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PubMed2026

Meningioma methylation profiling as a complement to WHO grading: a single-center experience.

OBJECTIVE: The methylation profile of meningiomas is a promising predictive tool that may improve risk stratification beyond WHO grading. This study aimed to evaluate the clinical relevance and real-world applicability of routine epigenetic testing in meningioma management. METHODS: The authors retrospectively analyzed patients who underwent meningioma resection between January 2021 and December 2023. Histopathological grading (WHO 2021) and methylation profiling (methylation class [MC]) with the MethylationEPIC v1.0 (850k) chip were performed by an independent neuropathologist. RESULTS: A total of 106 patients were included; 81 tumors (76%) were classified as WHO grade 1, 20 (19%) as grade 2, and 5 (5%) as grade 3. Epigenetically, 55 tumors (52%) were classified as benign, 18 (17%) as intermediate, and 2 (2%) as malignant; 31 (29%) could not be classified. Discordances between WHO grading and methylation profiling were observed in 18 of 74 cases. Tumor board decisions were made after a median of 8 days postoperatively, guided by WHO grading; however, the epigenetic report was only available after a median of 23 days. During follow-up, 20 patients experienced tumor progression. Progression was significantly associated with the MC (r = -0.4, p < 0.001) and tumor volume (r = 0.4, p = 0.0005), but not with WHO grading (r = 0.17, p = 0.084). However, the relatively high rate of unclassified tumors and delayed result availability limited the direct impact of MC profiling on immediate clinical decision-making. Interestingly, progression-free survival in MC-unclassified tumors mirrored that of the intermediate group. CONCLUSIONS: Methylation profiling demonstrates superior predictive accuracy for meningioma progression and complements WHO grading, especially in identifying malignant meningiomas. However, its current clinical utility is constrained by technical and logistical limitations. In real-world practice, epigenetic classification should therefore be considered a complementary tool rather than a replacement for established histopathological assessment.

Humans↗

PubMed2026

Protective association of the ELMO1 rs741301 variant against diabetes mellitus and diabetic nephropathy: a systematic meta-analysis of case-control studies.

CONTEXT: Diabetes mellitus (DM), an endocrine disorder, is characterised by persistently elevated blood glucose levels due to inadequate insulin production. Diabetic nephropathy (DN), is a critical complication associated with DM, often leading to end-stage renal failure and increased mortality. OBJECTIVE: This meta-analysis aimed to evaluate the association between the ELMO1 rs741301 polymorphism and susceptibility to DN among individuals with diabetes. METHOD: A systematic literature search was conducted for studies published between 2014 and 2024 using Embase, Google Scholar, and PubMed. Eligible case-control studies investigating the association between ELMO1 rs741301 and DN among individuals with DM were selected according to predefined inclusion criteria. Nine case-control studies comprising 880 individuals with DM and 1008 individuals with DN were included in the meta-analysis. RESULTS: The pooled analysis demonstrated a significant protective association between the ELMO1 rs741301 polymorphism and DN under the allelic model (OR = 0.77, 95% CI: 0.67-0.88), recessive model (OR = 0.74, 95% CI: 0.61-0.90), and dominant model (OR = 0.68, 95% CI: 0.53-0.88). In contrast, no statistically significant association was observed under the over-dominant model. CONCLUSION: The findings suggest that the ELMO1 rs741301 polymorphism may be associated with a reduced susceptibility to DN among individuals with DM. These findings provide evidence for a potential genetic contribution of ELMO1 to DN susceptibility and may help improve understanding of the genetic factors underlying diabetic complications. Further well-designed studies in diverse populations are warranted to validate this association.

Humans↗

PubMed2026

Sarcomas: Research on Ultrarare Subtypes Gains Ground.

