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PubMed2026

Methylation profiling in CNS tumor diagnostics: a single-centre real-world experience from Central Europe.

Genome-wide DNA methylation profiling has transformed neuro-oncology by providing an objective, machine learning-based taxonomy that mitigates interobserver variability and refines the histo-molecular criteria of the current WHO classification. We evaluate the real-world diagnostic performance and clinical utility of this modality in a prospective, consecutively accrued three-year cohort of 291 central nervous system (CNS) tumors across a mixed adult-pediatric population. Successful profiling was completed in 95.9% of cases. Using the Epignostix classifier, a high-confidence diagnostic match (calibrated score [CS] ≥ 0.84) was achieved in 70.3% of analyzable samples, while 26.5% returned lower-confidence scores (≥ 0.3 to < 0.84) and only 3.2% remained completely unclassifiable (CS < 0.3). When integrated into a comprehensive diagnostic framework, methylation profiling provided clinically useful results in 81.1% of cases, establishing diagnoses in 70 cases submitted for molecular subclassification and resolving diagnostic uncertainty or prompting major revisions in 149 histologically challenging tumors. Within truly ambiguous lesions, integration of methylome data dictated tumor grade modifications in 38.8% of cases (upgrading in 29.4% and downgrading in 9.4%), shifting patient risk stratification. Crucially, over half (52.7%) of the lower-confidence cases yielded meaningful clinical integration when supported by histomorphology and ancillary genetic or immunohistochemical markers, demonstrating that rigid score cutoffs should not dictate assay failure. Discrepant or misleading classifications occurred in 1.9%. Updating bioinformatic pipelines from version 11b4 to 12.8 rescued multiple ambiguous entries, increasing overall clinical utility to 84.1%. These findings demonstrate that integrating computational epigenomics with classical neuropathology enhances diagnostic precision, while highlighting the ongoing need for careful clinical-pathological correlation.

Central nervous system tumors↗

PubMed2026

Robot-assisted versus freehand cannulated-screw fixation for femoral neck fractures: a systematic review of technical, clinical and adoption outcomes.

Robot-assisted guidance may improve the technical precision of percutaneous cannulated-screw fixation for femoral neck fractures. Whether these procedural advantages translate into better clinical outcomes remains uncertain. We compared robot-assisted and conventional freehand fixation in adults with femoral neck fractures. MEDLINE, Embase and CINAHL were searched from inception to 15 July 2026 without language restrictions. Google Scholar was used only as a supplementary search source, together with forward and backward citation searching. Comparative studies of robot-assisted versus freehand fluoroscopy-guided cannulated-screw fixation were included. Risk of bias was assessed using RoB 2 and ROBINS-I, with the Newcastle-Ottawa Scale used as a complementary appraisal of non-randomised studies. Random-effects meta-analyses included prediction intervals and prespecified sensitivity analyses. The protocol was registered prospectively (PROSPERO CRD420261465038). Sixteen comparative studies involving 1,293 participants were included. Of these, 597 underwent robot-assisted fixation and 696 underwent freehand fixation. Two studies reporting random allocation and 14 non-randomised studies were included in the study. Robot-assisted fixation was associated with fewer guide-wire manipulations, greater screw-placement accuracy and 13.9 fewer fluoroscopic acquisitions per procedure (95% confidence interval [CI] -20.3 to -7.5). Earlier radiographic healing and modestly higher final Harris Hip Scores were also observed. Pooled estimates suggested lower risks of union failure, avascular necrosis and composite complications. Fluoroscopy duration, overall operative time and reoperation did not differ significantly. Heterogeneity was substantial for several continuous outcomes, with prediction intervals crossing the null for several estimates, indicating that the magnitude of benefit varied considerably between studies. Some clinical associations were also sensitive to eligibility-restricted analyses. Robot-assisted cannulated-screw fixation improves technical execution compared with freehand fixation. Patient-important clinical superiority and economic value have not been established, and evidence concerning learning curves, operator acceptability and system reliability remains insufficient. Current evidence does not support routine widespread adoption; adequately powered multicentre randomised trials incorporating economic and implementation evaluation are required.

Humans↗

PubMed2026

Astigmatic vector outcomes after FS-LASIK versus SMILE for high myopic astigmatism: a single-center retrospective comparative cohort study without cyclotorsion compensation.

