The Lancet Rheumatology

ObjectiveTo evaluate the criterion-related and discriminant validity, test-retest reliability and minimal detectable difference of The Index of ME Symptoms (TIMES) in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) MethodsPeople with ME/CFS in the UK completed the TIMES online (n=1055). Rasch-transformed interval data and parametric statistics were used: Pearson correlations (with the ME severity scale); analysis of variance; intra-class correlations (ICC) and standard error of measurement of ICC measured criterion-related and discriminant validity, test-retest reliability and minimal detectable difference respectively. ResultsHighly significant (P<0.001) moderate (r=0.400-0.528) correlations were seen between the TIMES scales and severity of ME/CFS except the gastro-intestinal and immune systems scales (r= 0.315 and 0.302 P<0.001 respectively). Discriminant validity was demonstrated with significant differences in TIMES scores between all five levels of ME severity, except between levels 4 and 5 in some cases, which were underpowered due to the small group numbers. Test-retest reliability was excellent (ICC>0.7, p<0.001) except the cranial nerves and immune system scales which were good (ICC = 0.681 and 0.669, p<0.001) and minimal detectable difference was excellent (3.95-17.45%). ConclusionsThe Index of ME Symptoms (TIMES) scales are valid, reliable, sensitive assessments of symptoms in ME/CFS. They are freely available for use.

ObjectiveTo develop and psychometrically evaluate an assessment of symptoms in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) MethodsAn initial symptom list was devised from the relevant literature with the patient and clinician advisory groups. An online survey with 85 symptom items in eight domains was completed by people with ME/CFS. Each item had two response structures (assessing symptom frequency and severity on five-point scales). Rasch analysis assessed each domain for unidimensionality, targeting, internal reliability, item fit and local dependency. ResultsSurvey data (n=721) indicated various item anomalies and inter-item dependencies, leading to item re-formatting or removal. The frequency and severity-based responses broadly replicated each other, and a four-point response format appeared more appropriate than a five-point response format. Following Rasch-based scale amendments, a revised version with a single four-point response format was re-administered to test the modifications. Validation data (n=354) showed the modified scale had an improved response structure and functionality across all domains, satisfying Rasch model assumptions. Additionally, domain-level super-items allowed for a summated total score along with sub-scales summarising neurological and autonomic symptoms, again satisfying Rasch model assumptions. ConclusionsThe Index of ME Symptoms (TIMES) and its associated sub-scales and domain scales are stable, valid assessments of symptoms in ME/CFS.

BackgroundAlthough ST-segment elevation myocardial infarction (STEMI) and non-STEMI (NSTEMI) are very similar regarding pathophysiology and clinical treatments, especially NSTEMI comprises a much more heterogenic group of patients and underlying diseases. We therefore aimed to assess the treatments and outcomes of both entities in a large contemporary cohort. MethodsPatients with STEMI and NSTEMI between 01/2010 to 12/2018 were identified from the largest German Health Insurance (AOK, {approx}26 million members). Patient demographics, their hospital course, adherence to guideline-directed drug therapy and overall survival were assessed. ResultsIn total 544,529 patients (mean age 74, IQR 62-82), one third of whom had a STEMI. Chronic kidney disease, peripheral arterial disease, and heart failure were more common in patients with NSTEMI. Patients with STEMI were more likely to get coronary angiograms and percutaneous coronary interventions. Although STEMI more frequently led to cardiogenic shock, the rate of serious cardiac events was lower. Mortality was higher for STEMI only within the first 30 days, whereas long-term survival rates were better. The combination of statins, angiotensin converting enzyme inhibitors /angiotensin receptor blockers, beta blockers, and oral anticoagulants or antiplatelet agents was associated with higher overall survival in patients with STEMI (hazard ratio [HR] 0.20; 95% confidence interval [95%CI] 0.18 - 0.24; p<0.001) or NSTEMI (HR 0.30; 95%CI 0.28 - 0.33; p<0.001). Nevertheless, the prescription rates decreased over time, particular in patients with NSTEMI. ConclusionClear differences between STEMI and NSTEMI were observed regarding short-and long-term survival. Guideline-recommended therapy improved long-term survival, but decreased during the follow-up period.

