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PubMed2026

Performance of AI-Based Screening Tools for Obstructive Sleep Apnea Across Apnea-Hypopnea Index Thresholds: Systematic Review and Meta-Analysis.

BACKGROUND: Obstructive sleep apnea (OSA) is highly prevalent but remains substantially underdiagnosed. Polysomnography (PSG) is the reference standard, but its cost and limited availability constrain large-scale case identification. AI-based screening tools may support risk stratification and referral prioritization, but their diagnostic accuracy across apnea-hypopnea index (AHI) thresholds remains uncertain. OBJECTIVE: This review aimed to systematically evaluate the diagnostic accuracy of AI-based OSA screening tools at AHI thresholds of ≥5, ≥15, and ≥30 events/hour, with emphasis on models using non-PSG-derived inputs. METHODS: PubMed, Embase, Scopus, and Web of Science were searched for studies published from January 1, 2016, to May 3, 2026. Eligible studies included adults evaluated for suspected OSA or recruited from population-based cohorts, assessed AI-based models intended or interpretable for OSA screening, risk prediction, or screening-oriented severity classification, used PSG as the reference standard, and reported sufficient data to construct or reconstruct 2×2 contingency tables. Diagnostic accuracy was synthesized separately by AHI threshold and input source using bivariate random-effects models, with 95% CIs and prediction intervals (PIs). Risk of bias and certainty of evidence were assessed using QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies 2) and GRADE (Grading of Recommendations Assessment, Development, and Evaluation), respectively. RESULTS: A total of 60 studies were included, of which 47 contributed data to the meta-analysis. At AHI thresholds of ≥5, ≥15, and ≥30 events/hour, pooled sensitivities were 0.94 (95% CI 0.92-0.96; 95% PI 0.71-0.99), 0.87 (95% CI 0.84-0.89; 95% PI 0.66-0.96), and 0.83 (95% CI 0.79-0.87; 95% PI 0.61-0.94), respectively; the corresponding specificities were 0.77 (95% CI 0.69-0.84; 95% PI 0.30-0.96), 0.81 (95% CI 0.75-0.85; 95% PI 0.39-0.96), and 0.91 (95% CI 0.87-0.94; 95% PI 0.55-0.99), respectively. The corresponding areas under the summary receiver operating characteristic curves were 0.943, 0.907, and 0.920. For non-PSG-derived tools, sensitivities were 0.92, 0.85, and 0.81, and specificities were 0.70, 0.74, and 0.85 at the 3 thresholds, respectively. For PSG-derived models, sensitivities were 0.96, 0.90, and 0.85, and specificities were 0.82, 0.88, and 0.96, respectively. Exploratory subgroup analyses suggested performance variation across selected study and model characteristics, including region, algorithmic framework, data source, and validation method. CONCLUSIONS: AI-based tools showed generally favorable screening performance for OSA across clinically relevant AHI thresholds, although wide PIs suggest variable performance across future comparable populations and settings. By synthesizing diagnostic accuracy across 3 AHI thresholds and distinguishing non-PSG-derived from PSG-derived models, this review extends previous broad or modality-specific reviews and offers a clinically interpretable, pathway-specific basis for linking model performance to intended use. The findings may clarify potential roles for non-PSG-derived tools in front-end screening and referral prioritization and for PSG-derived models in reduced-channel assessment and sleep-laboratory workflow support. Given substantial heterogeneity, limited external validation, and low or very low certainty of evidence, prospective validation is needed before routine implementation.

Humans↗

PubMed2026

Plant species identification by genome skimming across the vascular plant tree of life.

Accurate species identification is essential for biodiversity conservation and sustainable use, yet standard plant DNA barcoding often fails to achieve species-level resolution. We present a large-scale empirical evaluation of genome skimming as a tool to improve plant species discrimination. Using standardised data from 1969 individuals representing 475 species from 32 genera across major lineages of the vascular plant tree of life, we compare conventional plastid + internal transcribed spacer (ITS) barcodes with genome skimming approaches. Standard barcoding using rbcL, matK, trnH-psbA and ITS resolved about half of species (49.3%), with six genera showing < 25% species discrimination. By contrast, genome skimming enabled the recovery of complete plastid genomes, yielding 57.6% species discrimination. It also generated sufficient nuclear genomic data for additional resolution from k-mer analysis, achieving 66.8% species discrimination - an average gain of 17.5% over standard barcodes - while eliminating cases of extreme failure (< 25% resolution). The recovery of complete plastomes and ribosomal DNAs from genome skims also ensures backward compatibility with existing barcode datasets. Our results demonstrate that genome skimming provides data that substantially improves species-level resolution across diverse plant lineages and offers a scalable, high-throughput approach for building comprehensive reference resources to support global biodiversity initiatives.

