Life Sciences

Introduction: Neuroinflammation is a known pathophysiologic mechanism in multiple sclerosis and a proposed mechanism in fibromyalgia and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Positron Emission Tomography (PET) imaging of the translocator protein (TSPO) has been widely used to measure neuroinflammation, though second-generation ligands are highly sensitive to a single nucleotide polymorphism, rs6971, resulting in high, mixed, and low affinity binders. It is unknown whether this polymorphism is associated with neuroinflammatory disorders. Materials and Methods: Eighty-six total participant genotypes for TSPO binding affinity were identified through Sanger sequencing (30 fibromyalgia, 21 ME/CFS, 11 multiple sclerosis, and 24 healthy controls). Associations between patient group and genotype were assessed with Fishers Exact test. Associations between genotype and symptom severity from self-report questionnaires were assessed with Kruskal-Wallis tests. Results: In the present study individuals with fibromyalgia, (ME/CFS), or multiple sclerosis were more likely to have a mixed- or low-affinity genotypes compared to healthy controls. Presence of the low or mixed genotypes were also associated with greater self-reported fatigue severity and depressive symptoms. Discussion: These findings should be confirmed in larger samples but suggest functional consequences of rs6971 polymorphism that may be related to the pathophysiology of pain and fatigue illnesses.

BACKGROUND: White matter hyperintensities (WMHs), the principal imaging manifestation of cerebral small vessel disease, lack an animal model that produces pathology of sufficient magnitude to validate potential therapeutics. We characterized white matter (WM) degeneration in a renovascular hypertension (RVH) rat model, interrogated its mechanism, and tested its relevance in patients. METHODS: RVH was induced by two-kidney, two-clip surgery and assessed by T2-weighted and diffusion MRI, myelin and axonal histology, and blood-brain barrier (BBB) leakage markers. The influence of angiotensin II (Ang II) on barrier function in brain endothelial cells was examined using transendothelial electrical resistance and reactive oxygen species (ROS) assays. Losartan was infused intracerebroventricularly to block brain AT1R (Ang II type 1 receptor) without systemic blood pressure reduction. WMH burden was compared between patients with and without renal artery stenosis, and WMH progression across antihypertensive classes was assessed in the CHALLENGE (Korea), MSS2 (UK), LBC1936 (UK), and SPRINT-MIND-MRI (US) cohorts. RESULTS: Approximately two-thirds of RVH rats developed WMHs that expanded between 7 and 9 weeks, accompanied by reduced fractional anisotropy, demyelination, axonal and mature oligodendrocyte loss, and glial activation. IgG, albumin, and fibrinogen leakage was confined to affected WM. Ang II impaired endothelial barrier function and generated ROS through AT1R. Intracerebroventricular losartan attenuated WM pathology and improved behavior while blood pressure remained comparably elevated. Patients with renal artery stenosis had higher WMH volumes (10.52 versus 6.52 mL; P = 0.035). Angiotensin receptor blocker use was associated with the slowest tertile of annual WMH progression in the Korean cohort (OR, 2.57 [95% CI, 1.20-5.61]) and among White participants in SPRINT-MIND-MRI (OR, 3.52 [95% CI, 1.05-12.29]). CONCLUSIONS: RVH produces prominent ischemic WM degeneration driven by AT1R signaling, identifying a blood pressure-independent therapeutic target with corroborating clinical evidence.