Background and AimFibromyalgia is an idiopathic chronic widespread pain syndrome affecting 2-4% of the general population globally. Besides widespread fibromyalgia pain, morning stiffness, associated neurologic as well as sleep problems are also reported. Disease is more prevalent in females of middle-age group with low socioeconomic status, thus deteriorating overall productivity and psychosocial health. There is no permanent cure of the disease. This study aimed to explore, validate and assess the effect of four weeks of supervised yogic intervention on pain status, quality of life, sleep, cortical excitability, flexibility and range of motion in fibromyalgia patients, as compared to standard therapy. MethodCase-control study, interventional study and assessor-blined randomized controlled trial, conducted in 120 fibromyalgia patients (60 yoga group: 60 waitlisted controls) and 60 age-matched healthy controls. Pain was assessed subjectively, using questionnaires and objectively, using quantitative sensory testing and ELISA. Sleep and quality of life were assessed using common and disease specific decsiptors. Flexibility and range of motion was assessed using sit and reach box, lateral goniometry and modified Schobers test. Transcranial magnetic stimulation on M1 was used to assess corticomotor excitability of participants. Study parameters were assessed at baseline and after four weeks of the intervention. ResultsA significantly poor sleep, flexibility and quality of life was reported in the fibromyalgia patients due to excruciating pain (VAS = 6.92{+/-}0.12); corticomotor function was also abnormal in the patients, which were restored after four weeks of yogic intervention. On subjective and objective assessment of pain, we found significant relief and improvement in pain status in the yoga group as compared to the waitlisted controls. Fibromyalgia impact, sleep, quality of life and flexibility were also found solely better in fibromyalgia patients undergoing yogic interventions. Cortical parameters, specifically RMT, MEPs and MEP recruitment curves showed a significant improvement in yoga group as compared to waitlisted controls. ConclusionFour weeks of regular and supervised yogic intervention may ameliorate pain, improve flexibility and range of motion and changes cortical plasticity in the Indian cohort of fibromyalgia patients, as compared to standard therapy. Yoga-based interventions can also improve overall quality of life and sleep impairmentsby reducing catastrophization and fibromyalgia impact.

ObjectiveTo apply large language models (LLMs) to Reddit posts referencing systemic lupus erythematosus (SLE) to identify patient-expressed unmet medical needs, symptom experiences, and healthcare challenges, demonstrating how AI-enabled social media listening complements traditional patient-experience research. MethodsWe extracted 4,633 posts from ten SLE-related or health-focused Reddit communities using the public Reddit API (October-November 2025). After removing duplicates, promotional content, and posts with insufficient information, 2,603 posts remained. A thematic codebook was developed through manual review of 300 posts and iteratively refined. Two LLMs (Gemini 3.0 and GPT-5.2) were evaluated for automated thematic labeling using percent agreement, Cohens {kappa}, and a human-annotated reference set (n=100). The best-performing model was used to quantify theme prevalence, followed by qualitative review of representative narratives. ResultsGPT-5.2 demonstrated higher performance (F1=0.844) than Gemini 3.0 (F1=0.811), with substantial inter-model agreement across main themes (mean {kappa}=0.71). Posts reflected multidimensional experiences. The most frequent subtheme was Advice Seeking (84.1%), followed by Emotional Coping (55.6%). Common symptom-related themes included Pain (37.2%), Other Symptom Presentations (37.6%), Fatigue (24.7%), and Acute or Worsening Flares (30.2%). Diagnostic uncertainty was prominent, including confusion about laboratory results (24.0%) and emotional impact of uncertainty (33.0%). Qualitative review highlighted emotional distress, reliance on peer communities for interpretation of symptoms and labs, and difficulty managing complex treatment regimens. ConclusionLLM-enabled social media listening offers a scalable method for synthesizing large volumes of unstructured patient narratives, providing timely insights into lived experiences and unmet needs among individuals discussing lupus online. Findings align with established qualitative literature while highlighting persistent gaps in patient education, communication, and care coordination. This analytical framework can be applied across disease areas to support patient-centered care, measurement development, and evidence generation relevant to therapeutic and health-services research. What is already known on this topicO_LIPeople living with systemic lupus erythematosus (SLE) experience substantial unmet needs related to diagnostic uncertainty, symptom burden, emotional distress, medication challenges, and healthcare system barriers. C_LIO_LITraditional qualitative methods (e.g., interviews, focus groups, surveys) capture valuable patient perspectives but are limited by small sample sizes, recall bias, and restricted question frameworks. C_LIO_LISocial media listening has emerged as a promising way to collect real-time patient insights, and recent regulatory guidance acknowledges its value as patient experience data. However, systematic, scalable analysis of large patient-generated datasets has historically been constrained by analytic burden and variability. C_LI What this study addsO_LIThis study is among the first to apply state-of-the-art large language models (LLMs) to a large corpus of SLE-related social media posts, enabling scalable thematic analysis of thousands of patient narratives. C_LIO_LIIt provides a validated methodological framework for using dual-LLM agreement, human-annotated references, and performance benchmarking (precision, recall, F1) to ensure reliability in automated thematic labeling. C_LIO_LIFindings reveal a multidimensional patient burden consistent with prior studies while uncovering persistent gaps in patient education, confusion around laboratory testing, care coordination challenges, and heavy reliance on peer communities for advice. C_LIO_LIThe approach demonstrates that LLM-enabled social media listening can generate timely, granular, patient-prioritized insights at a scale unattainable by traditional methods. C_LI How this study might affect research, practice, or policyO_LIResearch: Establishes a reproducible, scalable framework for integrating LLM-based thematic analysis into patient-focused evidence generation, accelerating insight extraction from large unstructured datasets across disease areas. C_LIO_LIClinical practice: Highlights actionable gaps in patient education, communication, and care coordination, informing interventions to improve clinical encounters, shared decision-making, and symptom management support. C_LIO_LIPolicy and regulatory science: Demonstrates how social media-derived patient experience data, when paired with rigorous quality controls, can complement formal qualitative studies and support patient-focused drug development, measurement development, and health-services planning. C_LI