PURPOSE: To compare astigmatic correction vector outcomes between femtosecond laser-assisted in situ keratomileusis (FS-LASIK) and small-incision lenticule extraction (SMILE, also termed Keratorefractive Lenticule Extraction, KLEx) without intraoperative cyclotorsion compensation in patients with high myopic astigmatism (- 2.00 to - 3.75 D), and to clarify procedure-specific correction tendencies under this non-standardized alignment protocol. METHODS: This single-center retrospective comparative cohort study enrolled 155 eyes (one eye randomly selected per patient) that underwent FS-LASIK (80 eyes) or SMILE/KLEx (75 eyes) for high myopic astigmatism correction from January 2023 to July 2024 in Beijing Fenglian Jiayue Lige Clinic. Intraoperative cyclotorsion compensation was intentionally disabled to isolate inherent procedural astigmatism correction characteristics. Standardized Alpins vectorial analysis was performed at 3 months and 12 months postoperatively. PRIMARY ENDPOINT: 12-month Alpins correction index (CI). Multivariable propensity score adjustment was applied to mitigate confounding by clinical treatment selection bias. Statistical multiplicity control was implemented for secondary vector and visual outcomes. RESULTS: Baseline demographic, refractive, corneal and ocular biometric parameters were balanced between groups after propensity matching. No statistically significant intergroup differences were detected in uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), residual cylinder, safety index or efficacy index at 3 and 12 months (all P > 0.05). Under the non-cyclotorsion-compensated protocol, significant intergroup differences were identified in the magnitude of surgically induced astigmatism (SIA), correction index (CI), and magnitude error (ME) at both follow-up timepoints (all P < 0.0001). Target induced astigmatism (TIA), difference vector (DV), index of success (IOS), and angle error (AE) magnitudes were comparable between groups (all P > 0.05). The vector mean axis of DV differed significantly between groups at 3 and 12 months (Watson-Williams circular test, all P < 0.0001). No reoperations were documented in clinic medical records for either cohort. No standardized dry eye questionnaires, tear film testing or corneal nerve density metrics were collected to quantify dry eye adverse events; only unstructured clinical notes were reviewed for complication screening. CONCLUSIONS: Under surgical alignment without cyclotorsion compensation, FS-LASIK and SMILE/KLEx both yielded acceptable visual and refractive safety/efficacy for high myopic astigmatism (- 2.00 to - 3.75 D) at 1-year follow-up, but demonstrated divergent astigmatism correction tendencies: FS-LASIK exhibited relative astigmatism overcorrection (vector mean DV: - 0.35 ± 0.43 D × 91°, CI > 1), while SMILE/KLEx showed relative undercorrection (vector mean DV: - 0.21 ± 0.53 D × 12°, CI < 1). These correction biases are specific to the study's manual limbal alignment protocol without cyclotorsion tracking and cannot be generalized to modern optimized surgical platforms equipped with automated cyclotorsion compensation. Residual refractive errors across both groups are likely multifactorial, including differential corneal stromal healing responses, divergent femtosecond/excimer laser tissue modification mechanisms, and uncorrected intraoperative ocular cyclotorsion.

Humans↗

PubMed2026

From prediction to mechanism: Explainable AI uncovers plasma and CSF proteomic signatures of Alzheimer's disease.