Introduction: Thyroid diseases are major health problems and among the most common endocrine disorders worldwide, including in Ethiopia. They are characterized by alterations in hormone secretion, enlargement of the thyroid gland, or both. Fine needle aspiration cytology is an important initial screening tool, and histopathologic examination is essential for the definitive diagnosis of thyroid disease. This study aimed to compare the diagnostic accuracy of fine needle aspiration cytology with histopathology in identifying thyroid diseases. Methods: A cross-sectional study was conducted at three health facilities in Hawassa City, Ethiopia, involving 304 patients who underwent both thyroid fine needle aspiration cytology and histopathologic examination of the same site between 30th October 2024 and 29th October 2025. FNAC results were classified using the Bethesda system, with histopathology as the gold standard. Data were entered into Kobo Toolbox, exported to SPSS version 27, and analyzed using cross-tabulation and chi-square ({chi}{superscript 2}) tests to determine diagnostic accuracy. Result: 304 patient records were included in the study. The fine needle aspiration cytology was determinate/diagnostic in 81.6% of cases. The study revealed the sensitivity and specificity of fine needle aspiration cytology to be 88.2% (CI 77.6-95.1%) and 94.4% (CI 90.6-97.1%), respectively. The false negative and false positive rates in this study were 2.4% and 4.4%, respectively. The positive predictive value was 80.3% (CI 68.7-89.3%), and the negative predictive value was 96.8% (CI 93.8-98.7%). The accuracy of fine needle aspiration cytology in differentiating benign from malignant thyroid lesions was 93.1%. Conclusion: FNAC demonstrated strong agreement with histopathology and remains a reliable, cost-effective first-line diagnostic tool for thyroid disease, particularly in resource-limited settings. Strengthening sample handling, ultrasound guidance, and adherence to Bethesda criteria may further improve diagnostic precision

The gut-brain axis has emerged as a critical modulator in neurological diseases, including stroke. While acute post-stroke dysbiosis is well established, it remains unclear whether these alterations persist long-term and can be therapeutically modulated. This study addresses this gap through integrated metagenomic and metabolomic profiling in two independent clinical stroke cohorts, complemented by experimental models. Experimental stroke induced persistent changes in gut microbiota composition and altered short-chain fatty acid profiles. In patients, microbiota composition remained distinct from controls up to three months after ischemic stroke or transient ischemic attack (TIA), accompanied by persistent reductions in propionic and valeric acid and reduced abundance of Prevotella-associated microbial signatures. We performed a randomized, double-blind interventional trial (PRISE) testing a multispecies probiotic versus placebo, using household members as additional controls. Probiotic intervention led to microbiome compositional changes with increased abundance of beneficial taxa and significantly improved functional recovery. The tested probiotic strains showed anti-inflammatory and antioxidant effects in vitro. These findings suggest that targeted modulation of the microbiome represents a promising therapeutic avenue to improve chronic stroke recovery, warranting validation in larger Phase III clinical trials.

Polyendocrine Metabolic Ovarian Syndrome (PMOS, formerly PCOS) is associated with chronic low-grade inflammation. This study aimed to characterize the peripheral cytokine landscape in women with PMOS and identify cytokines associated with disease pathogenesis and phenotypic variation. Plasma concentrations of 48 cytokines were quantified using a multiplex bead-based assay in 102 women with PMOS and 114 healthy controls. We performed receiver operating characteristic (ROC) analysis, odds ratio estimation, correlation analysis, and network analyses to characterise cytokine alterations and identify phenotype-associated inflammatory signatures. Fourteen cytokines were significantly elevated in PMOS compared with healthy controls: IL-18, IL-1Ra, IL-12p70, IL-13, IL-16, MCP-1, MCP-3, CTACK, Eotaxin, RANTES, IP-10, M-CSF, HGF, and {beta}-NGF. ROC analysis identified IL-16, CTACK, and IP-10 as potential discriminators of phenotype A, whereas IL-18, M-CSF, and HGF demonstrated promising discriminatory performance for phenotype B. Odds ratio analysis identified 11 cytokines with odds ratios greater than 1, with IL-16 showing the strongest association with PMOS. Correlation analysis revealed 10 strongly correlated cytokine pairs (r [≥] 0.7) in the PMOS group, suggesting coordinated regulation of inflammatory mediators. Gene ontology and network analysis highlighted alterations in chemotaxis and immune cell migration pathways, implicating these processes in PMOS-associated immune dysregulation. These findings reveal a distinct peripheral inflammatory cytokine signature and phenotype-associated differences in PMOS. IL-16 emerged as a prominent candidate for further investigation, given its strong association with PMOS. Peripheral cytokine profiling may provide a minimally invasive approach to characterising immune alterations and identifying candidate biomarkers for disease characterisation and phenotype stratification.