Rare cancers account for almost one fourth of all cancers. Sarcomas belong to the group of cancerous diseases with an incidence of less than 6 cases per 100,000 inhabitants. Over the past decade, activities were launched worldwide to elucidate the peculiarities of many of the more than 100 sarcoma subtypes described in the World Health Organization handbook. The major contributor to exact diagnosis is molecular pathology. The subgroup of ultrarare sarcomas (URS) poses a significant problem as each URS type has its own morphology, biology, natural history, and prognosis. In 2020, 35 international sarcoma centers agreed to standards of evaluating URS. The threshold was set to an incidence of less than 1 case per 1,000,000 inhabitants, and 77 URS subtypes were defined. Also quality criteria for centers to be selected for retrieving data to registries were consented. This issue of Cancer Epidemiology, Biomarkers & Prevention contains the first article to validate these principles of URS using the data from a nationwide cancer database. The authors from Taiwan also pointed out limitations of the approach. Combination with the national death database allowed to calculate overall survival (OS) and identified age as a significant factor for OS per URS type. These new data might foster future research on diagnosis and treatment of URS. See related article by Lee et al., p. 1654.

Humans↗

PubMed2026

RFC1 Repeat Expansions in Chronic Idiopathic Axonal Polyneuropathy: Prevalence, Phenotype, and Diagnostic Implications.

BACKGROUND AND AIMS: Chronic idiopathic axonal polyneuropathy (CIAP) accounts for approximately 20%-30% of adult-onset axonal polyneuropathies. Pathogenic RFC1 repeat expansions have emerged as a frequent cause of idiopathic sensory neuropathy, but their recognition in routine clinical practice may be challenging, particularly in the presence of potentially confounding comorbidities. We aimed to determine the prevalence of pathogenic RFC1 repeat expansions in a well-defined CIAP cohort, characterize the associated clinical and electrophysiological phenotype, and evaluate whether coexisting well-controlled diabetes mellitus (DM) or monoclonal gammopathy of undetermined significance (MGUS) may hinder recognition of RFC1-related neuropathy. METHODS: We performed a retrospective observational study of adult patients with CIAP followed at a tertiary neuromuscular unit. All patients underwent RFC1 genetic testing. Clinical and electrophysiological features were compared between RFC1+ and RFC1- patients in the full cohort and after exclusion of patients with DM or MGUS. RESULTS: Ninety patients met CIAP criteria and were analyzed. Twenty-four (27%) carried biallelic pathogenic AAGGG repeat expansions in RFC1, of whom 6 (25%) had coexisting DM or MGUS. Compared with RFC1- patients, RFC1+ individuals more frequently exhibited dysautonomic symptoms, unsteadiness, history of falls, need for walking support, chronic cough, impaired vibration sense in the upper limbs and up to the knees in the lower limbs, brisk upper-limb reflexes, mild cerebellar signs, an abnormal head-impulse test, and a positive Romberg's test. Most of these differences persisted after exclusion of DM or MGUS. Electrophysiological studies in RFC1+ patients showed widespread sensory nerve involvement, including the upper limbs, with relative motor sparing, whereas RFC1- patients exhibited a more typical length-dependent pattern. INTERPRETATION: Biallelic AAGGG repeat expansions in RFC1 were identified in 27% of patients with CIAP. Specific clinical and electrophysiological features may help distinguish RFC1-related disease from other forms of CIAP and identify candidates for genetic testing, even in the presence of potentially confounding comorbidities such as well-controlled DM or MGUS.

Humans↗

PubMed2026

Early and late CTCAE and patient-reported outcomes following lung cancer radiotherapy: A sex-stratified descriptive analysis from the REQUITE cohort.

