.06 to 0.01) for the upper-to-lower body segment ratio. Adverse events occurred in 71 of 74 patients (96%) in the infigratinib group and in 37 of 39 patients (95%) in the placebo group; serious adverse events occurred in 4 of 74 patients (5%) and 1 of 39 patients (3%), respectively. No serious adverse events or adverse events leading to treatment discontinuation were considered by the investigator to be related to infigratinib or placebo. CONCLUSIONS: In children with achondroplasia, treatment with once-daily oral infigratinib for 52 weeks resulted in a significantly greater increase from baseline in the annualized height velocity than placebo. (Funded by BridgeBio Pharma; PROPEL 3 ClinicalTrials.gov number, NCT06164951; EudraCT number, 2023-506130-67.).

Adolescent↗

PubMed2026

Azacitidine-Venetoclax or Induction Chemotherapy for Acute Myeloid Leukemia.

BACKGROUND: Induction chemotherapy has long been a key component of curative therapy for fit patients with acute myeloid leukemia (AML), despite its frequently severe side effects and substantial health care utilization. For patients who are ineligible for induction chemotherapy, hypomethylating therapy plus venetoclax is the standard treatment owing to its efficacy and side-effect profile. METHODS: In this multicenter, phase 2 trial, we randomly assigned, in a 1:1 ratio, previously untreated adults with AML who were eligible for induction chemotherapy to receive either azacitidine plus venetoclax or induction chemotherapy. Patients with core binding factor fusions, mutations in the gene encoding FMS-like tyrosine kinase 3 (FLT3), or mutations in the gene encoding nucleophosmin-1 (NPM1; unless the patient was ≥60 years of age) were excluded. The primary end point was event-free survival. RESULTS: A total of 172 patients underwent randomization, with 86 patients assigned to each group. The median age of the patients was 64 years. A total of 72% of the patients had adverse-risk disease according to the European LeukemiaNet 2022 classification. At a median follow-up of 21.9 months, the median event-free survival was 14.5 months (95% confidence interval [CI], 10.4 to 24.4) in the azacitidine-venetoclax group, as compared with 6.2 months (95% CI, 4.1 to 10.1) in the induction chemotherapy group, corresponding to a hazard ratio for event or death of 0.57 (95% CI, 0.39 to 0.84; P = 0.002 by the stratified log-rank test). Infection of grade 3 or higher occurred in 28% of the patients (95% CI, 19 to 39) receiving azacitidine-venetoclax and in 41% of those (95% CI, 30 to 52) receiving induction chemotherapy; hemorrhage of grade 3 or higher occurred in 2% (95% CI, 0.3 to 8) and 12% (95% CI, 6 to 20), respectively. CONCLUSIONS: In this phase 2, randomized trial, azacitidine-venetoclax therapy led to significantly longer event-free survival than induction chemotherapy among induction-eligible patients with AML. (Funded by AbbVie and others; PARADIGM ClinicalTrials.gov number, NCT04801797.).

Adult↗

PubMed2026

Validation of the newly introduced Deauville score 5a for patients treated for advanced-stage classic Hodgkin lymphoma.

The Lugano Imaging Committee recently refined the Deauville score (DS), subdividing DS5 into DS5a (>2× liver uptake without new lesions) and DS5b (new lesions). We investigated whether this improves prognostic discrimination at interim positron emission tomography (PET) after 2 cycles (PET-2) in patients with advanced-stage classical Hodgkin lymphoma (AS-cHL) treated in recent German Hodgkin Study Group randomized phase 3 trials. The primary analysis cohort was HD18 postamendment standard arms (uniform treatment with 6 cycles of escalated doses of bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone [eBEACOPP]); sensitivity cohorts were HD18 intention-to-treat and HD21 eBEACOPP and brentuximab vedotin, etoposide, cyclophosphamide, doxorubicin, dacarbazine, and dexamethasone arms. Progression-free survival (PFS) was analyzed by landmark Cox models starting at PET-2. DS5a was infrequent (4%-6% across cohorts; 39/639, 67/1745, 33/568, and 29/560). In the primary cohort, DS5 was associated with inferior PFS vs DS1 to DS3 (hazard ratio [HR], 3.00; 95% confidence interval [CI], 1.25-7.23) and vs DS1 to DS4 (HR, 2.35; 95% CI, 1.01-5.50). Across sensitivity cohorts, DS5a remained adverse compared with DS1 to DS4 (HR range, 2.57-5.47), whereas DS4 according to the new definition did not consistently separate from DS1 to DS3, which is likely a result of PET-adapted treatment. Overall survival trends were concordant, but interpretation is limited by few events. To our knowledge, this is the first prognostic validation of the refined DS in prospectively randomized trial populations. The newly introduced DS5a isolates a small high-risk AS-cHL, which further supports risk assessment and adaptation using quantitative biomarkers from PET. The HD18 and HD21 trials were registered at www.clinicaltrials.gov as NCT00515554 and NCT02661503, respectively.