INTRODUCTION: Whether APOE e4 modifies relationships between subclinical cardiac phenotypes and brain structure is unknown. METHODS: In Framingham Heart Study Offspring participants, we related antecedent echocardiographic remodeling (Examinations 4-6) to repeated brain MRI, and cardiac magnetic resonance phenotypes to regional cortical morphometry, testing cardiac x APOE e4 interactions with false-discovery-rate (FDR) correction and permutation testing of the regional screen. RESULTS: APOE e4 modified the association between antecedent left atrial (LA) remodeling and subsequent lateral ventricular expansion (beta=-0.00858, P=1.45 x 10^-4, q=0.0023; N=1,305; 3,787 MRI observations), the only FDR-significant result of 16 longitudinal tests, including with participant-specific MRI-time slopes (q=0.034); it weakened when intracranial volume x MRI time was modeled. Four regional ventricular cardiac x APOE e4 interactions met within-family FDR criteria, but their number was consistent with chance (permutation P=0.70). Maximum LA volume index showed an APOE e4-dependent association with left middle-occipital cortical-thickness variability (whole-brain q=0.017; permutation P=0.041) that persisted after ventricular adjustment. Cardiac phenotypes and trajectories showed no FDR-significant APOE e4-dependent associations with plasma Abeta42/40, p-tau181, GFAP, or NfL, and adjustment for these biomarkers changed the regional interactions by at most 3.2%. Allen Human Brain Atlas data showed cholesterol-biosynthesis enrichment in the right superior frontal cortex, implicated by the LV end-systolic volume interaction, but without convergent pathway evidence. DISCUSSION: APOE e4 modified atrial-brain relationships, with the strongest evidence linking antecedent atrial remodeling to later ventricular expansion. Replication with prespecified models is needed.

INTRODUCTION: Alzheimer's disease (AD) begins with cerebral amyloid-beta (A{beta}) deposition decades before clinical symptoms. While the microbiota-gut-brain axis has been implicated in AD, its role in this preclinical phase remains unclear. We examined potential links between gut microbiome features and presymptomatic cerebral A{beta} burden. METHODS: Asymptomatic individuals (n=101, median age 70.0 years, 53% female) underwent cognitive assessment, cerebral A{beta} quantification, and stool metagenomic sequencing. Associations between microbial characteristics and A{beta} levels were performed using multivariable-adjusted ordinal logistic regression. RESULTS: Gut microbiota composition varied with A{beta} levels (p(perm)=0.03, R2=0.014). Higher A{beta} was associated with increased Alistipes communis, and decreased Anaerotignum faecicola and Eubacterium rectale, abundance (q<0.001). A{beta}-associated microbiome traits corresponded to lower biosynthetic capacity for {gamma}-aminobutyric acid, and systemic regulators of immunity and autophagy (q<0.01). DISCUSSION: Early A{beta} accumulation is associated with distinct gut microbial signatures and reduced neuroactive metabolic potential, identifying targets for potential preclinical AD intervention.