Autoimmune inflammatory myopathies (AIM) with prominent B cell aggregates (BCM) on muscle biopsy is an uncommon finding. We aimed to compare the characteristics and clinical course of patients with BCM on muscle biopsy to those without and characterize B cell infiltrates in the muscle of these patients. We performed a retrospective study of subjects with AIM in the Canada Inflammatory Myopathy Study (CIMS) cohort to identify cases with BCM on muscle biopsy, which was defined as [&ge;]30 CD20+ cells/aggregate. AIM cases without BCM that encompassed the broader spectrum of AIM, namely dermatomyositis, overlap myositis and inclusion body myositis were selected as controls. Descriptive statistics were used to compare BCM cases and controls. Cyclic immunofluorescence (Cyc-IF) was performed to characterize inflammatory infiltrates and B cell structures. We included 69 subjects (mean age at diagnosis 51{+/-}16 years, 77% females): 22 BCM, 24 dermatomyositis, 14 overlap myositis, and inclusion body myositis. Most BCM subjects (18/22, 82%) had an associated autoimmune disease: 12 (55%) had systemic sclerosis, 5 (23%) rheumatoid arthritis and one (5%) systemic lupus erythematosus/systemic sclerosis overlap. Extra-muscular features found in BCM patients included arthritis (50%), interstitial lung disease (43%), Raynauds phenomenon (32%), and dermatomyositis rash (27%). Two patients (9%) had facial muscle weakness and one (5%) had positive anti-AChR autoantibodies. In BCM subjects, upper extremities were weaker than lower extremities in 7/21 (33%) of cases. Neck flexor weakness was frequent (17/22, 77%), while neck extensor weakness was uncommon (1/15, 7%). Cyclic immunofluorescence (Cyc-IF) spatial analysis of BCM biopsies displayed many features akin to tertiary lymphoid structures. Findings suggest possible involvement of both the traditional germinal center reaction and the extrafollicular pathway in BCM. In conclusion, in this series of myositis with B cell aggregates reported to date we found clinical similarities (i.e., associated with overlapping autoimmune diseases) and differences (i.e., muscle weakness distribution) with previous reports. The discovery of tertiary lymphoid structures on spatial analysis of muscle biopsies of BCM patients provides novel insight into its pathophysiology and potential therapeutic targets.

ObjectivesTo screen the entire genome for genes associated with risk for lateral epicondylopathy and improve understanding of underlying biological mechanisms and inform future research aimed at risk stratification and personalized prevention and treatment strategies. MethodsA genome-wide association study was conducted using UK Biobank data. Lateral epicondylopathy cases were identified based on electronic health records from individuals of European ancestry. Logistic regression tested associations between single-nucleotide polymorphisms and disease status, adjusting for sex, age, height, weight and ancestry principal components. Previously-identified candidate genes from the literature were also tested for association with lateral epicondylopathy. ResultsAmong 20,390 cases of lateral epicondylopathy, two loci reached genome-wide significance: one comprising 144 linked SNPs and one single SNP. The first locus, led by rs13127477 (p=7.7x10-12; OR 0.93, 95% CI 0.91 to 0.95), is located near three SIBLING genes (IBSP, MEPE and SPP1) involved in extracellular matrix remodelling at fibrocartilaginous entheses. The risk allele was associated with increased SIBLING gene expression, suggesting that excessive entheseal matrix remodelling contributes to disease susceptibility. The second locus was defined by rs138254824 (p=3.69x10-8; OR 3.42, 95% CI 2.23 to 5.25) near NEDD9 and TMEM170B. Previously reported collagen gene associations were not replicated. ConclusionIn the first genome-wide screen for lateral epicondylopathy, two loci were identified. These loci provide insight regarding the pathophysiology of lateral epicondylopathy and a roadmap for preventing and treating this injury with personalized medicine. Summary BoxO_ST_ABSWhat is already known on this topicC_ST_ABSLateral epicondylopathy is a common and disabling overuse tendon condition, yet its genetic basis has remained poorly characterised, with prior studies limited to small candidate gene analyses. What this study addsThis study provides the first genome-wide association analysis of lateral epicondylopathy, identifying two risk loci on chromosomes 4 and 6 and implicating SIBLING genes (IBSP, MEPE, and SPP1) involved in entheseal extracellular matrix remodelling. How this study might affect research, practice or policyThese findings offer new biological insight into disease susceptibility and challenge previously reported collagen gene associations.