Alzheimer's disease (AD) plasma and cerebrospinal fluid (CSF) proteomics can distinguish AD from cognitively normal controls, but the generalizability of machine learning performance and the recurrence of biological signals across datasets require cautious interpretation. We developed an explainable artificial intelligence framework spanning two fluids and four ADNI proteomic datasets, covering 2082 modality specific samples, all analysed internally within ADNI. Phase 1 analysed plasma using a 119 analyte NULISA and targeted UPENN panel (n = 727; 216 CE, 511 controls). Phase 2 extended the analysis to CSF using SOMAscan7k, TMT-MS and targeted SET2, with Elecsys Aβ42, Aβ40, total tau and p-tau181 as anchor biomarkers. Only SOMAscan was subject-independent relative to Phase 1 plasma; TMT-MS and SET2 overlapped with Phase 1 for 96.0% and 97.7% of subjects and therefore are not independent replication cohorts. Under subject-level splits with fold internal preprocessing, we compared Elastic Net, Explainable Boosting Machines and gradient boosted trees with SHAP-based explanations. Among the candidate pipelines, we selected the pipeline with the highest held-out test ROC AUC for each platform; the selected values were 0.927 in plasma and 0.954-0.973 across the three CSF datasets. Because the same held out test performance was used for pipeline selection and headline reporting, these are optimistically selected single-holdout estimates, not unbiased estimates of generalizable or clinical performance. Explanations identified five recurring biological axes within ADNI: cholinergic (ACHE), tau/14-3-3 (YWHAG, YWHAZ, YWHAB, YWHAE), neuro-axonal (NEFL, NEFH), microglial/complement (CHIT1, SMOC1, CHI3L1, C7, CFH) and synaptic (NPTXR, NPTX2, DLG4, SYT5, VSNL1, ELAVL2). CSF analyses showed synaptic vesicle-cycle enrichment (q = 2 × 10-6), and CSF YWHAG correlated strongly with total tau (ρ = 0.87). Cross-fluid directional concordance was modest overall (54-57%) but increased to 73-80% among mapped analyte/protein rows reaching q < 0.05 in CSF. These findings provide hypothesis-generating, internally supported evidence within ADNI. Independent external cohorts with locked pipelines are required to evaluate generalizable performance and biological reproducibility; the overlapping TMT-MS and SET2 analyses should not be interpreted as independent replication.

Alzheimer Disease↗

PubMed2026

The efficacy of modified psychodynamic psychotherapy for patients with schizophrenia-spectrum disorders in Germany: a prospective, single-centre, assessor-blinded, parallel-group, randomised controlled trial.

BACKGROUND: People with schizophrenia-spectrum disorders have difficulties in interpersonal functioning that remain insufficiently addressed by standard care. Despite long-standing clinical use, psychodynamic psychotherapy has little empirical support compared with other psychosocial treatments for people with schizophrenia-spectrum disorders. We evaluated the efficacy of Modified Psychodynamic Psychotherapy for Schizophrenia (MPP-S), a manualised treatment tailored to the interpersonal vulnerability characteristic of this population, plus treatment as usual (TAU), compared with TAU alone. METHODS: This prospective, single-centre, assessor-blinded, parallel-group, randomised controlled trial was conducted at the Psychiatric University Hospital of the Charité at St Hedwig Hospital in Berlin, Germany. Participants were outpatients aged 18-64 years who were diagnosed with schizophrenia or schizoaffective disorder and exclusion criteria included organic brain disorder, somatic illness affecting cerebral function, and current or past alcohol or illicit drug misuse requiring addiction-specific treatment. Participants were randomly assigned 1:1 in blocks of ten to MPP-S (minimum 30 sessions) plus TAU or TAU alone. Outcome assessors were masked, but participants and therapists were not. The primary outcome was psychosocial functioning, measured using the Mini International Classification of Functioning, Disability and Health Rating for Limitations of Activities and Participation in Psychological Disorders (Mini-ICF-APP) and evaluated at baseline and prespecified post-treatment (24 months) and follow-up (36 months) assessments. Analyses followed the intention-to-treat principle. Linear mixed models were used to analyse incomplete longitudinal data under a missing-at-random assumption. People with lived experience were not formally involved in the design, conduct, or reporting of this study. This trial was preregistered at ClinicalTrials.gov (NCT02576613) and is complete. FINDINGS: From Oct 12, 2015, to Dec 7, 2021, 130 participants (57 [44%] female and 73 [56%] male) were randomly assigned to either MPP-S plus TAU (n=65) or TAU alone (n=64). One participant withdrew consent to data analysis. Regarding the primary outcome of psychosocial functioning, linear mixed models showed significant group-by-time interactions favouring the intervention: estimated marginal means indicated adjusted between-group differences in Mini-ICF-APP scores of -3·45 (95% CI -5·51 to -1·40; p=0·0011) at 24 months and -4·07 (-6·19 to -1·94; p=0·0002) at 36 months. The frequency of adverse events was similar between groups. There were three serious adverse events: two participants died by suicide (one in the MPP-S plus TAU group who did not start psychotherapy and one in the TAU alone group) and one participant in the MPP-S plus TAU group was admitted to a forensic hospital. INTERPRETATION: MPP-S added to TAU could improve psychosocial functioning compared with TAU alone. Our findings suggest efficacy and possible long-term benefits of psychodynamic psychotherapy for schizophrenia-spectrum disorders and indicate its potential role alongside other psychotherapeutic and psychosocial treatments. FUNDING: Berlin Institute of Health, Deutsche Gesellschaft für Psychoanalyse, Psychotherapie, Psychosomatik und Tiefenpsychologie, International Psychoanalytic University Berlin, and Köhler-Stiftung.