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

Omics in hereditary optic neuropathies: A systematic review of clinical studies with an integrated point of view.

Hereditary optic neuropathies are characterized by bilateral visual loss due to the degeneration of retinal ganglion cells, resulting in optic nerve degeneration and atrophy. Although the genetic origin of the main isolated and syndromic hereditary optic neuropathies has been characterized, the clinical phenotypes exhibit significant and poorly understood variability in both penetrance and expressivity. Additionally, the genetic and environmental factors that influence the onset of these optic neuropathies remain poorly understood, with limited biomarkers to predict disease progression or as readouts for therapeutic trials. Data-driven omics strategies allow deep phenotyping to improve our understanding of pathophysiological mechanisms and to search for new biomarkers and therapeutic targets. We explore whether the omics strategies applied to patients with hereditary optic neuropathies have provided such new insights. MEDLINE, Web of Science and EMBASE databases were screened for studies with terms relating to hereditary optic neuropathies, transcriptomics, epigenomics, proteomics, metabolomics and lipidomics in clinical studies exploring patients' samples. Out of 1244 references identified, 22 articles were included after double-masked data curation. These articles focused only on the 3 main forms of hereditary optic neuropathies, namely, OPA1-related dominant optic atrophy (n = 4), Leber hereditary optic neuropathy (n = 13), and Wolfram syndrome (n = 5). While the methodological designs and results of these studies were highly heterogeneous, they revealed molecular alterations that we have attempted to discuss at the integrated multi-omics level. This data integration highlighted several common pathophysiological mechanisms such as energetic impairment, endoplasmic reticulum stress, proteotoxic and oxidative stresses, lipid remodeling and altered amino acid and purine metabolisms, while suggesting potential new biomarkers and therapeutic targets. These findings underscore the potential of integrated multi-omics approaches to deepen our understanding of the phenotypic complexity of hereditary optic neuropathies and to support the development of innovative diagnostic and therapeutic strategies.

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

Malaria rapid diagnostic tests: performance, pitfalls, and progress.

PURPOSE OF REVIEW: Malaria rapid diagnostic tests (RDTs) have revolutionized malaria diagnosis in endemic settings. RDTs are simple to use and accurate for clinical cases, although sensitivity is reduced at parasite densities below 200 parasites/μl. However, increasing prevalence of hrp2/3 gene deletions in certain areas threaten utility of histidine-rich protein 2 (HRP2)-based RDTs, and lingering HRP2 antigenemia can generate false-positive results after parasite clearance. This review summarizes current performance of malaria RDTs, threats to their validity, and recent innovations to improve their performance and continued role in malaria diagnosis. RECENT FINDINGS: Most World Health Organization (WHO) prequalified RDTs perform well for clinical diagnosis, with only occasional exceptions, including a recently reported issue affecting several countries. RDT sensitivity is generally related to malaria transmission intensity, with higher proportions of false-negative results in lower-transmission areas. Newly prequalified lactate dehydrogenase (pLDH)-based RDTs perform well for both Plasmodium falciparum in areas with >5% hrp2/3 gene deletions and for Plasmodium vivax diagnosis. Several point-of-care alternatives to RDTs, including micro-fluidic devices, hemozoin-detecting devices, and automated hematology analyzers, have shown promising results in small studies, but require larger-scale trials before widespread use. SUMMARY: RDTs remain a critical tool in clinical diagnosis of malaria, and newer pLDH-based tests perform well in areas where hrp2/3 gene deletions threaten validity of HRP2-based RDTs.

Humans↗

PubMed2026

Artificial Intelligence Technologies in Nursing Clinical Decision-Making: An Umbrella Review.