DNA Barcoding, Taxonomic↗

PubMed2026

Glaucoma filtering surgery combined with phacoemulsification in the era of new aqueous humor filtration devices: A systematic review.

We evaluate the efficacy and safety of filtering glaucoma surgeries combined with phacoemulsification (PCE)-including new aqueous humor drainage devices-compared to standalone procedures. We performed a systematic search up to March 23, 2025, including all comparative studies assessing trabeculectomy (TRAB), non-penetrating deep sclerectomy (NPDS), Xen® Gel Stent (XEN), or Preserflo® MicroShunt (PMS) combined with PCE, versus the same surgery alone. Key exclusion criteria include inadequate follow-up (less than 12-month), absence of a defined success criterion, more than 50% of loss to follow-up at 12-month, and lens extraction performed without PCE. Main outcome was surgical success at ≥ 12 months. Secondary outcomes included intraocular pressure (IOP) reduction, decrease in hypotensive medications, and rates of complications. A total of 27 studies were included for analysis. Among studies comparing TRAB/PCE with standalone TRAB, half reported similar success rates, while others favored standalone TRAB, particularly using strict IOP thresholds. Safety profiles were comparable. For NPDS/PCE, data mostly showed equivalent outcomes versus standalone NPDS, with comparable safety. In studies on XEN/PCE and PMS/PCE, results suggested similar rates of surgical success, efficacy in IOP and medication reduction, and safety compared to their stand-alone procedures. Small differences occasionally favored standalone procedures under stricter success definitions. Current evidence suggests that combined filtering glaucoma surgery provides long-term efficacy and safety comparable to standalone, though some subgroups and outcome thresholds may slightly favor standalone approaches. The limited availability of high-quality prospective trials underscores the need for further large-scale robust studies.

Humans↗

PubMed2026

Livestock Multi-Omics Integration: A Systematic Framework From Statistical Association to Causal Interpretation.

Livestock multi-omics integration is key to unraveling complex trait regulation, yet systematic, livestock-specific strategies remain scarce. This review traces the progression from single-omics accumulation to multi-dimensional integration, highlighting how large-scale genomic, epigenomic, and transcriptomic projects lay the foundation for functional dissection. We identify core impediments: extreme species diversity, marked data heterogeneity, limited sample sizes, and a pervasive reduction of multi-omics data to simplistic differential screens, resulting in low translational efficiency. We critically appraise four common pitfalls-overinterpreting correlation as causation, relegating proteomics to corroborating transcriptomics, incomplete microbiome-host integration lacking environmental context, and systematic neglect of metabolic fluxomics-and show how exposomics and fluxomics add necessary causal and dynamic dimensions. To address these, we propose a livestock-adapted three-tier analytical framework: (1) statistical association of cross-omics covariation patterns; (2) machine learning-driven feature mining and integrative modeling; and (3) causal interpretation encompassing Mendelian randomization, prior-knowledge-guided network inference, and physical causal evidence via fluxomics and metabolic control analysis. We further discuss how multimodal sequencing (single-cell, spatial, temporal) and generative AI can fundamentally mitigate heterogeneity and strengthen causal evidence. Finally, we outline future priorities in database standardization, livestock-specific benchmarking, and translational pipelines, charting a path from correlation-centric reporting to mechanistic causality and precision breeding.

Animals↗

PubMed2026

The Childhood Cancer and Leukemia International Consortium (CLIC): Expanding global collaboration in pediatric cancer etiology research.

Childhood cancers are rare, but incidence has risen modestly in countries with robust registration, partly reflecting improved diagnosis. In high-income countries, cancer is the leading cause of disease-related death in children. Marked inequities in incidence, survival, and research capacity underscore the need for large-scale collaboration to identify environmental, genetic, and contextual determinants of risk. The Childhood Cancer and Leukemia International Consortium (CLIC) was established in 2007 to study the etiology of childhood leukemia and later expanded in 2019 to include other childhood cancers, principally solid tumors. CLIC pools harmonized, individual-level data from case-control and cohort studies, obtained through interviews, record linkage (insurance claims, registries), or geographic information systems, and integrates germline genomic data where available. Membership has grown from 13 studies in 9 countries to 57 studies in 21 countries; recruitment spans the early 1960s to the present and encompasses approximately 150,000 cases across all tumor types and 300,000 controls with clinical, demographic, and exposure data, centralized via harmonized data dictionaries at the Data Coordination Center, established in 2014 at the International Agency for Research on Cancer, and supported by a secure analysis platform. Pooled analyses across diverse populations have implicated parental age, prenatal vitamin or folic acid use, mode of delivery, fetal growth, selected congenital anomalies, occupational or household exposures (e.g., pesticides), paternal smoking, and markers of early-life immune modulation (e.g., breastfeeding, daycare attendance) in leukemia risk, informing carcinogen evaluation and prevention. The integration of genetic ancestry and germline susceptibility data is clarifying ancestry-related differences in leukemia biology and outcomes, while confirming risk loci with population-specific effects. CLIC is now adding polygenic risk scores and exposomic data to refine etiologic subtyping and identify modifiable pathways, while broadening representation from underserved regions through partnership-building and capacity-strengthening.