Humans↗

PubMed2026

Clinical applications of digital twin technology in In Vitro Fertilisation.

BACKGROUND: Digital twin technology, originating from aerospace and manufacturing industries, has emerged as a transformative tool in healthcare. In vitro fertilisation (IVF) faces persistent challenges including suboptimal embryo selection, unpredictable treatment outcomes, and limited personalisation of protocols. Despite advances in assisted reproductive technology, existing literature exhibits fragmentation: artificial intelligence applications in embryo selection, ovarian stimulation, and endometrial assessment have been developed independently without systematic integration into comprehensive treatment frameworks. Digital twin technology offers unprecedented opportunities to create virtual replicas of biological systems, enabling real-time monitoring, predictive modelling, and personalised treatment strategies. AIM: This narrative review aims to critically examine the current applications of digital twin technology in IVF, evaluate its potential benefits and limitations, synthesize existing evidence into an integrative conceptual model, and identify future directions for implementation in reproductive medicine. METHOD: A comprehensive narrative review was conducted using PubMed, Scopus, Web of Science, and IEEE Xplore databases. A narrative review approach was selected over systematic review to accommodate the heterogeneity of evidence types in this emerging field, including theoretical frameworks, simulation studies, and proof-of-concept implementations that would be excluded from systematic reviews. Search terms included "digital twin," "IVF," "in vitro fertilisation," "assisted reproductive technology," "embryo selection," and "predictive modelling." Studies published between 2015 and 2025 were included, focusing on original research articles, systematic reviews, and proof-of-concept studies describing digital twin applications in reproductive medicine. RESULTS: Digital twin technology in IVF demonstrates significant potential across multiple domains including embryo development simulation, ovarian response prediction, endometrial receptivity modelling, and personalised stimulation protocols. Current applications integrate artificial intelligence, machine learning algorithms, time-lapse imaging, and omics data to create comprehensive virtual models. Early evidence suggests improvements in embryo selection accuracy, ovarian response prediction, and treatment protocol optimization, though large-scale randomized controlled trials remain limited. Implementation challenges include data integration complexity, computational requirements, regulatory considerations, and validation requirements. CONCLUSION: Digital twin technology represents a paradigm shift in IVF practice, offering personalised, predictive, and precision medicine approaches. This review synthesizes existing evidence to propose an integrative conceptual model for digital twin implementation across the IVF treatment spectrum, identifies critical knowledge gaps, and establishes research priorities to advance clinical translation. Despite current limitations, continued advancement promises improved success rates and patient outcomes.

Humans↗

PubMed2026

Transcranial Magnetic Stimulation for Patients with Exposure Therapy Resistant Obsessive-Compulsive Disorder (TETRO): Study Protocol for a Multicenter Randomized Controlled Trial.