Biomedical artificial intelligence (AI) increasingly relies on heterogeneous data sources, yet differences in data structure, terminology, evidence quality, and provenance complicate their integration into reliable knowledge resources. Here, we develop an evidence-aware framework for processing and integrating heterogeneous pharmacovigilance data from FDA Adverse Event Reporting System (FAERS) reports, biomedical literature, clinical trials, and electronic health records in Mass General Brigham. The framework combines large language model (LLM)-based information extraction, ontology-driven semantic normalization, cross-source evidence assessment, statistical and machine learning-based prioritization, and ingredient-based adverse drug event (ADE) relationship inference to transform heterogeneous evidence into a structured and evidence-based knowledge resource. The constructed knowledge system contains 11,588 drug nodes, 44,843 ingredient nodes, 3,275 ADE nodes, 993 indication nodes, and more than 2.47 million relationships, with each drug-ADE relationship assigned a confidence score. We further developed a drug-level web interface for accessing the knowledge resource and validated its utility in downstream AI tasks. Specifically, incorporating the developed knowledge resource improved the comprehensiveness, relevance, and overall quality of LLM-based drug-specific ADE synthesis and improved the precision and F1 score of clinical ADE relation extraction. These results demonstrate that AI-assisted processing combined with evidence-aware curation can transform heterogeneous biomedical evidence into reusable, AI-ready knowledge with explicit provenance and evidence strength information. The framework provides a general strategy for integrating heterogeneous biomedical data to support reproducible knowledge construction and downstream biomedical AI applications.

Neuropsychiatric symptoms (NPS) are highly prevalent in Mild Cognitive Impairment (MCI), conceptualized as an intermediate clinical state between normal aging and dementia. Although neuroimaging studies have reported associations between NPS and brain alterations in MCI, longitudinal evidence on NPS and their relationship with multimodal MRI measures remains limited. We aimed to investigate (1) longitudinal changes in NPS, volumetric assessment and measurement of regional cerebral blood flow (CBF) within the medial temporal lobe (MTL); (2) associations between longitudinal changes in MRI measures and NPS; (3) whether baseline MRI measures predicted longitudinal changes in NPS. Thirty individuals with MCI aged over 65 years were recruited, of whom eighteen followed up for a mean period of 29 {+/-} 8.9 months. There were significant reductions in total grey matter and white matter volumes, together with volume loss in the bilateral hippocampus, bilateral parahippocampal gyrus and right entorhinal cortex (pFDR[&le;]0.05) over the follow up period. Volume loss in the right parahippocampal gyrus was associated with increase in aggression (pFDR<0.01), and CBF increase in the right hippocampus and parahippocampal gyrus was associated with worsening in agitation (pFDR<0.01). Furthermore, lower baseline volume of the right entorhinal cortex was associated with increase in aggression, and lower baseline CBF in the right hippocampus and parahippocampal gyrus was associated with worsening of agitation (pFDR<0.05). Our findings highlight the importance of identifying NPS in individuals with MCI and the role of structural and perfusion MRI measures as promising biomarkers for monitoring disease progression and improving risk prediction of conversion to dementia.

People experiencing homelessness (PEH) have substantially lower quality-adjusted life expectancy and substantially higher healthcare spending compared to housed populations. California has the largest population of PEH in the United States, and an estimated ten percent of PEH have co-occurring opioid use disorder (OUD). We developed a lifetime, individual-level microsimulation of the 18,928 PEH with OUD in California to evaluate the health and economic effects of expanding access to housing through a Housing First approach, which does not require OUD treatment or abstinence. Increases in permanent housing and shelter access were based on Los Angeles County's Measure A goals, and we accounted for both housing and healthcare costs. Expanding housing access increased mean age at death by 0.34 years, reduced fatal overdoses for the cohort by 39, and produced an incremental cost-effectiveness ratio of $31,083 per quality-adjusted life-year gained, well below conventional willingness-to-pay thresholds. We provide evidence that housing is a high-value health intervention for PEH with OUD in California. Policymakers should support Housing First programs as part of integrated responses to the intertwined crises of homelessness and opioid use.