ObjectiveQuantitative computed tomography (QCT) can automatically quantify parenchymal abnormalities on chest CT imaging using deep learning. We leveraged QCT to detect pulmonary abnormalities in patients with early rheumatoid arthritis (RA) compared to healthy controls. MethodsWe analyzed high-resolution CT chest imaging from participants with early RA in the prospective, multicenter, SAIL-RA study and healthy non-smoking controls from the COPDGene study. A deep learning classifier quantified the percentage of normal lung, interstitial abnormalities, and emphysema for each participant. We compared the percentage of QCT features between early RA participants and healthy comparators and examined associations using multivariable linear regression. ResultsWe analyzed 200 participants with early RA (median RA duration 8.3 months, mean age 55.7 years, 74.5% female) and 104 healthy controls (mean age 62.0 years, 68.3% female). The median percentage of interstitial abnormalities on QCT was 3.7% (IQR 2.1, 6.1%) for early RA and 1.6% (IQR 0.8, 2.4%) for healthy controls (p<0.0001). Early RA was associated with 9.3% less normal lung on QCT than healthy controls, adjusted for age and sex (p<0.0001). Among RA participants, QCT interstitial abnormalities were associated with older age (multivariable {beta}=0.1 per year, 95%CI 0.07-0.2, p<0.0001) and higher DAS28-ESR (multivariable {beta}=0.6 per unit, 95%CI 0.01-1.3, p=0.046). ConclusionParticipants with early RA had less normal lung and more interstitial abnormalities on a deep learning-derived QCT measure than healthy controls. These results suggest that loss of normal lung is already present in early RA and emphasizes the urgent need for strategies to preserve lung health in RA.

Individuals who have serum elevations of anti-cyclic citrullinated protein (anti-CCP) antibodies are at risk for developing rheumatoid arthritis (RA), yet immunologic factors that lead to a transition from pre- to clinical RA remain unclear. Here, we used materials from anti-CCP antibody-positive individuals enrolled in a clinical trial that evaluated the efficacy of hydroxychloroquine to prevent clinical RA, and performed multi-modal single-cell profiling (transcriptome, surface proteins, T/B-cell receptor sequencing, and chromatin accessibility) on samples obtained at baseline and at RA onset in those who developed clinical RA (Converters) or follow-up point in matched Nonconverters. At both baseline and follow-up, Converters had expansions of peripheral helper T (Tph) cells and CD8+ T cells expressing GZMK and GZMB, along with elevated potentially autoreactive T-cell receptors in CD4+ T cells compared to Nonconverters. Induction of age-associated B cell signatures was observed in B cells of Converters prior to RA onset. Epigenetic profiling further identified chromatin accessibility changes in Converters over time, particularly within myeloid and NK cells. Lastly, predictive modeling using baseline immune features, including Tph cells, GZMK+XCL1+ CD8+, and GZMB+CD57+ CD8+ T cells, together with clinical features such as anti-CCP3 levels, RF-positivity, and HLA shared epitope status, stratified RA risk and predicted time to onset. These findings define immune endotypes in pre-RA that could serve as targets for future preventive interventions and be used to stratify the risk of developing clinical RA in anti-CCP antibody-positive individuals.

BackgroundOsteoarthritis (OA) is a leading cause of disability worldwide, yet no licensed therapies can prevent or slow its progression. We aimed to identify potential targets for disease-modifying OA drugs (DMOADs) by integrating genetic and differential protein expression (DPE) evidence. MethodsWe evaluated genetically predicted perturbations of plasma protein levels using cis-protein quantitative trait loci (cis-pQTLs) across three large European cohorts (UK Biobank Pharma Proteomics Project, deCODE, and Fenland) and outcome data from the Genetics of Osteoarthritis Consortium, covering 11 OA phenotypes. DPE analyses were performed in 44,789 UKB participants, comparing 2,920 protein measurements between OA cases and controls, supported by sensitivity analyses. Proteins identified through genetic and/or DPE approaches were further assessed in downstream analyses. FindingsIn total, 305 proteins showed evidence of association with OA through genetically predicted perturbations, with 81 supported by colocalisation across datasets. DPE analyses identified 605 proteins associated with at least one OA phenotype, of which 450 (74{middle dot}4%) remained robust after sensitivity testing. Several novel targets were identified, including PPP1R9B, PCSK7, and ITIH4. Integration of both approaches prioritised 5 proteins, 4 of which demonstrated druggable potential, including 3 high-confidence candidates DLK1, TNFRSF9, and OGN. Downstream analyses highlighted key biological pathways and candidate compounds with potential for repurposing. InterpretationThis large-scale study combines genetic and DPE evidence to prioritise candidate DMOAD targets. Findings reinforce established biology while revealing novel proteins and pathways, providing a foundation for therapeutic development in OA. FundingWL is supported by the Guangzhou Elite Project (project no. JY202314). SSZ is supported by The University of Manchester Deans Prize, Arthritis UK Career Development Fellowship (grant no. 23258). This work is supported by the NIHR Manchester Biomedical Research Centre (NIHR203308). Research in contextO_ST_ABSEvidence before this studyC_ST_ABSCirculating proteins have been linked to osteoarthritis (OA) in observational studies, supporting their potential as biomarkers and drug targets. However, differential protein expression analyses are vulnerable to confounding and reverse causation. Mendelian randomisation (MR) studies using proteomic GWAS instruments have suggested causal roles for several circulating proteins in OA-related traits and highlighted druggable candidates. However, many analyses relied on earlier OA GWAS data (e.g., Genetics of Osteoarthritis Consortium 1{middle dot}0) and smaller proteomic GWAS datasets, and typically did not integrate MR findings with large-scale differential protein expression. As a result, it remains unclear how well genetically predicted protein effects align with observed protein expression in OA, and how robust prioritised targets are when replicated across proteomic data from multiple cohorts. Added value of this studyThis study integrates large-scale proteomic MR and differential protein expression (DPE) analyses across multiple OA phenotypes using the largest datasets to date. By combining genetic evidence with observed protein dysregulation in population-based cohorts, we strengthen causal inference and improve robustness of target prioritisation. This approach allows us to distinguish proteins that are likely to play a causal role in OA from those that reflect downstream disease processes, and to highlight targets with greater translational relevance than identified by either method alone. Implications of all the available evidenceTaken together, our findings support a causal role for a subset of circulating proteins in OA and demonstrates the value of integrating genetic and observational proteomic data for target prioritisation. Proteins supported by both MR and DPE are more likely to represent biologically relevant drivers of disease and actionable therapeutic targets. This integrated framework reduces false positives arising from confounding or reverse causation and provides a more reliable basis for drug development, biomarker discovery, and patient stratification in OA.