BACKGROUND: Obsessive-compulsive disorder (OCD) is a disabling mental disorder, characterized by obsessions, compulsions, and substantial morbidity. Approximately 50% of adults with OCD fail to achieve satisfactory outcomes from first-line treatments, such as exposure therapy with response prevention (ERP), with or without medication. This leads to chronic social, educational, and occupational impairment. While invasive procedures such as deep brain stimulation are available for severe, treatment-refractory cases, a need remains for less invasive alternatives. Repetitive transcranial magnetic stimulation (rTMS), a noninvasive intervention, shows promise in reducing OCD symptoms. Unlike in depression, rTMS is not yet reimbursed for OCD in the Dutch healthcare system. OBJECTIVE: This study examines the efficacy and cost-effectiveness of low-frequency (1Hz) rTMS targeting the presupplementary motor area (pre-SMA) compared to sham rTMS as an adjuvant treatment to ERP in adults with OCD with inadequate response to first-line treatment. METHODS: A total of 250 adults with OCD will be enrolled in this multicenter randomized controlled trial. Participants will be randomly assigned to ERP combined with either active or sham 1Hz rTMS over the pre-SMA. Treatment is administered 4 times weekly for at least 5 weeks (20 rTMS-ERP sessions), with optional extension of 1 to 2 weeks, up to 28 rTMS-ERP sessions. Clinical assessments occur at baseline, weekly during treatment, posttreatment, and at 3, 6, and 12 months follow-up. Participants undergo pre- and posttreatment (functional) (MRI) scans, including a symptom provocation task. Blood sampling takes place pre- and posttreatment and at 3-month follow-up. The primary outcome is OCD severity at posttreatment, as measured by the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS). Secondary outcomes include functional improvement, quality of life, and societal costs. Pretreatment symptom profiles, genotype, and brain network topology will be analyzed as predictors of response and relapse risk. Pre-to-post treatment change in blood-based and magnetic resonance (MR)-based neuroplasticity markers will help explore differential mechanisms between ERP alone and combined rTMS-ERP. We expect that the verum rTMS protocol will be cost-effective compared to sham-rTMS. RESULTS: Recruitment started in April 2022, and as of February 2026, 201 participants have been enrolled. Posttreatment assessments are projected to be completed in December 2026, with final one-year follow-up evaluations anticipated by the end of 2027. CONCLUSIONS: To our knowledge, this study is the first adequately powered randomized controlled trial examining efficacy, cost-effectiveness, and mechanism of action of rTMS for OCD as adjuvant therapy to ERP. In case of efficacy and/or cost-effectiveness, it will pave the way for rTMS as insured health care for adults with OCD in the Netherlands, and possibly other European countries. Furthermore, this trial will provide insight into the mechanisms of treatment response to intensive ERP, with and without adjunctive rTMS, as well as potential side effects, individual variability, and long-term outcomes in adults with OCD.

Humans↗

PubMed2026

Analysis of end-stage renal disease mediated by cuproptosis-related genes.

OBJECTIVE: The complex pathophysiological mechanism of end-stage renal disease (ESRD) has not been fully understood. Cuproptosis is a newly discovered type of programmed cell death. Therefore, this study attempts to clarify the relationship between cuproptosis-related genes (CRGs) and the phenotype of ESRD. MATERIALS AND METHODS: The National Center for Biological Information Gene Expression Omnibus database was applied to obtain the GSE37171 dataset comprising whole-genome microarray analysis of peripheral blood samples. A 3 : 1 case-control design was employed with 75 ESRD patients and 20 healthy controls who were frequency-matched for age, sex, and ethnicity. Based on differentially expressed genes (DEGs) and genes related to cuproptosis, CRGs were identified. Thereafter, we explored two different subpopulations based on the cuproptosis gene and analyzed their expression and immune infiltration. Genes specific to the CRG cluster were identified through the weighted gene co-expression network analysis algorithm, and the best prediction model was determined and verified by four machine learning methods. RESULTS: The study identified 14 differentially expressed CRGs, among which ATP7B, SLC31A1, LIAS, LIPT1, DLD, MTF1, CDKN2A, DBT, and DLST had relatively high expression levels in the ESRD samples. Compared with the control group, expression levels of FDX1, DLAT, PDHA1, PDHB, and GLS were significantly lower in the ESRD group, and CRGs played a key role in the regulation of immune infiltration in ESRD. Two cuproptosis-related molecular clusters were identified in the ESRD samples. Cluster2 was more correlated with the immune infiltration of ESRD. By analyzing the intersection points between CRG cluster and key genes of ESRD, a total of 888 specific DEGs were identified. Functional differences related to specific DEGs were further explored using gene set variation analysis. Five significant genes (SMC5, USP47, USP53, AGA, and DMXL1) were identified by the support vector machine model as key predictors for ESRD disease risk, achieving an area under the curve (AUC) of 1.00 in internal validation. However, external validation in independent cohorts is required prior to clinical application. Individual gene analysis showed an AUC > 0.81 in discriminating ESRD patients from healthy controls, and the expression of all 5 genes in ESRD patients was significantly lower than in the control group. CONCLUSION: This study clarified the relationship between CRGs and the phenotype of ESRD, analyzed their specific roles in the immune microenvironment, and obtained a predictive model, providing new insights for the study of its potential therapeutic targets.