Humans↗

PubMed2026

A flexible framework for robust and efficient Mendelian randomization with debiasing.

Mendelian randomization (MR) has been widely used to infer causal relationships between exposures and outcomes in epidemiological studies. However, classical MR assumptions can be violated when genetic variants are associated with outcomes through pathways other than the exposure, leading to uncorrelated and/or correlated pleiotropy. Additionally, measurement error arising from the inherent uncertainty in summary statistics obtained from large-scale genome-wide association studies can introduce bias into the causal effect estimate. To address these issues, we develop a debiased mixture inverse variance weighting ($\mathsf{dmIVW}$) method with three major advantages. First, it is capable of simultaneously handling various types of pleiotropy and eliminating the bias caused by uncertainty. Second, it can guard against distortion caused by invalid genetic variants while effectively harnessing their information. Third, our unified framework facilitates a fair comparison and combination of a series of submodels, encompassing several popular MR methods as special cases. Through real data applications, the effectiveness and robustness of $\mathsf{dmIVW}$ in estimating the causal effects of risk factors on common diseases are demonstrated.

Mendelian Randomization Analysis↗

PubMed2026

Upscaling Genotyping by Amplicon Sequencing With GBAS-GUI.

Genotyping by amplicon sequencing (GBAS) is a relatively low-cost approach for generating genotypic data compared with established genomic methods, making it highly scalable and particularly suitable for large-scale genetic monitoring projects. However, most existing analytical pipelines are either marker-specific, insufficiently scalable, or lacking efficient data management systems for the long-term integration of genotypic information, limiting the full potential of GBAS. Here, we address this gap by introducing GBAS-GUI (https://github.com/sonnenbe-dot/GBAS-GUI), a pipeline capable of generating GBAS-based genotypic data for a wide variety of loci at scale. GBAS-GUI integrates a graphical user interface with multiple checkpoints to improve accessibility and robustness. It implements multiprocessing architecture and a relational database that links genotypic data with associated sample metadata to enhance scalability and data management. The pipeline further enables marker screening through automated calculation of polymorphism information content (PIC) and implements a strategy to recover homologous genotypic information from paralogous loci with non-overlapping amplicon length ranges. Using multiple empirical datasets, we demonstrate substantial improvements in processing speed, database management and handling artefacts related to co-amplification of unspecific regions and duplicates of the same genomic region. We further show that incorporating the full sequence information captured by an amplicon increases marker information content beyond what is achievable with length-based genotyping alone and expands the analytical versatility of GBAS. Overall, GBAS-GUI provides a robust, scalable and versatile framework that unlocks the potential of GBAS for large-scale population genetic and phylogeographic studies.

Genotyping Techniques↗

PubMed2026

ntSynt-viz: Visualizing synteny patterns across multiple genomes.

With the explosion of chromosome-scale genome assemblies being generated in recent years, there is vast potential for comparative genomics analyses through detecting multi-genome synteny. While existing tools can detect synteny blocks between multiple genomes, their text-based outputs make it challenging to intuitively explore large-scale synteny patterns. Interpretable, information-rich and easy-to-use synteny visualization tools are imperative to enable important biological insights from the synteny block data output by the aforementioned utilities. Here, we present ntSynt-viz, a command-line tool for automated sorting, normalization and plotting of multi-genome synteny blocks. We show how ntSynt-viz provides clearer and more easily interpretable chromosome painting ribbon plots compared to the state-of-the-art tools NGenomeSyn and plotsr when evaluating synteny between 14 human genomes, and compared to NGenomeSyn when comparing 9 hoverfly genomes. As plotsr is limited to comparing genomes with equal chromosome numbers, it was not applicable to the hoverfly dataset. Furthermore, we demonstrate how ntSynt-viz can also be applied to visualize syntenic patterns encoded in pangenome graphs, using a Minigraph-Cactus graph built from 16 Drosophila genomes. We expect that ntSynt-viz will provide crucial insights into large-scale synteny patterns between divergent genomes, thereby advancing research into key evolutionary questions.