AIM: To describe contemporary peer-reviewed literature on artificial intelligence in nurses' clinical decision-making. METHODS: An umbrella review of literature reviews. DATA SOURCES: Four major databases were searched for reviews published between 2019 and 2024. RESULTS: Sixteen literature reviews reported on 965 nursing artificial intelligence primary studies. The studies focused on technology development and emerging performance evaluations, whilst real-world testing or implementation in nursing clinical settings was rare. Rigorous comparative analyses were lacking. While artificial intelligence demonstrates promise in decision-making, challenges such as a lack of controlled studies, algorithmic bias, limited reproducibility and insufficient clinical trials hinder its practical impact. Ethical concerns, transparency and patient data privacy issues pose barriers to AI integration in nursing practice. Ethical and legal guidelines for patient privacy are needed and should be taught along with AI literacy training for nurses. CONCLUSIONS: Artificial intelligence has the potential to enhance clinical nursing decision-making, although evidence is limited by too few examples of nurse participation during development. Underutilisation in administrative nursing functions hinders implementation. Nurses should assume a central role in the design and development of AI applications to ensure that these technologies address the realities of nursing practice. With such improvements, artificial intelligence can transform nursing practice, improve nurses' clinical decision-making and ultimately enhance consumer healthcare outcomes. PATIENT OR PUBLIC INVOLVEMENT: No Patient or Public Involvement. REPORTING METHOD: While there is no reporting checklist for umbrella reviews, the PRISMA guide for systematic reviews was followed.

Artificial Intelligence↗

PubMed2026

Chlorfenapyr-pyrethroid nets for pyrethroid-resistant malaria vectors: efficacy, resistance risks, and policy implications.

The Global Technical Strategy for Malaria 2016-2030 aims to reduce malaria incidence and mortality by 90%, yet widespread pyrethroid resistance among major malaria vectors in sub-Saharan Africa threatens this goal. Thus, the World Health Organization recommends chlorfenapyr-pyrethroid combination nets as a priority intervention where pyrethroid resistance undermines vector control. This systematic review synthesizes evidence on the performance, emerging resistance risks, and policy implications of these next-generation insecticide-treated nets. A structured search of literature from 2010 to 2024 across PubMed, Embase, WHO IRIS, and Google Scholar identified 31 eligible studies from 113 records. Evidence shows that chlorfenapyr-pyrethroid nets consistently outperform pyrethroid-only nets against resistant Anopheles populations, demonstrating a 1.8-fold increase in mosquito mortality (95% CI: 1.5-2.1). Community trials report 40-60% reductions in malaria infection incidence and entomological inoculation rates following deployment. However, early signs of chlorfenapyr resistance have emerged in Anopheles gambiae populations in Central Africa (RR: 2.4, p = 0.01), linked to CYP6P4 metabolic overexpression. A significant correlation was also observed between agricultural pesticide use and vector resistance patterns (r = 0.62, p < 0.05). Although chlorfenapyr-pyrethroid nets provide an important short-term tool for managing pyrethroid resistance, their long-term effectiveness depends on integrated resistance management. Rotational deployment with other insecticide classes, strengthened genetic and phenotypic surveillance, and a coordinated 'One Health' approach involving both public health and agriculture are essential to sustain gains and advance progress toward the 2030 malaria targets.

Pyrethrins↗

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

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

Automated CEAP Classification of Venous Duplex Reports Using Multimodal Artificial Intelligence.

OBJECTIVE: To develop and internally validate a prototype multimodal artificial intelligence system for automated CEAP (Clinical, Etiological, Anatomical and Pathophysiological) classification of venous duplex ultrasound (VDUS) reports, integrating natural language processing of free-text components with computer vision analysis of hand-drawn anatomical diagrams. METHODS: Single centre retrospective observational study using routinely collected clinical data. One thousand consecutive venous duplex ultrasound reports from Cambridge University Hospitals NHS Foundation Trust, UK (July 2024 - May 2025) were labelled according to the CEAP classification, excluding the Etiological component, which could not be reliably determined from duplex reports alone. Transfer learning was applied using ClinicalBERT for text and MobileNetV3 for diagrammatic data. Clinical classes were predicted from request line text. Text- and image-based pathophysiological models were developed for four anatomical territories (Great Saphenous Vein, Small Saphenous Vein, Deep system, Perforators), combined using late fusion with probability averaging. RESULTS: The clinical CEAP model achieved accuracy of 0.91, macro-F1 of 0.82, and macro-AUC of 0.98. Pathophysiological prediction varied, with text models broadly outperforming image models. Fusion yielded heterogeneous benefits, improving SSV performance but reducing Deep system accuracy. The performance of the final pathophysiological CEAP fusion models varied across anatomical territories: accuracy ranged from 0.70-0.92 and macro-AUC from 0.80-0.92. CONCLUSION: This study demonstrates the feasibility of automated CEAP classification from VDUS reports. Despite class imbalance affecting minority class predictions, the strong discriminatory performance validates this multimodal ML model for extracting clinically meaningful information from real-world data. This approach offers potential, pending external validation, to streamline vascular services through automated triage and guideline-compliant decision making.