Humans↗

PubMed2026

Stage-specific ROMO1 in rheumatoid arthritis: predictive immune insights into the MIF pathway and HLA-DR/IL2RA axis via integrated GWAS, transcriptomic, single-cell, and spatial profiling.

Emerging evidence links reactive oxygen species modulator 1 (ROMO1), a key mitochondrial ROS regulator, to rheumatoid arthritis (RA) pathogenesis. However, its exact mechanism remains elusive given the conflicting evidence about its specific function. We used a four-level integrative framework combining multi-omics data and literature‑supported mechanistic inference. At the genetic level, Mendelian randomization (MR) was performed to explore potential causal relationships between ROMO1, IL2RA, HLA-DR, MIF, and RA risk, followed by differential expression analysis and machine learning-based feature selection to identify key mROS genes. The temporal expression dynamics of ROMO1 were assessed in RA progression. At the cellular and tissue levels, we integrated single-cell RNA sequencing and spatial transcriptomics to map cell-type-specific expression and synovial localization of ROMO1-related immune cells and pathways. Finally, our multi-omics findings were contextualized with literature-supported mechanistic inference. (1) MR results were consistent with a potential protective effect of ROMO1 on RA (OR = 0.52) and its potential regulation of risk factors IL2RA (OR = 0.46) and HLA-DR (OR = 0.40). Conversely, IL2RA (OR = 1.42), HLA-DR (OR = 1.88), and MIF (OR = 1.17) were positively associated with RA risk. Additionally, ROMO1 was identified as a top candidate diagnostic predictor with stage-specific dynamics: downregulated in the early but upregulated in the late/remission stages. (2) Single-cell RNA sequencing showed ROMO1's cell-specific expression in CD14+ HLA-DR+ CD74+ monocytes and CD4+ IL2RA+ T cells. Cell communication analysis further suggested that these cells may participate in MIF pathway regulation. Spatial transcriptomics subsequently identified that ROMO1-related cells localized to synovial pathological regions, with MIF pathway changes correlated with RA progression. (3) Finally, literature-supported mechanistic inference suggests that ROMO1 may modulate mROS levels to promote anti-inflammatory M2 macrophage polarization, which could theoretically contribute to reduced systemic inflammation and the alleviation of multi-organ decline in RA. This integrated multi-omics investigation, supported by literature-based mechanistic inference, suggests ROMO1 as a stage-dependent biomarker candidate and potential immune regulator in RA.

Humans↗

PubMed2026

Methods for defining equity-stratifying variables: a systematic review of validation studies.