Synteny↗

PubMed2026

Cognitive behavioural therapy-based interventions on stress outcomes in pregnant women: A systematic review and meta-analysis.

BACKGROUND: Stress symptoms were the most common psychological problem in pregnancy. Cognitive behavioural therapy-based interventions are effective for antenatal depression and anxiety symptoms; but there are fewer studies for stress symptoms. OBJECTIVE: The review aims to (1) examine the effectiveness of cognitive behavioural therapy-based interventions in reducing stress outcomes (pregnancy-specific stress symptoms, generic symptoms, and objective stress) in pregnant women, and (2) identify significant moderators affecting the effectiveness of the intervention. DESIGN: Systematic review, meta-analysis, and meta-regression analysis of randomised controlled trials. METHODS: We conducted a three-step search (12 databases, 4 clinical registries, and citation searches) in English and Chinese up to July 24, 2025, by two independent reviewers. Meta-analysis, subgroup, and meta-regression analyses were performed using the R software. Quality assessment and certainty of the evidence were assessed with the Cochrane risk-of-bias tool version 2 and Grading of Recommendations, Assessment, Development, and Evaluation criteria. Publication bias was assessed using funnel plots and Egger's test. RESULTS: We included 20 randomised controlled trials involving a total of 6966 pregnant women from nine countries. Random-effects meta-analyses found that interventions significantly alleviated pregnancy-specific stress symptoms (Hedges' g = -0.84, 95% Confidence Interval, CI -1.42, -0.26, p < .01, I2 = 92.3%), reduced generic stress symptoms (g = -0.64, 95% CI -1.09, -0.20, p < .01, I2 = 87.4%) with median and large effect sizes at post-intervention. No effect was found in lowering cortisol levels (g = -0.99, 95% CI -2.58, -0.60, p = .12, I2 = 84%) at post-intervention. Subgroup and meta-regression analyses indicated that region, age of participants, use of intention-to-treat, missing data management analyses, frequency, modalities, and approaches of interventions, use of different comparators, and attrition rate were significant factors affecting the effectiveness of interventions. Subgroup analyses suggested that the intensity of intervention should be more than once per week using a blended mode among Asian populations. Multivariate meta-regression analyses indicated that both younger age (β = 0.13, p = .02) and a lower attrition rate (β = 0.03, p = .03) significantly improved the effectiveness of interventions. The overall certainty of the evidence was rated as either very low or low. CONCLUSIONS: Cognitive behavioural therapy-based interventions can supplement antenatal care to alleviate pregnancy-specific stress symptoms and generic stress symptoms, particularly in young Asian women. However, the evidence has some uncertainties. These findings should be interpreted with caution due to substantial heterogeneity. Well-designed trials on a large-scale with long-term follow-ups were needed. REGISTRATION: PROSPERO registration ID: CRD420251115913.

Humans↗

PubMed2026

Comparative efficacy and safety of bi-flanged metal stents versus lumen-apposing metal stents for endoscopic drainage of pancreatic fluid collections: a systematic review and meta-analysis.

INTRODUCTION: Pancreatic fluid collections (PFCs), particularly walled-off necrosis, are common complications of acute pancreatitis that often require endoscopic drainage. Bi-flanged metal stents (BFMS; NAGI; Taewoong Medical, Gyenoggi-do, Korea) and electrocautery-enhanced lumen-apposing metal stents (LAMS; AXIOS, Boston Scientific Corporation, Marlborough, Massachusetts, USA) are frequently used, but comparative data remain limited. This study aims to compare the efficacy and safety of BFMS and LAMS in the endoscopic drainage of PFCs. METHODS: This meta-analysis followed the Cochrane Handbook for Systematic Reviews of Interventions and Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Comprehensive database searches were conducted through November 2024 to identify studies comparing BFMS and LAMS for endoscopic ultrasound-guided drainage of PFCs. Outcomes were pooled using a random-effects model with RevMan Web, and statistical significance was defined as a P value less than 0.05. RESULTS: Three studies ( n  = 627; 329 BFMS and 298 LAMS) met inclusion criteria. No significant differences were observed between BFMS and LAMS for technical success [odds ratio (OR): 1.16; 95% confidence interval (CI): 0.55-2.43] or clinical success (OR: 0.97; 95% CI: 0.51-1.87). Similarly, there were no differences in walled-off necrosis recurrence (OR: 2.01; 95% CI: 0.17-24.02), number of direct endoscopic necrosectomy sessions (OR: 0.52; 95% CI: 0.05-5.12), or mean number of endoscopic procedures (mean difference: 0.18, 95% CI: 2.08-2.45). Adverse events were also comparable between groups, including bleeding (OR: 0.64), infection (OR: 1.18), stent migration (OR: 1.83), and stent occlusion/dysfunction (OR: 1.71). CONCLUSION: BFMS and LAMS provide equivalent efficacy and safety in the endoscopic ultrasound-guided drainage of PFCs. Either stent type represents a viable therapeutic option. Further large-scale prospective studies are warranted to refine stent selection strategies.