BackgroundColorectal carcinoma (CRC) remains a significant cause of cancer morbidity and mortality worldwide. Right- and left-sided tumours differ in clinical, morphological, and molecular features. Microsatellite instability-high (MSI-H) tumours, often right-sided, are associated with distinct histopathological characteristics and prognostic implications. In Sri Lanka, molecular MSI testing is currently unavailable, highlighting the need for alternative predictive approaches. ObjectivesGeneral Objective: To describe the clinical and histopathological characteristics of right- and left-sided colorectal cancers in a Sri Lankan cohort and evaluate their usefulness in predicting MSI-H tumours. Specific ObjectivesTo compare clinicopathological features between right- and left-sided colorectal cancers. To predict MSI-H tumours based on clinicopathological features, including assessment of the MsPath score and histological parameters. To determine interobserver agreement for MsPath score application in selecting cases for MSI assessment. MethodsA retrospective analytical study was conducted on 156 colorectal carcinoma resections diagnosed between 2019 and 2021 at the National Hospital of Sri Lanka. Histopathological evaluation included tumour differentiation, mucinous and medullary features, tumour-infiltrating lymphocytes (TILs), and Crohn-like reaction. MsPath scores were calculated based on age, tumour site, and histological parameters. Immunohistochemistry (IHC) for PMS2 and MSH6 was performed on 46 selected cases to assess mismatch repair (MMR) status. ResultsOf 156 cases, 41 (26%) were right-sided and 115 (74%) left-sided. The majority were moderately differentiated adenocarcinomas (89%). Histological features suggestive of MSI-H including TILs (29%) and Crohn-like lymphoid reaction (23%) were more frequent in right-sided tumours. MsPath scores ranged from 0.0 to 5.9, with 50% of cases scoring below 1. Among the 46 cases evaluated by IHC, MMR deficiency was observed predominantly in higher MsPath score categories, and a significant association was found between MsPath score category and MMR status ({chi}{superscript 2} = 13.76, df = 2, p = 0.001). Interobserver agreement for MsPath scoring was substantial (Kappa = xx, indicating reproducibility). ConclusionRight-sided colorectal carcinomas in this Sri Lankan cohort more frequently exhibited histological features suggestive of MSI-H, including mucinous differentiation, TILs, and Crohn-like lymphoid reaction. MsPath scoring correlated with MMR deficiency in the IHC-tested subset, but its predictive value is limited without immunohistochemical confirmation. IHC using a two-antibody panel (PMS2 and MSH6) proved to be a feasible, cost-effective, and reliable method for MSI screening in resource-limited settings. This study is the first comprehensive evaluation of right-versus left-sided colorectal carcinomas and MsPath utility in Sri Lanka, underscoring the need for expanded IHC capacity, larger cohorts, and integration of molecular testing for MSI validation.

BackgroundInterleukin-6 (IL-6) is a cytokine that plays a key role in systemic hyperinflammation and may mediate the relationship between acute COVID-19 and severe long-term outcomes such as Long COVID or death. IL-6 modulating drugs may reduce patients risk of severe post-COVID-19 outcomes. MethodsWe conducted an emulated target trial in a retrospective cohort of patients with moderate-to-severe rheumatoid arthritis who were prescribed IL-6 receptor antagonists (sarilumab or tocilizumab, pooled treatment) or other biologic agents (anakinra or baricitinib, pooled comparator) in 2022. We compared the 12-month cumulative incidence of mortality and Long COVID (diagnosed and probable) between groups using Super Learner and targeted maximum likelihood estimation, adjusting for covariates of interest. ResultsIn our cohort of 3,553 patients, we found that prescription of IL-6 receptor antagonists was associated with a lower 12-month cumulative mortality (adjusted relative risk (aRR) 0.40, 95% CI 0.27, 0.59), diagnosed Long COVID aRR 0.42, 95% CI 0.23, 0.78), and probable Long COVID (aRR 0.71, 95% CI 0.61, 0.83), compared to prescription of other biologic agents, among rheumatoid arthritis patients. ConclusionsIL-6 receptor antagonists may prevent the incidence of severe post-COVID-19 outcomes, such as Long COVID or mortality. This supports the hypothesis that IL-6 may be a mechanistic biomarker of COVID-19 sequelae and that acute COVID-19 severity may mediate this relationship.