BACKGROUND: Long-term prospective data on lung cancer patients treated with radiotherapy are limited, restricting understanding of outcomes and sex-specific characteristics. The multicentre REQUITE study provides standardized follow-up data from an international cohort. METHODS: We analysed longitudinal data from 530 lung cancer patients treated with radical radiotherapy (sequential or concurrent chemoradiotherapy, or stereotactic body radiation therapy [SBRT]) between 2014 and 2017 at 16 centres in Europe and the USA. Healthcare professionals prospectively recorded 21 pulmonary, oesophageal, neurological, cardiac, and skin adverse events using CTCAE v4.0. Patient-reported outcomes assessed symptoms, quality-of-life, fatigue, and physical activity. Adverse event incidence was stratified by sex, radiotherapy technique, chemotherapy administration, smoking status, and other clinical factors. RESULTS: At 12 months, 309 patients were evaluable, with 151 having follow-up beyond one year. Pulmonary adverse events were most frequent (40% grade ≥ 2), mainly dyspnoea and cough. Women had higher rates of oesophagitis, and more frequently reported dysphagia, and chest wall pain, while men experienced a higher frequency of cardiac adverse events. Exploratory subgroup analyses identified significant sex-related differences in grade ≥ 3 pulmonary adverse events following SBRT and in overall grade ≥ 2 oesophageal adverse events among patients with clinical stage I-II and those aged >70 years. Patient-reported outcomes showed persistent fatigue and reduced physical activity, particularly in females. Symptom prevalence and severity varied by sex, age, treatment modality, smoking status, and clinical stage. CONCLUSION: The REQUITE-Lung cohort provides prospectively collected real-world data on radiotherapy-related adverse events in lung cancer patients. This study describes patterns of adverse events and patient-reported outcomes according to sex, age, and treatment characteristics. These findings are hypothesis-generating and may support future validation in independent and pooled datasets.

Patient-reported outcomes↗

PubMed2026

Statistical test to compare the linkage model and the admixture model based on central limit results.

In the Admixture Model, the probability that an individual carries a certain allele at a specific marker depends on the allele frequencies in K ancestral populations and the proportion of the individual's genome originating from these populations. The markers are assumed to be independent. The Linkage Model is a Hidden Markov Model that extends the Admixture Model by incorporating linkage between neighboring loci. We prove consistency and asymptotic normality of maximum likelihood estimators for the ancestry of individuals in the Linkage Model, complementing earlier results by (Pfaff et al., 2004; Pfaffelhuber and Rohde, 2022; Heinzel, 2025) for the Admixture Model. These results are used to prove that a statistical test that allows for model selection between the Admixture Model and the Linkage Model is an asymptotic level-α-test. Finally, we demonstrate the practical relevance of our results by applying the test to real-world data from The 1000 Genomes Project Consortium (2015).

Genetic Linkage↗

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

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

Single-organ proteomics in Drosophila melanogaster larva.

The combination of genetic accessibility, organ complexity, evolutionary conservation, and cost-efficiency makes Drosophila melanogaster (Dm) a well-known model system for biomedical and fundamental biological research. Proteomic analysis of single organs enables the identification and quantification of proteins expressed in specific organs. This will help to uncover specific biological functions and unique protein profiles that are not detectable in whole-organism analyses. In this study we have isolated single organs form Dm larvae, and we have performed a deep proteomics mapping by following a minimal manipulation preparation procedure. The combined dataset across all organs comprised 9132 identified proteins. As anticipated, principal component analysis (PCA) revealed clear separation between the proteomes of most organs, confirming distinct protein profiles. These findings demonstrate the applicability of the sample preparation strategy for high-resolution proteomic characterization of individual organs in Drosophila. Given the extensive genetic tools available for this model organism, our approach has the potential to open new avenues for proteomic studies in Drosophila melanogaster and any other biological systems where the sample amount is limiting. SIGNIFICANCE STATEMENT: Drosophila melanogaster is a well-known model system for biomedical and fundamental biological research that serves as a valuable in vivo model organism due to its high degree of evolutionary conservation with higher vertebrates, tractable genetics, and logistical efficiency. However, the proteome of Drosophila at single organ level has been elusive to date, due to several factors like low sensitivity of previous generation mass spectrometers and sample preparation procedures, difficult isolation of some organs. In this study we have applied a compilation of advanced methods including minimal sample manipulation together with simple, straightforward and efficient protein extraction and digestion methods. Obtained peptides were minimally handled to be analyzed by applying specific and sensitive nLC methods coupled on-line to state-of-the-art MS/MS system. Altogether, the applied strategy allowed us to get the first single organ study to date for this animal. These datasets represent a significative resource for future genomic, transcriptomic and proteomic studies in Drosophila, as multi-omic integration requires deep proteomics to translate data into functional biochemistry, and serves as a critical bridge and an indispensable standalone resource across the genomic, transcriptomic, and proteomic landscapes.

Animals↗

PubMed2026

Impact of Commercial Artificial Intelligence on Radiologist Reading Time for Pulmonary Nodule Evaluation at Chest CT.