Humans↗

PubMed2026

TET2 promotes monocyte inflammatory activation in asthma via ALKBH5-m6A regulation and PI3K signaling: evidence from m6A-SNP and single-cell analyses.

Asthma is a complex inflammatory airway disease with strong genetic determinants, yet the functional relevance of most asthma-associated non-coding variants remains unclear. Emerging evidence suggests that N6-methyladenosine (m6A) modification may serve as a critical epitranscriptomic link between genetic variation and immune regulation. In this study, we aimed to systematically identify functionally relevant m6A-regulated genes in asthma by integrating large-scale GWAS data, m6A-SNP annotations, and single-cell transcriptomic analyses, and to investigate their roles in monocyte-driven airway inflammation. We identified TET2 as a key m6A-regulated gene associated with both asthma and lung function, which was selectively upregulated in monocytes during asthma and accompanied by activation of inflammatory and PI3K signaling pathways. Mechanistic experiments further demonstrated that inflammatory stimulation induced ALKBH5 expression, reduced m6A modification of TET2 mRNA, and increased TET2 protein levels, thereby promoting PI3K/AKT signaling and pro-inflammatory cytokine production, whereas inhibition of TET2 or ALKBH5 attenuated these effects. Collectively, these findings demonstrate that ALKBH5-mediated m6A regulation of TET2 enhances PI3K/AKT signaling in monocytes, thereby promoting inflammatory responses in asthma. Our study establishes TET2 as a key m6A-regulated gene linking genetic susceptibility to monocyte-driven inflammation, and highlights the ALKBH5-m6A-TET2 axis as a potential therapeutic target for modulating aberrant immune responses in asthma.

Humans↗

PubMed2026

Disentangling the association between chronic pain and sarcopenia-related traits: A bidirectional Mendelian randomization study.

ObjectiveThis study aimed to investigate the potential causal relationships between chronic pain and three key sarcopenia-related quantitative traits: (a) hand grip strength; (b) usual walking pace; and (c) appendicular lean mass, using bidirectional two-sample Mendelian randomization.MethodsWe conducted bidirectional two-sample Mendelian randomization using summary-level data from large-scale genome-wide association studies to assess the genetically predicted associations between chronic pain, including multisite chronic pain and chronic widespread musculoskeletal pain, and the aforementioned sarcopenia-related traits.ResultsMendelian randomization revealed that multisite chronic pain was significantly associated with an increased risk of low hand grip strength (odds ratio = 1.70; p < 0.001) and decreased usual walking pace (odds ratio = 0.81; p < 0.001); chronic widespread musculoskeletal pain was also significantly associated with decreased usual walking pace (odds ratio = 0.15; p < 0.001). Additionally, higher left hand grip strength was significantly associated with a lower risk of multisite chronic pain (odds ratio = 0.90; p< 0.001) and chronic widespread musculoskeletal pain (odds ratio = 0.99; p = 0.002); higher right hand grip strength was significantly associated with a lower risk of multisite chronic pain (odds ratio = 0.91; p = 0.002); and higher usual walking pace was significantly associated with a lower risk of multisite chronic pain (odds ratio = 0.49; p < 0.001) and chronic widespread musculoskeletal pain (odds ratio = 0.92; p < 0.001). No significant causal associations were detected for appendicular lean mass in either direction (all p > 0.05).ConclusionThis study provides genetic evidence supporting potential causal links between chronic pain and key phenotypic components of sarcopenia.