BackgroundRetrieval-augmented generation (RAG) frameworks such as RAPID [1] have demonstrated that staged planning and retrieval grounding improve long-form text generation. However, most implementations remain similarity-driven and open-domain, lacking the epistemic safeguards required for biomedical synthesis, where mechanistic completeness, temporal governance, traceability, and explicit gap classification are essential. ObjectiveTo develop and evaluate a topology-aware, graph-augmented retrieval framework for structured biomedical narrative synthesis, and to position it as a domain-constrained evolution of staged RAG aligned with structural principles of digital evidence-based medicine (dEBM). MethodsWe implemented a two-layer architecture operating on a closed, version-controlled corpus of 11,861 peer-reviewed text chunks on iron deficiency. A metadata-constrained vector retriever (RAG01) was extended with a Graph-RAG (RAG02) overlay (RAG02) constructed from chunk-level entity extraction and weighted co-occurrence networks (30 nodes; 118 directed edges). Topic planning was organized through predefined mechanistic axes functioning as structured hypothesis probes. Retrieval was performed under identical deterministic constraints (top-k = 5; cosine threshold = 0.50; publication year [&ge;] 2023), and graph diagnostics--including local connectivity, induced subgraph density, modular overlap, and multi-hop stability--were used to distinguish retrieval insufficiency from corpus-level evidentiary scarcity. ResultsIn a case study of obesity-associated iron deficiency, the entity network exhibited a centralized regulatory topology with hepcidin as a high-connectivity hub. Axis-based retrieval combined with graph auditing consistently reinforced an inflammation-mediated hepcidin pathway linking obesity to iron deficiency, while alternative mechanisms lacked stable multi-hop embedding. Compared with vector-only retrieval, graph augmentation preserved semantic alignment and increased mean cosine similarity from 0.673 to 0.694 while reducing similarity dispersion (SD 0.056 to 0.035) under identical constraints. Graph activity ratio was 1.00 in the temporally filtered corpus. ConclusionsBy integrating mechanistic axis decomposition, topology-aware auditing, causal scaffolding, and expert-driven iterative refinement, the proposed framework implements selected structural constraints inspired by evidence-based medicine within a controlled digital synthesis environment. The approach advances retrieval-augmented generation beyond similarity-based summarization toward a reproducible model of topology-aware biomedical evidence interrogation with implications for AI-assisted systematic reviews.

ObjectivesMosaic chromosomal alterations (mCAs) increase with age and are associated with many diseases, including autoimmune diseases. The associations between mCAs and systemic sclerosis (SSc) and its clinical subtypes have not been explored. MethodsWe recruited study subjects from two independent datasets (Set 1: 635 SSc, 4,401 controls; Set 2: 347 SSc, 2,170 controls) and detected mCAs (Loss, LOH, Gain, and mLOX) from their peripheral blood samples. Logistic regression analyses were conducted with covariates in each cohort, and the results were meta-analyzed. We also conducted stratified analyses by age groups, the age at disease onset, clinical phenotypes based on the skin lesions, autoantibody profiles, the presence of complications. ResultsWe observed a trend of increased Loss in SSc, especially in old age (P=0.0063). The association of Loss was strengthened in certain subtypes of SSc, including lcSSc (OR=2.22, P=0.019) and SSc with vascular complications (digital ulcers, pulmonary hypertension, or renal crisis, OR=3.30, P=0.0054). The effect sizes of Loss increased in patients with high cell fractions (CFs). We also observed that mLOX was significantly associated with SSc, lcSSc, and ACA-SSc only for subjects with high CFs. mLOX was significantly associated with lcSSc and ACA-SSc even compared with dcSSc and ATA-SSc, respectively. These associations were consistently observed in each of the two data sets. Finally, we identified majority of the associations of Loss were mainly driven by SSc with late age at onset. ConclusionsLoss and mLOX were significantly and differentially associated with SSc and its subtypes, underscoring potential phenotype-specific contributions of mCAs. WHAT IS ALREADY KNOWN ON THIS TOPICO_LISystemic sclerosis (SSc) is a heterogeneous disease, with its phenotypes and disease outcomes varying among patients. C_LIO_LIAge-related mosaic chromosomal alterations (mCAs) in blood and subsequent clonal haematopoiesis are associated with various adverse health outcomes. C_LIO_LImCAs have also been linked to several immune-mediated diseases, such as LORA, and hence may influence immune cells and their functions. C_LI WHAT THIS STUDY ADDSO_LIAutosomal copy-number loss (Loss) is increased in SSc in aged subjects. C_LIO_LILoss was associated with lcSSc, ACA-SSc. ILD-SSc, and VC-SSc in a dose-dependent manner of cell fraction. C_LIO_LImLOX was associated with SSc and its subtypes only in patients with high cell fraction. C_LIO_LILate-onset SSc and its subtypes show stronger associations with Loss with higher effect sizes compared to non-late onset SSc. C_LI HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICYO_LIOur study facilitates further research to recapitulate the current findings in independent cohorts as well as in different ancestries. C_LIO_LIIncorporating profiles of Loss and mLOX in blood into conventional clinical information may enable a better stratification of SSc patients and the development of a better management strategy. C_LIO_LIFurther experimental approaches, such as whole genome sequences and single-cell C_LI RNA sequences, that investigate the underlying molecular mechanisms of phenotypic heterogeneity of SSc driven by Loss and mLOX are also warranted.