Background Chest CT is a primary method for identifying pulmonary nodules, yet interpreting scans remains time-intensive and demanding. Currently, artificial intelligence (AI) is expected to reduce reading times, but the effect of AI on reporting times in this setting is unknown. Purpose To evaluate the impact of a commercial AI software on radiologists' reading time for pulmonary nodule assessment on chest CT scans within a real-world clinical setting. Materials and Methods This retrospective study included patients who underwent chest CT examinations at a tertiary medical center between September 2021 and May 2024. The study period was divided into pre- and post-AI phases. The primary outcome was radiology reporting time. The association between AI implementation and reporting time was evaluated using a multivariable parametric Weibull shared frailty survival model adjusted for reader function, examination type, patient location, and requesting specialty, with clustering at the radiologist level. Interaction analyses assessed heterogeneity across prespecified subgroups. An exploratory extrapolation estimated projected workforce and financial impact. Results This study included 19 433 patients (mean age, 62 years ± 14.2 [SD]; 21 814 men; 39 323 chest CT examinations, 19 190 pre-AI, and 20 133 post-AI). AI implementation was associated with faster report completion (adjusted hazard ratio, 1.17; 95% CI: 1.14, 1.21; P < .001). The adjusted median reporting time decreased from 21.3 minutes pre-AI to 18.2 minutes post-AI (14.6% reduction; P < .001). Heterogeneity was observed across reader function (P < .001), examination type (P = .048), and requesting specialty (P = .03). The largest relative reductions were observed for CT thorax electrocardiogram-gated examinations (-41.1%; P < .001) and thoracic radiologists (-25.0%; P < .001), whereas emergency department examinations showed increased median reporting time (7.1%; P < .001). At institutional scan volumes (approximately 20 000-22 000 chest CT examinations annually), exploratory modeling suggested an approximate reduction of 0.5 full-time equivalent radiologist workload. Conclusion Implementation of commercial AI-assisted pulmonary nodule assessment on chest CT scans reduced radiologist reporting time in a real-world clinical setting. © The Author(s) 2026. Published by the Radiological Society of North America under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Iwasawa in this issue.

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

Genomic science and the nurse educator's role: Promoting integration from curriculum to clinical practice.

BACKGROUND: Registered nurses and nurse educators play a critical role in preparing future clinicians to translate genomic discoveries into practice. However, emerging evidence suggests that both groups may lack sufficient knowledge and confidence in genomics, potentially limiting their ability to teach, mentor, and apply genomics in real-world settings. This gap is especially concerning in Aotearoa New Zealand, where the genomic literacy of nurse educators and clinicians remains underexplored. OBJECTIVE: This study aims to: (1) assess nurse educators' genomic literacy and confidence in teaching genomics; and (2) evaluate registered nurses' knowledge and confidence in applying and teaching genomics in clinical practice. DESIGN: Exploratory descriptive qualitative. SETTING: This study was conducted in the greater Auckland area. PARTICIPANTS: A total of 17 participants were recruited using purposive sampling to ensure a diverse range of perspectives across varying levels of teaching experience, disciplinary backgrounds, and exposure to genomic content. METHODS: Data were collected using semi-structured focus group interviews, a method well-suited for generating in-depth discussion and facilitating interaction among participants with shared professional interests. The collected data were analysed using thematic analysis methods. RESULTS: The findings offer insight into the preparedness of New Zealand's nursing workforce to engage with genomic-informed healthcare and inform strategies for integrating genomics into nursing curricula and continuing professional development. Given the interdisciplinary nature of genomic healthcare, these insights may also be relevant to other health professionals-including midwives, pharmacists, and allied health practitioners-who increasingly encounter genomic information in clinical practice and require foundational competencies to support patient care. CONCLUSION: Addressing this educational gap is critical to ensuring that nurses-key facilitators of patient care and public health-are equipped to deliver safe, equitable, and evidence-based genomic healthcare.

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

A smartphone-integrated Pt@Cu-HCF nanozyme-based paper sensor for on-site determination of total antioxidant capacity in marine oils.