Humans↗

PubMed2026

Effectiveness of Wearable Digital Therapeutics in Improving Sleep Outcomes Among Individuals With Insomnia: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Wearable devices are increasingly used for sleep monitoring and as adjunctive treatment. Existing meta-analyses mostly pool composite digital therapies and rarely isolate stand-alone wearables or distinguish between objective and subjective end points. Whether stand-alone wearable interventions improve sleep outcomes in adults with insomnia, and which factors moderate treatment heterogeneity, remains unclear. OBJECTIVE: This study aims to evaluate the effectiveness of wearable digital interventions on sleep outcomes in adults with insomnia versus control strategies and explore moderators of effectiveness, including device-wearing position, intervention duration, and control type, using meta-regression. METHODS: This systematic review and meta-analysis was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta‑Analyses) 2020 statement and the PRISMA-S (Preferred Reporting Items for Systematic Reviews and Meta‑Analyses Literature Search Extension) guideline. Five electronic databases and clinical trial registries were searched from inception to May 18, 2026. Eligible studies were randomized controlled trials (RCTs) evaluating wearable digital interventions in adults with insomnia compared with sham, waitlist, usual care, or active control conditions and had an intervention duration of at least 1 week. Study screening, data extraction, and risk-of-bias assessment were carried out independently by 2 reviewers. Pooled estimates were calculated using a restricted maximum likelihood random-effects model with the Hartung-Knapp-Sidik-Jonkman correction. Heterogeneity was assessed using the I² statistic, and 95% prediction intervals (PIs) were calculated for the primary analyses. The certainty of evidence was rated using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) approach. RESULTS: Sixteen RCTs (N=910) were included. Wearable digital interventions were associated with a significant reduction in objective sleep-onset latency (SOL; mean difference [MD] -4.52, 95% CI -8.38 to -0.67, PI -9.52 to 0.47 min) and a significant improvement in subjective sleep efficiency (SE; MD 2.00%, 95% CI 1.90%-2.11%, PI 1.85%-2.15%). Subjective total sleep time (TST) also showed a significant increase (MD 19.11, 95% CI 2.98-35.24, PI -16.20 to 54.43 minutes). Meta-regression showed that control type, intervention duration, and device location did not explain the heterogeneity of the insomnia severity index (ISI) (R²=0). Sensitivity analysis confirmed the robustness of pooled ISI estimates, and an Egger test indicated no small-study effects (P=.07). Certainty of evidence ranged from moderate to high. CONCLUSIONS: Wearable digital interventions provide selective benefits for objective SOL, subjective SE, and subjective TST in adults with insomnia, with no improvement in overall ISI. Despite statistically significant effects on several sleep parameters, wide PIs, substantial heterogeneity, and limited study numbers indicate preliminary, nonconclusive findings. Wearables should be viewed as affordable adjunctive tools requiring further validation, not substitutes for first-line cognitive behavioral therapy for insomnia. Large-scale, long-term RCTs with standardized protocols and patient-level external validation are required to consolidate the evidence base.

Humans↗

PubMed2025

Predicting the First Onset of Suicidal Thoughts and Behaviors in Adolescents Using Multimodal Risk Factors: A 4-Year Longitudinal Study.

OBJECTIVE: Suicide is one of the leading causes of death among youth worldwide, yet existing studies that aimed to predict the first onset of suicidal thoughts and behaviors (STB) included a limited number of data modalities and/or focused on adult populations. This study aimed to prospectively predict first-onset STB across 4-year follow-ups in adolescents using an existing STB history classification model that was previously applied to baseline data and a new machine learning model with 195 biopsychosocial features. METHOD: Participants were 7,503 unrelated adolescents (54.5% female, ages 9-11 years at baseline) from the multisite, longitudinal Adolescent Brain Cognitive Development (ABCD) Study. An existing baseline STB history classification model was applied to predict longitudinal first-onset STB in adolescents compared with healthy controls and clinical controls (individuals with a mental health disorder but no STB). A new elastic net logistic regression model with 195 features was trained on data from 14 sites (n = 5,220), and the resulting top 15 features were validated at 7 independent sites (n = 2,283). RESULTS: The previously developed model to classify STB lifetime history also prospectively predicted first-onset STB in adolescents with an area under the curve (AUC) [95% CI] of 0.73 [0.70, 0.75], p < .001, compared with healthy controls and AUC [95% CI] of 0.63 [0.60, 0.66], p < .001, compared with clinical controls. The newly trained model with top 15 features performed similarly with AUC [95% CI] of 0.73 [0.71, 0.76], p < .001, and AUC [95% CI] of 0.64 [0.60, 0.66], p < .001, for the same comparison groups. The most consistent predictors across models included female sex, sleep disturbances, and maladaptive home and school environments. CONCLUSION: The models predicted first-onset STB in adolescents with moderate accuracy. This study also confirmed the roles of well-established psychological risk factors for STB and identified several novel neurocognitive and brain imaging risk factors. Future studies should validate these models in large-scale diverse samples before clinical translation. PLAIN LANGUAGE SUMMARY: This study followed over 7,500 adolescents for 4 years and tested 2 machine learning models using psychological, social, and brain data to identify those at risk of experiencing suicidal thoughts or behaviors. Both models predicted first-time suicidal thoughts or behaviors with moderate accuracy. Key risk factors that were identified included being female, experiencing sleep problems, and negative home and school environments. DIVERSITY & INCLUSION STATEMENT: We worked to ensure sex and gender balance in the recruitment of human participants. We worked to ensure race, ethnic, and/or other types of diversity in the recruitment of human participants. We worked to ensure that the study questionnaires were prepared in an inclusive way. Diverse cell lines and/or genomic datasets were not available. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science. We actively worked to promote sex and gender balance in our author group. One or more of the authors of this paper received support from a program designed to increase minority representation in science. We actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our author group. While citing references scientifically relevant for this work, we also actively worked to promote sex and gender balance in our reference list. While citing references scientifically relevant for this work, we also actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our reference list. The author list of this paper includes contributors from the location and/or community where the research was conducted who participated in the data collection, design, analysis, and/or interpretation of the work.