Gout is driven by an interleukin-1{beta}-mediated intense innate immune reaction to monosodium urate (MSU) crystals (MSUc). In cell culture models of inflammatory gout there is a synergistic effect of phagocytosis of MSUc and TLR2 and TLR4 activation by agonists such as free fatty acid and lipopolysaccharide (LPS) in NLRP3-inflammasome activation and IL-1{beta} secretion. A substantial number of gout patients do not report a dietary trigger, and observational studies associate airborne particulate matter with incident gout and flares. Airborne particulate matter contains LPS and airborne-derived particulate matter stimulates IL-1{beta} secretion in cell culture. We hypothesized that air-borne particulate matter could co-stimulate, with MSUc, IL-1{beta} secretion and inflammation. We tested the hypothesis using MSUc with extracted airborne PM4 in human cells (the THP-1 monocyte cell line, primary human monocytes and PBMCs) or carbon black particles with ozone (CB+O3) in a murine foot-pad injection model of gout. There was strong NLRP3-inflammasome-dependent co-stimulation of IL-1{beta} secretion in THP-1 cells with PM4+MSUc and a moderate additive effect in primary human PBMCs. However, there was no added effect on IL-1{beta} secretion of PM4 in isolated primary human monocytes. Inhalation of CB+O3 persistently exacerbated MSUc-induced murine paw inflammation, with an increase of alveolar/lavage macrophages that contained CB+O3 particles and increased lavage expression of IL-1{beta}. In conclusion, airborne-derived PM4 particulate matter enhanced MSUc-induced IL-1{beta} secretion in THP-1 cells and PBMCs. Combined with exacerbation of MSUc-induced inflammation by fine particulate matter in in vivo experiments, these data provide evidence that exposure to fine particulate matter may play a role in the etiology of gout.

ObjectiveTo clinically evaluate a digital biomarker, the Finger Fold Index (FFI), derived from the ratio of joint diameter to finger fold surface area in hand photographs, for assessing joint swelling in inflammatory arthritis. MethodsSmartphone hand photographs from two routine care cohorts of patients with rheumatoid (RA) and psoriatic arthritis (PsA) were analyzed using a machine learning pipeline for automated detection and processing of proximal interphalangeal (PIP) joints. The FFI was clinically evaluated by correlation with joint swelling scores (0-3) and DAS28-CRP. A healthy cohort was used to establish FFI reference ranges, which were then compared to the arthritis cohorts. ResultsA total of 1275 PIP joint images of 124 arthritis patients and 53 healthy individuals were included. FFI values correlated with swelling scores in the arthritis population with r = 0.443 (95% CI 0.384-0.498). A correlation was observed between the mean FFI and DAS28-CRP dichotomized at 3.2 (r = 0.310, 95% CI 0.123-0.475). FFI values exceeding the healthy reference ranges were associated with swelling (Cramers V = 0.400-0.631; p < 0.001). ConclusionFFI values derived from hand photographs showed a significant association with clinical joint swelling and disease activity in RA and PsA patients. Longitudinal studies are needed to assess sensitivity to change and to establish whether this biomarker can be reliably used for remote patient monitoring.