Total antioxidant capacity (TAC) serves as a key indicator for evaluating the nutritional quality of foods. In this study, we designed a platinum-embedded copper hexacyanoferrate (denoted as Pt@Cu-HCF) nanozyme that exhibits high oxidase-like activity, efficiently catalyzing the oxidation of chromogenic substrates to generate robust colorimetric signals. Antioxidants quench hydroxyl radicals (∙OH) produced during the catalytic process, leading to a concentration-dependent suppression of the color signal. Leveraging this mechanism, a smartphone-integrated, colorimetric paper sensor for on-site TAC quantification was developed, using vitamin E as the calibration standard. The sensor was applied to determine TAC in fish oil, algal oil, and krill oil, demonstrating a linear response range of 9.78-312.5 μM and a limit of detection (LOD) of 6.41 μM. Validation using real-world marine oil samples showed excellent agreement with a commercial assay kit, confirming the reliability and practical applicability of this portable sensor for TAC measurement in complex biological matrices.

Antioxidants↗

PubMed2026

Assessing perinatal depression identifying abilities among maternal and child health workers in rural China using smartphone-based virtual patients: a multi-center cross-sectional study.

OBJECTIVE: To assess rural maternal and child health (MCH) workers' virtual patients (VPs)-assessed performance in identifying perinatal depression (PND) using smartphone-based VPs, and to identify factors associated with this performance in rural Hunan, China. METHODS: A multicentre cross-sectional study was conducted in Hunan Province, China. A standardized questionnaire collected demographic and work-related characteristics of rural MCH workers. Smartphone-based VPs were used to assess PND identification performance in a simulated clinical scenario. An overall score ≥60 was used as a prespecified operational benchmark across consultation, ancillary assessment, diagnosis, management, and health education domains. Data were analyzed using SPSS 26.0. RESULTS: A total of 375 rural MCH workers participated, yielding an effective response rate of 90.4%. Only 25.9% met the prespecified operational benchmark for VP-assessed PND identification performance. The mean accuracy scores for consultation, ancillary assessment, diagnosis, management, and health education were 94%, 48%, 64%, 58%, and 74%, respectively. Complete consultation accuracy was higher among MCH workers from township health centers than among those from county-level MCH hospitals. MCH workers aged 18-39 years showed higher odds of complete diagnostic accuracy for PND than those aged ≥40 years. CONCLUSIONS: Smartphone-based VP assessment was feasible in rural MCH settings and revealed suboptimal PND identification performance. Mobile VPs may help identify frontline performance gaps and inform targeted training, but further validation against real-world clinical performance, or standardized patient encounters is needed before large-scale implementation. These findings may support targeted capacity-building for rural MCH workers and more equitable perinatal mental health care.

Humans↗

PubMed2026

Systematic review of microorganism disinfection performance by chemical and ultraviolet light water treatment methods.

Safe drinking water is critical for public health, yet microbial contamination remains a significant global challenge. We conducted a systematic review to update World Health Organization guidance on water disinfection technologies by synthesizing peer-reviewed literature from 1997 to 2021 on the performance of free chlorine, chlorine dioxide, ozone, and ultraviolet (UV) light against bacteria, viruses, and protozoa. Following PRISMA guidelines, we analyzed log10 reduction values (LRVs) and contact times (Ct) or fluence (for UV) from laboratory and field studies. We included studies from multiple databases and expert-recommended studies. Results show mean Cts for 2 LRV of non-opportunistic bacteria as 6.0 (free chlorine), 0.4 (chlorine dioxide), and 1.2 (ozone) mg/L*min, and a mean UV fluence of 8.2 mJ/cm² (all bacteria). Viruses required lower Cts, except for UV-resistant adenoviruses, while protozoa required higher Cts or fluences. Opportunistic bacteria required significantly higher Cts than non-opportunistic bacteria for free chlorine and chlorine dioxide. Temperature and pH effects were inconsistent, highlighting data variability and gaps in field studies. These findings support global guidance on water treatment and may be used alongside other context-specific data to understand the roles these technologies play in reducing waterborne exposures. We recommend standardized reporting from performance studies to enable straightforward synthesis of evidence.