Artificial intelligence↗

PubMed2026

Deciphering S-nitrosylation-regulated metabolic networks in postmortem beef based on label-free modificomics: Identification of ferroptosis as a novel quality-related pathway.

This study elucidated the molecular mechanisms of S-nitrosylation on postmortem beef metabolism and quality based on the label-free modificomics. Varying degrees of S-nitrosylation were exogenously induced in beef semimembranosus (SM) muscle. Results indicated that a high S-nitrosylation level significantly increased beef pH and Warner-Bratzler shear force (WBSF) while reducing centrifugal loss (P < 0.05). A total of 828 S-nitrosylated proteins and 1458 modification sites were identified, of which 114 sites on 81 proteins (DSNPs) exhibited differential modification abundance, representing an increase of 125% compared with previous proteomics studies. DSNPs were mainly involved in glycolysis, the tricarboxylic acid cycle, oxidative phosphorylation, calcium signaling, cell structure, and ferroptosis. Notably, this study provides the first evidence in postmortem muscle that S-nitrosylation regulates key ferroptosis-related proteins, including ACSL, CP, and TF, offering new insights into the link between S-nitrosylation and the ferroptosis pathway in meat. Correlation analysis demonstrated that TF was significantly negatively correlated with pH and WBSF, but positively correlated with centrifugal loss (P < 0.05). Collectively, protein S-nitrosylation critically modulates postmortem beef quality through the coordinated regulation of multiple metabolic processes. More importantly, the identification of ferroptosis as a S-nitrosylation-sensitive pathway provides a new perspective for regulating meat quality through protein post-translational modifications.

Animals↗

PubMed2025

Influence of soil types with different soil-forming process on the qualitative and quantitative detection of microplastics by near-infrared spectroscopy.

Microplastics (MPs) have become a pressing global environmental threat, with soils-acting as sinks for MPs from multiple sources-gaining increasing attention. Near-infrared (NIR) spectroscopy offers a promising tool for MPs detection due to its rapid, non-destructive, and field-applicable features. Although previous studies have focused on the effects of individual soil components on the NIR detection performance of MPs, there is still a lack of systematic research on how the complex background-formed by the coupling of multiple physicochemical properties in natural soils-affects detection performance. This study focuses on soil types with different soil-forming processes, selected five representative agricultural soils to systematically evaluate how the combinations of physicochemical properties they represented affect the performance of NIR-based qualitative and quantitative analysis of MPs in soils. The results demonstrated that soil type significantly affected both the spectral response and detection performance of MPs. Brown Pedocals and Brown Earth exhibited clearer characteristic absorption and stronger linear responses, achieving higher identification accuracy under low (<1.5 %) or zero MPs concentrations and the best quantitative performance (R2 ≥ 0.988, prediction set root mean square error (RMSEP) ≤ 0.110 %). In contrast, Phaeozem and Red Soil were more prone to misclassification at low concentrations, while Fluvo-aquic Soil showed the poorest quantitative performance. This study is the first to reveal, at a holistic level, the critical constraints posed by natural soil complexity on the NIR detection of MPs, offering targeted empirical evidence to support the application of NIR technology in real-world soil environments.

Soil↗

PubMed2026

Predicting training outcomes for developmental dyslexia from EEG data.