ObjectiveAlthough trauma-focused psychotherapies are effective for posttraumatic stress disorder (PTSD), recovery under routine outpatient conditions remains variable. We examined whether participation in a structured Specialty Care (SC) model integrating clinician specialization, flexible treatment density, and coordinated navigation was associated with accelerated PTSD recovery compared with standard outpatient care. MethodsWe conducted a retrospective matched cohort study (2024-2025) of U.S. adults with active PTSD symptoms (PTSD Checklist for DSM-5 score [&ge;]31) receiving care through an employer-sponsored digital mental health platform. Access to SC was determined by employer benefit design. Propensity-score matching with weighting balanced cohorts on baseline severity and demographics. Primary outcomes included longitudinal PTSD symptom trajectories and time to recovery, remission, and reliable improvement. Secondary outcomes assessed depressive symptoms (PHQ-9). Linear mixed-effects and Cox proportional hazards models were applied. ResultsThe matched sample included 356 SC and 9,409 standard care participants. SC participants received higher treatment intensity, including greater session volume and faster early follow-up, and greater care navigation engagement. SC participation was associated with steeper PTSD symptom decline ({beta} = -1.3 per log-week, p < .001) and a higher likelihood of recovery (hazard ratio = 1.31; 95% CI, 1.10-1.57). At 12 weeks, predicted recovery was 29% in SC versus 23% in standard care. Depressive symptoms improved in both groups, without significant differences in time to categorical recovery. ConclusionsUnder routine outpatient conditions, a structured SC model was associated with accelerated PTSD recovery, suggesting that reorganization of outpatient delivery may improve real-world outcomes.

BackgroundAcute lymphoblastic leukemia is the most common childhood malignancy; however, survival remains highly heterogeneous across regions, particularly in low- and middle-income settings. In geographically vulnerable areas such as the Brazilian Amazon, structural barriers related to health system organization, centralization of specialized services, and continuity of care may substantially influence treatment trajectories and mortality. This study aimed to examine health system and epidemiological determinants of mortality among patients with acute lymphoblastic leukemia in Amazonas, Brazil. MethodsThis retrospective cohort study included 393 patients diagnosed with acute lymphoblastic leukemia between 2016 and 2021 at the state referral center for hematologic diseases in Amazonas, Brazil. Sociodemographic, clinical, laboratory, and health system-related variables were analyzed. Multivariate logistic regression models were used to identify factors associated with mortality. Spatial analyses described the geographic distribution of cases, and overall survival was evaluated using Kaplan-Meier curves. ResultsThe cohort was predominantly pediatric, with a substantial proportion of adolescents and young adults. Most patients presented with high-risk clinical and laboratory features at diagnosis. Mortality occurred in 48.5% of patients and was strongly associated with age at diagnosis, with higher odds of death among adolescents, young adults, and individuals aged 51-60 years. Geographic concentration of specialized services and treatment-related trajectories were closely linked to survival patterns. ConclusionMortality from acute lymphoblastic leukemia in the Brazilian Amazon remains high and is primarily influenced by age-related vulnerability and health system factors rather than baseline sociodemographic characteristics. These findings underscore persistent regional inequalities in access to specialized care and highlight the need for health system strengthening to improve cancer survival in geographically vulnerable settings.

Academic institutions privilege norms of continuous productivity and uninterrupted availability, creating conformity pressures that systematically disadvantage those who deviate from an implicit template of the ideal academic. This study explores how doctoral students and faculty in the health sciences perceive the reproduction of social homogeneity. Semi-structured interviews were conducted with nine participants at a German university hospital. Data were analysed using reflexive thematic analysis with extended idiographic engagement. Participants perceived homogeneity as reproduced through external exclusion, enacted by others through networks, normative expectations, or institutional arrangements, and self-exclusion, whereby individuals withdrew, reduced visibility, or reshaped identity in anticipation of exclusion ( anticipatory compliance). Across both processes, the tacit norm of the ideal academic organised access and belonging. Supportive supervision and visible role models were perceived as partial buffers but did not structurally alter underlying norms. Interpreted through the social identity threat framework, these findings are consistent with a self-reinforcing cycle: structural homogeneity may generate identity-threatening environments that activate concealment and withdrawal, concentrating homogeneity further. These findings suggest that achieving substantive inclusion requires challenging the structural conditions that naturalise presence, mobility, and availability as measures of academic success.

Lipoedema is a chronic adipose tissue disorder mainly affecting women with excess subcutaneous fat deposition on the lower limbs, associated with pain and tenderness. There is often a family history of lipoedema, suggesting a genetic origin, but the contribution of genetics is not well studied. We conducted a genome-wide association study (GWAS) for this disorder in a clinically ascertained cohort from Spain and performed a meta-analysis with the UK lipoedema cohort GWAS. We then used the results of this study as a replication of the inferred UK Biobank "lipoedema phenotype" study. Whilst our meta-analysis alone did not identify any genome-wide significant associations, our clinical cohorts provide support for three loci identified through the UKBB study: the chr2q24.3 GRB14-COBLL1 locus (rs6753142, PMETA=1.64x10-6), chr6p21.1 VEGFA locus (rs4711750, PMETA=8.99x10-7) and the chr5q11.2 ANKRD55-MAP3K1 locus (rs3936510, PMETA=1.67x10-5). We identify numerous rare SNPs with strong association signals in our meta-analysis (P<1x10-6) with support in both UK and Spanish datasets, three of which also show nominal support in the UKBB (P<0.05). These findings provide a starting point towards understanding the genetic basis of clinical lipoedema and demonstrate the utility of the interplay of large-scale biobanks genetic data and clinically ascertained cohorts to elucidate the genetic architecture of lipoedema.