BACKGROUND AND OBJECTIVE: Disease burden is often disproportionally higher among those who are socially disadvantaged by factors defined in the PROGRESS-Plus framework (ie, Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, and Social capital, with "Plus" covering features like age and disability). The accuracy and applicability of case definitions to identify these variables from administrative and clinical health data are unknown. We conducted a systematic review to explore how equity-stratifying variables, as categorized by the PROGRESS-Plus framework, have been defined and validated in epidemiologic studies using administrative health, population-level, or electronic health record (EHR) data. METHODS: Medline, EMBASE, CINAHL, Web of Science, and Google Scholar were searched from the inception of the databases to 2024 for validation studies of equity-stratifying variables in adults using administrative health datasets, health registries, or EHR data. Titles and abstracts, followed by relevant full-text articles, were screened in duplicate by two reviewers for eligibility. The data sources utilized, algorithms employed, and their associated performance measures were extracted and synthesized from included studies. Given substantial heterogeneity in study design, equity-stratifying variable definition, and performance metrics, meta-analysis was not possible. RESULTS: Of the 9099 unique citations screened, 188 full texts were reviewed and 116 were included in this review. Most studies were published between 2019 and 2024 (n = 64, 55%) and were validation studies of race/ethnicity definitions that used race/ethnicity codes or surname list algorithms (n = 66, 57%). No studies examined religion. Regarding the reported performance measure estimates, the race/ethnicity/culture/language equity-stratifying variables category had the largest variability across sensitivity, positive predictive value (PPV), and Cohen's Kappa. Occupation validation studies had the lowest variation in sensitivity and PPV. CONCLUSION: Despite an increasing number of publications reporting on the validation of equity-stratifying variables relevant to the PROGRESS-Plus framework, performance measures varied widely across studies. The significant heterogeneity in equity-stratifying variable definitions and methods used to validate them support the need for further rigorous validation of equity-stratifying variables in administrative and clinical health data. PLAIN LANGUAGE SUMMARY: Disease burden is often higher in people who experience financial hardships, lower level of education, discrimination due to race/ethnicity, and unstable housing. These social factors can be considered health equity factors and are important for understanding health inequalities. Health researchers often use large datasets, such as hospital or electronic health records (EHRs), to study these health equity factors. However, it is not clear how accurately these data sources capture information about people's social circumstances and how these factors are defined. In this study, we reviewed existing research to understand how health equity factors have been defined across health data sources and how accurate they are at measuring aspects of health equity and social disadvantage. Of the more than 9000 studies we identified, we included 116 that met our criteria for this systematic review. Most included studies focused on identifying race and ethnicity, often using codes or surname-based methods. We found that the accuracy of these methods varied widely across studies, meaning results may not always be reliable or comparable. Overall, our findings show that there are inconsistencies in how social factors are defined and measured in health data. This makes it difficult to fully understand and address health inequalities using routinely collected health data. More work is needed to develop and validate better quality and more consistent methods for capturing these important social factors.

Humans↗

PubMed2026

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry↗

PubMed2026

Effectiveness of a Web-Based Educational eHealth Platform on Women's Health Literacy About Phthalate Exposure: Randomized Controlled Trial.

BACKGROUND: Phthalates are environmental endocrine-disrupting chemicals widely used in plastics, cosmetics, food packaging, and personal care products. Women may experience frequent exposure through everyday consumer and household products. Improving phthalate-related health literacy may support informed exposure-reduction decisions; however, conventional health education provides limited opportunities for repeated, interactive, and individually tailored learning. OBJECTIVE: This randomized controlled trial evaluated the effectiveness of an eHealth educational intervention (Phthalates Free) in improving women's overall and domain-specific phthalate-related health literacy and examined the association between platform engagement and health literacy outcomes. METHODS: A double-blind randomized controlled trial was conducted in the outpatient department of a regional teaching hospital in Taipei, Taiwan. A total of 114 women were randomly assigned to an intervention group (n=58) receiving a 6-month eHealth platform-based education program and a control group (n=56) receiving conventional paper-based education. Assessments were conducted at baseline (T0), 3 months (T1), and 6 months (T2). The Phthalate Health Literacy Scale (10 items; α=.90, content validity index=0.93) measured overall and domain-specific literacy (health care, disease prevention, and health promotion). Longitudinal outcomes were analyzed using generalized estimating equations based on all available observations according to participants' original randomized assignments, with adjustment for waist circumference and pregnancy history. Analysis of covariance (ANCOVA) was used to compare 6-month outcomes after adjustment for baseline scores. Platform engagement and perceived usability were assessed using back-end analytics and the System Usability Scale (SUS). RESULTS: At 6 months, the intervention group showed a significantly greater increase in total health literacy than the control group (+9.93 points, Wald χ²1=17.74; P<.001). Domain analyses revealed significant improvements in health care (+1.52; P=.001), disease prevention (+1.32; P=.001), and health promotion (+1.12; P=.001) domains. ANCOVA confirmed the between-group difference at T2 after adjusting for baseline scores (F1,109=11.43; P=.001; adjusted mean difference=7.15, 95% CI 2.96-11.34). Engagement analysis showed that high-engagement users (n=10) scored significantly higher in overall health literacy (t55=-3.00; P=.004) and all domains than general users. The SUS results (mean 84.7, SD 5.2; n=46, 79.3%) indicated high perceived usability. CONCLUSIONS: The Phthalates Free eHealth educational intervention significantly improved women's overall and domain-specific health literacy over 6 months. Higher platform engagement was associated with better health literacy outcomes. The intervention may serve as a practical adjunct to nurse-led education in outpatient and community settings by providing accessible, continuous, and evidence-based guidance on reducing phthalate exposure.