Adolescent↗

PubMed2026

Effects of time-restricted eating on markers of glucose metabolism and regulation in individuals with prediabetes or type 2 diabetes: a systematic review and meta-analysis of randomised controlled trials.

AIMS/HYPOTHESIS: This systematic review and meta-analysis aimed to investigate the effects of time-restricted eating (TRE) on glucose metabolism and regulation in individuals with prediabetes (fasting blood glucose of 5.6-6.9 mmol/l or HbA1c of 39-47 mmol/mol [5.7-6.4%]) or type 2 diabetes (fasting blood glucose ≥7 mmol/l or HbA1c ≥48 mmol/mol [6.5%]). METHODS: A literature search was performed in MEDLINE, Embase and CENTRAL from inception to 5 August 2025. Moreover, forward and backward citation searches were performed. Eligible studies were RCTs in adults with prediabetes or type 2 diabetes, lasting ≥2 weeks, reporting markers of glucose metabolism and regulation, comparing TRE (≤12 h eating window) with a non-time-restricted control diet. Studies involving pregnancy, other fasting regimens, or non-peer-reviewed publications were excluded. Data were pooled as weighted mean differences with 95% CIs using random-effects generic inverse variance models in Cochrane Review Manager Web, and results are presented as forest plots. The certainty of evidence was defined using Grading of Recommendations, Assessment, Development and Evaluations methodology, and risk of bias was estimated by using the Revised Cochrane risk-of-bias tool for randomised trials (RoB 2). RESULTS: Out of 2043 records identified through the database search, as well as 1249 from forward and backward citation searches, ten RCTs including 599 participants were included. The mean length of the studies was 4 months, and the eating windows ranged from 4 to 10 h per day. The pooled meta-analysis showed no overall effect of TRE on HbA1c (-3.33 mmol/mol; 95% CI -6.87, 0.20 (-0.30% points; -0.63, 0.02); p=0.06, moderate certainty). Nevertheless, following stratification by subgroups, TRE resulted in a reduction in HbA1c of 0.93 mmol/mol (-1.70, -0.17 [-0.09% points; -0.16, -0.02]; p=0.02) in individuals with prediabetes but not in individuals with type 2 diabetes (-4.68 mmol/mol; -10.08, 0.72 (-0.43% points; -0.92, 0.07); p=0.09). TRE reduced fasting blood glucose in the pooled analysis (-0.30 mmol/l; -0.53, -0.07; p<0.01, moderate certainty) as well as in the subgroup analyses in individuals with prediabetes (-0.14 mmol/l; -0.27, -0.01; p=0.03) and with type 2 diabetes (-0.48 mmol/l; -0.78, -0.17; p<0.01). Moreover, TRE lowered body weight by 1.6 kg (-2.2, -1.0; p<0.001) in the pooled analysis. The evidence was limited by imprecision arising from wide confidence intervals in some of the included studies, which may be due to small sample sizes. Lastly, the effects of TRE on markers of insulin sensitivity, beta cell function and continuous glucose monitoring measurements were inconclusive. CONCLUSIONS/INTERPRETATION: Moderate-certainty evidence indicates that TRE reduces fasting blood glucose but not HbA1c. The subgroup analyses revealed that TRE improved HbA1c and fasting glucose in individuals with prediabetes and improved fasting glucose in individuals with type 2 diabetes. Future large-scale studies should investigate long-term effects of TRE in prevention and treatment of type 2 diabetes. TRIAL REGISTRATION: PROSPERO CRD42024523591 FUNDING: This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. Three authors (JS, A-DT, THA) are employed at Steno Diabetes Center Copenhagen, a public hospital and research institution under the Capital Region of Denmark, partly funded by a grant from the Novo Nordisk Foundation.

Humans↗

PubMed2026

Application of SPI-guided analgesia in laparoscopic gynecologic surgery: a randomized controlled trial evaluating the remifentanil-sparing effect and predictive value of time-weighted SPI.