Disinfection↗

PubMed2026

Major cardiovascular event risk of advanced therapies in inflammatory bowel diseases: systematic review and meta-analysis.

BACKGROUND: Patients with chronic immune-mediated disorders (IMIDs), including inflammatory bowel disease (IBD), are at increased risk of cardiovascular disease. While advanced therapies show cardioprotective effects in other IMIDs, their impact on major adverse cardiovascular events (MACE) in IBD remains unclear. We conducted a meta-analysis of randomized controlled trials (RCTs) and observational studies evaluating MACE risk with advanced therapies in IBD. METHODS: Systematic search of PubMed, Embase, and Cochrane Central Register of Controlled Trials identified 43 studies (36 RCTs, including 9 long-term follow-up (LTF) studies, and 7 observational studies) published between 2002 and 2024. Primary analyses estimated odds ratios (OR) for MACE comparing advanced therapy to placebo, with secondary analyses stratifying studies by drug class and length of follow-up. Sensitivity analyses were conducted using alternative methods to account for zero-event data. RESULTS: Placebo-controlled RCTs showed a nonsignificant trend toward reduced MACE risk (OR 0.60; 95% CI 0.24-1.51), with similar findings across sensitivity analyses accounting for sparse and zero-event data. Class-specific trends suggested lower MACE risk with IL-12/IL-23 inhibitors (OR 0.35; 95% CI 0.05-2.21), JAK inhibitors (OR 0.57; 95% CI 0.16-2.06), and a potential increase with Anti-TNF agents (OR: 3.04; 95% CI 0.31-29.47), though none reached statistical significance. LTF studies showed consistent findings. Observational studies suggested lower MACE risk with Anti-TNF therapies (OR 0.29; 95% CI 0.21-0.40), but not with IL-12/IL-23 (OR 4.41; 95% CI 0.49-39.28) or JAK inhibitors (OR 1.57; 95% CI 0.86-2.84). CONCLUSION: Advanced therapies did not demonstrate a clear increase or decrease in cardiovascular risk in IBD. The discrepancies between RCTs and observational studies underscore the urgent need for rigorous-designed observational research with long-term follow-up to evaluate the real-world impact of advanced therapies on MACE risk.

Humans↗

PubMed2026

Effects of short-bout accumulated exercise on postprandial metabolism in adults: A systematic review and meta-analysis.

OBJECTIVE: To systematically evaluate the acute effects of short-bout accumulated exercise (SBAE) interrupting prolonged sedentary behaviour on postprandial glucose, insulin, and triglycerides in adults. METHODS: Systematic searches in PubMed, Web of Science, Embase, Cochrane Library, CINAHL, SPORTDiscus, and CNKI (inception to 10 December 2025) identified randomised crossover trials comparing SBAE (≤10 min/bout, inter-bout interval ≥30 min or adequate recovery) with continuous sedentary behaviour. Outcomes included postprandial glucose, insulin, and triglyceride AUCs. Standardised mean differences (SMD) were pooled using random-effects models. RESULTS: Thirty-one publications reporting data from 29 independent cohorts involving 573 unique participants (mean age 47.8 ± 20.3 years; 47.5% female; mean BMI 29.0 ± 5.1 kg/m²) were included. Compared with continuous sedentary behaviour, SBAE significantly reduced glucose AUC (SMD = -0.53, 95% CI: -0.71 to -0.34, P < 0.001) and insulin AUC (SMD = -0.58, 95% CI: -0.85 to -0.31, P < 0.001), but not triglyceride AUC (SMD = -0.17, 95% CI: -0.48 to 0.15, P = 0.306).Exploratory subgroup analyses showed statistically significant reductions in glucose and insulin for walking and for inter-bout intervals < 60 min, but not for standing alone or intervals ≥ 60 min. A statistically significant insulin-lowering effect was observed in obese individuals. CONCLUSION: SBAE acutely improves postprandial glucose and insulin control. Exploratory subgroup analyses showed statistically significant effects for walking and for inter-bout intervals < 60 min, but these comparisons are observational and no formal interaction test was conducted. These findings provide preliminary evidence for acute SBAE in sedentary populations, though long-term health effects and real-world generalisability require further investigation.

Adult↗