Developmental dyslexia (DD) is characterised by lower-than-average reading abilities and is diagnosed in approximately 10% of individuals. The societal barriers may limit professional fulfilment and psychological wellbeing of individuals with DD, calling for the development of effective interventions to counteract them. As DD is associated with challenges in both phonological and visuo-attentional domains, different longitudinal training approaches were developed to strengthen them. However, they require a considerable amount of personal, social and economic resources and the outcomes may vary depending on individual differences in behavioural and neurophysiological functionality. Hence, predicting training outcomes might help in developing personalised treatment protocols and optimising the use of resources. In the present work we applied machine learning to resting-state EEG to predict longitudinal training outcomes in adults with DD enrolled in a randomized clinical trial. In particular, one group received a visuo-attentional training combined with transcranial alternating current stimulation (tACS), another group received visuo-attentional training with sham/placebo stimulation, and the third group received a phonological training with sham/placebo stimulation. The improvement in text reading speed was associated with spectral power in low-beta and individual frequencies in the alpha (IAF) and beta (IBF) bands, while the improvement in pseudoword reading was associated with IBF. The findings highlight the potential of capturing neural markers of treatment responsiveness in DD. Future studies should focus on the generalisability of predictive models to real-world settings, while investigating whether specific EEG markers predict responsiveness to distinct remediation protocols, thus supporting the development of personalised interventions.

Humans↗

PubMed2026

HYPNOSA: Study protocol for a prospective observational cohort of patients with obstructive sleep apnea.

BACKGROUND: Obstructive Sleep Apnea (OSA) is a common chronic disease that affects more than 20% of the adult population. One of the most frequent and characteristic symptoms of OSA is excessive daytime sleepiness (EDS). This symptom is typically treated in patients with OSA with the application of continuous positive airway pressure (CPAP), the gold-standard treatment for this disease. In some patients who are adequately treated with CPAP, residual excessive daytime sleepiness (REDS) persists. The prevalence, associations, and outcomes associated with REDS remain poorly understood. METHODS: Multicenter, prospective, observational cohort study including 1000 patients. Participants will undergo a sleep study for the diagnosis of obstructive sleep apnea (OSA), 24-h ambulatory blood pressure monitoring, clinical assessment, quality-of-life questionnaires, Epworth Sleepiness Scale, and collection of biochemical variables and biological samples. Patients with OSA will receive standard care, and those prescribed continuous positive airway pressure (CPAP) will be monitored for treatment adherence. OSA patients will be assessed at baseline and at 6, 12, and 24 months. DISSCUSION: We aim to establish a prospective observational cohort of patients with obstructive sleep apnea (OSA) treated with CPAP, with and without REDS. The HYPNOSA project will create the largest available registry of patients with OSA and REDS using real-world data, providing accurate prevalence estimates and long-term outcomes. Biological samples will be analyzed to assess the role of specific biomarkers. TRIAL REGISTRATION: Registered at ClinicalTrials.gov. Identifer: NCT06514482.

Adult↗

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

Germline variants and impact on lung cancer outcomes following chemotherapy: A systematic review.

BACKGROUND: Lung cancer is the primary cause of cancer deaths in the UK and globally, and the main subtypes are non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). Many treatment options are available, with platinum-based chemotherapy being a key component for many patients. However, variation in survival outcomes exists among individuals of European ancestry, which makes it important to identify germline genetic variants that help guide decision-making and optimise patient treatment and outcomes. METHOD: A systematic literature search was conducted in PubMed and Web of Science for lung cancer studies investigating the impact of germline genetic variants on systemic anti-cancer therapy (SACT) outcomes in populations of European ancestry. The review was conducted according to the Preferred Reporting Items of Systematic Review and Meta-Analysis (PRISMA) and Synthesis without Meta-Analysis (SWiM) guidelines. RESULTS: A total of 20 studies were included in the review out of 4469 on NSCLC and SCLC, encompassing 3639 patients. The most thoroughly investigated area was NSCLC treated with platinum-based chemotherapy. Genetic variants associated with overall survival and/or progression-free survival included XPD Lys751Gln, XPD Asp312Asn, ERCC1 C118T, and XRCC1 Arg399Gln. For non-platinum-treated NSCLC and SCLC, there was insufficient evidence to conduct a meaningful investigation. CONCLUSION: The XPD Lys751Gln, XPD Asp312Asn, ERCC1 C118T, and XRCC1 Arg399Gln variants showed potential associations with survival outcomes among patients of European ancestry with NSCLC after platinum-based chemotherapy. To support clinical implementation, large real-world pharmacogenomics studies stratified by ancestry are needed to overcome statistical power and heterogeneity limitations.

Humans↗