Humans↗

PubMed2026

Effectiveness of Caregiver-Mediated Spoken Language Interventions for Children Under Five at Risk of Developmental Language Disorder: A Systematic Review and Meta-Analysis.

BACKGROUND AND AIMS: Caregiver-mediated interventions are commonly used by Speech and Language Therapists to support early language development. Developmental Language Disorder (DLD) is associated with reduced quality of life throughout the lifespan. Understanding factors that predict intervention success is essential for developing appropriate, cost-effective therapy provision for the approximately 12% of preschool children who present with early markers for Developmental Language Disorder (DLD). This systematic review and meta-analysis examined the effectiveness of caregiver-mediated spoken language interventions for under-fives at risk of DLD, and factors influencing intervention effectiveness. METHODS: A systematic review following PRISMA guidelines was conducted. Five electronic databases were searched to identify experimental studies comparing caregiver-mediated spoken language interventions to control conditions in under-fives presenting with risk factors for DLD. Risk factors included prematurity, socioeconomic factors, caregiver language development concerns, and formal or informal language screening or assessment scores. Twenty-six experimental studies with 1407 child participants were included in qualitative synthesis. Meta-analysis was performed on nine Randomised Controlled Trials involving 947 children. RESULTS: Effectiveness was examined for outcomes including child language gains, child wellbeing, inclusion and attainment. Meta-analysis indicated a significant effect of caregiver-mediated spoken language interventions on language outcomes compared to treatment-as-usual, non-language intervention or waitlist control conditions. Non-language outcomes were evaluated via qualitative synthesis. Interventions significantly improved language development trajectories for under-fives presenting with risk factors or early markers for DLD. CONCLUSION AND IMPLICATIONS: This review contributes to the growing evidence base demonstrating that caregiver-mediated interventions can positively impact language development and wellbeing outcomes for children under five at risk of DLD. These findings support the implementation of caregiver-mediated environmental language interventions in clinical practice to maximise accessibility and cost-effectiveness while delivering optimal outcomes for vulnerable populations. WHAT THIS PAPER ADDS: What is already known on this subject Previous research on caregiver-mediated spoken language interventions has highlighted gaps in the evidence regarding the impact of risk factors, demographic characteristics, dosage and intervention components on child language outcomes. Developmental Language Disorder has relatively high population prevalence, estimated at 7%. Prevalence is associated with risk factors including low household socioeconomic status (SES), prematurity and late language emergence. In contrast to its prevalence, there is low public and professional awareness of DLD and a low diagnostic rate. Therefore, a strengthened evidence base and additional insights into the factors affecting success of family-based interventions is important in order to increase the effectiveness of service provision and care planning for this underserved population. Timely and effective intervention with young children presenting with early markers for DLD has the potential to offer lifelong improvement to their wellbeing, inclusion and attainment outcomes. Recent systematic reviews of the effectiveness of caregiver-mediated language interventions had differences in population age range and diagnostic inclusion criteria. What this paper adds to existing knowledge Our review examines the effectiveness of caregiver-mediated early spoken language interventions on child language, attainment and wellbeing, and on caregiver self-efficacy and adherence to language support strategies. Our population was children under five presenting with risk factors for Developmental Language Disorder, in the absence of other neurodevelopmental or genetic conditions such as intellectual disability or autism. This review adds depth and detail to the evidence base supporting the effectiveness of caregiver-mediated spoken language interventions in improving outcomes for this population of young children, and factors that influence their success. What are the potential or actual clinical implications of this work? The high prevalence of Developmental Language Disorder, estimated at around 7% of the population, and the strong association with risk factors including low SES, prematurity and late language emergence, coupled with the low awareness of DLD and low diagnostic rate, mean that a strengthened evidence base and additional insights into the factors affecting success of family-based interventions can increase the effectiveness of service provision and care planning for this population. Timely and effective intervention in this group of young children has the potential to improve wellbeing and attainment outcomes across the lifespan. This review contributes to our understanding of how to implement cost-effective, socially valid and maximally engaging partnership working with families of young children at risk for DLD.

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