This study aimed to achieve two primary objectives: (1) to evaluate the opioid-sparing effect of Surgical Pleth Index (SPI)-directed analgesia during surgery via a randomized controlled trial (RCT), and (2) to propose and preliminarily assess a novel dynamic metric, Threshold-based Time-Weighted SPI (Tb-TW-SPI), which integrates stimulus intensity and duration, for its predictive efficacy regarding postoperative moderate-to-severe pain. Employing an RCT combined with exploratory analysis, 61 patients undergoing elective laparoscopic gynecologic surgery were randomized into an SPI-directed analgesia group or a conventional analgesia group. The primary outcome was total intraoperative remifentanil consumption. Postoperatively, an exploratory analysis of the control group data evaluated the correlation between Tb-TW-SPI and Numeric Rating Scale (NRS) pain scores in the post-anesthesia care unit (PACU), calculating its predictive value for moderate-to-severe pain (NRS ≥ 4). Results: The SPI-directed group required significantly less intraoperative remifentanil than the conventional group [median (IQR): 5.84(5.02,6.62)vs. 6.96(5.81,8.19)µg/kg/h; P = 0.016]. Postoperative pain scores did not differ significantly between groups (P > 0.05). Exploratory analysis of the conventional analgesia group revealed that Tb-TW-SPI values were significantly higher in patients with moderate-to-severe postoperative pain (NRS ≥ 4) compared to those without (P = 0.0417).The area under the ROC curve for Tb-TW-SPI predicting this pain was 0.74 (95% CI: 0.52-0.96), with 67% sensitivity and 76% specificity at an optimal cutoff of 1210. This RCT suggests that SPI-directed analgesia can safely and moderately reduce intraoperative remifentanil consumption. Furthermore, the proposed Tb-TW-SPI metric, in this exploratory analysis, suggests potential for predicting postoperative pain, though this finding requires validation in larger cohorts with higher-frequency SPI sampling, offering a new direction for SPI interpretation. Large-scale, multicenter trials are warranted to validate the predictive utility of Tb-TW-SPI. Clinical Trial Registration, China Clinical Trial Registry: ChiCTR2400088444.

Humans↗

PubMed2026

Scalable, generalizable and uncertainty-aware integration of spatial multiomics across diverse modalities and platforms with SCIGMA.

Recent advances in spatial omics technologies have enabled simultaneous profiling of transcriptomic, proteomic, epigenomic, metabolomic and imaging data at high spatial resolution, offering unprecedented opportunities to dissect tissue complexity. However, integrating these diverse and large-scale spatial multimodal datasets remains a major computational challenge. We present SCIGMA, a scalable and generalizable deep learning framework for spatial multiomics integration. SCIGMA introduces an uncertainty-aware contrastive learning objective and multiview graph neural networks to preserve modality-specific signals while learning biologically meaningful joint representations. Unlike previous methods, SCIGMA provides spatially resolved uncertainty estimates, interpretably identifying regions of biological or technical heterogeneity. SCIGMA supports integration of up to five modalities, and its modular framework is extensible to future technologies with even more modalities. It also scales to more than 1 million spatial locations, enabling analysis of high-resolution datasets such as Visium HD and Xenium Prime. We evaluated SCIGMA across 19 datasets spanning 8 modalities, 10 tissues and 9 platforms. On benchmarkable datasets, SCIGMA outperformed other methods in spatial domain detection, modality preservation, feature reconstruction and reproducibility. SCIGMA identifies biologically meaningful structures, refined spatial domains and modality-specific regulatory programs, providing a robust, flexible and future-ready solution for scalable spatial multimodal integration.

Multiomics↗

PubMed2026

ECHO: a nanopore sequencing-based workflow for (epi)genetic profiling of the human repeatome.

SUMMARY: The human genome is dominated by repetitive DNA, whose genetic and epigenetic variation plays a key role in gene regulation, genome stability, and disease. Recent advances in long-read sequencing now enable large-scale, haplotype-resolved, and DNA methylation-informative analysis of the human genome, including on previously inaccessible complex and repetitive regions. However, the comprehensive, simultaneous characterisation of the "human repeatome" remains challenging, largely due to the lack of comprehensive tools integrated in a single pipeline that can capture the full spectrum of variation across diverse types of DNA repeats. Here, we present ECHO, a user-friendly, Snakemake-based pipeline for the "(Epi)genomic Characterisation of Human Repetitive Elements using Oxford Nanopore Sequencing." ECHO provides a reproducible and scalable framework for end-to-end analysis of whole-genome nanopore sequencing data, enabling integrative but also tailored (epi)genetic analyses of the human repeatome. AVAILABILITY AND IMPLEMENTATION: ECHO is freely available at Github: https://github.com/leenput/ECHO-pipeline, with the archived version at Zenodo: https://zenodo.org/records/19068468.

Humans↗