Background: The relationship between recent viral infection and subsequent susceptibility to, or protection against, other viruses remains unclear, particularly across ages and symptom status. Methods: A prospective cohort study enrolled participants aged 6 months to 49 years in Washington and Oregon, USA, 2022-2024. Weekly nasal swabs were tested for SARS-CoV-2, respiratory syncytial virus (RSV), and influenza A/B; additional swabs were collected during symptomatic illness and were also tested for parainfluenza (PIV) 1-4, endemic human coronaviruses (hCOV), adenovirus, human metapneumovirus, human rhinovirus (hRV), and enteroviruses. Proportional hazards regression models were used to characterize associations between incident symptomatic infection (illness) and history of recent illness due to other viruses (within 1-7, 8-14, 15-30, 31-60, 61-90, 91-180 days), adjusted for geographic region, age, sex, daycare/school/work attendance, household size, and number of children in the household. For SARS-CoV-2, influenza, and RSV, these analyses were repeated to study incidence of infection (including asymptomatic cases). Findings: Of 3,560 participants, 2,969 (83%) had [&ge;]1 illness over 4,299 person-years. Adjusted hazard ratios (aHRs) in the short term ([&le;]2 weeks) after an illness were predominantly below 1, indicating that recent viral illness was often associated with lower risk of subsequent illness with other viruses. Across age groups, recent hRV illness was associated with lower risk of hCOV, PIV, and RSV illness (aHRs 0.07-0.27). SARS-CoV-2 illness was associated with a higher short-term risk of adenovirus and PIV illness (aHRs 3.20-3.33). In children aged 6 months-4 years, recent influenza illness was associated with higher short-term risk of SARS-CoV-2 illness. Including asymptomatic infections generally attenuated these associations. Interpretation: Some viral illnesses may alter short-term susceptibility to subsequent viral illnesses. Interactions may differ by age and symptom status. Funding: US Centers for Disease Control and Prevention; Washington State Department of Health.

BACKGROUND: The chromosome 9p21.3 locus is among the strongest genetic risk loci for cardiovascular disease (CVD), yet the regulatory mechanisms underlying this association remain poorly understood. Previous vascular disease studies focused predominantly on the role of this locus in smooth muscle cell (SMC) dysfunction, whereas its potential role in endothelial cells (ECs) remains less well characterized. Here, we sought to identify candidate regulatory variants at 9p21.3, their distal target genes, and effector transcripts that contribute to CVD-related phenotypes in ECs. METHODS: Promoter capture Hi-C was used to map chromatin interactions at 9p21.3 in primary human ascending aortic SMCs (n=6), supplementing the previously obtained ECs (n=16) dataset. To support the regulatory relevance of these interactions, expression quantitative trait locus analysis was performed in 136 vascular biopsies. Variant effects were prioritized in silico using AlphaGenome. The regulatory activity of the prioritized region was validated using CRISPR activation. RESULTS: Chromatin interaction mapping identified a complex regulatory architecture at the 9p21.3 locus involving 19 putative regulatory elements and 15 genes across ECs and SMCs. MIR31HG showed the most recurrent distal promoter connectivity with the 9p21.3 region. Consistent with the chromatin interaction map, expression of MIR31HG transcripts was associated with genetic variation at the 9p21.3 locus. In ECs, the lncRNA MIR31HG, but not miR-31, was responsive to hemodynamic flow. Depletion of MIR31HG in ECs was associated with endothelial activation. Epigenetic tracks and deep learning predictions highlighted an active enhancer element at 9p21.3, which was subsequently validated by CRISPR activation and increased MIR31HG expression, confirming its capacity to regulate MIR31HG over a large genomic distance of approximately 538 kb. CONCLUSIONS: Altogether, these data implicate lncRNA MIR31HG as a likely effector of the 9p21.3 CVD locus, linking the cis-regulatory element and heritable genetic variation in the respective region to endothelial activation through long-range enhancer regulation.

Background: Artificial intelligence (AI) may improve electrocardiographic differentiation of Takotsubo syndrome from acute anterior ST-segment elevation myocardial infarction (STEMI), but its impact on human diagnostic performance, the added value of visual explanations, and differences by reader background and experience remain uncertain. Methods: Using 12-lead electrocardiogram (ECG) images from two hospitals, we developed and externally validated an ensemble of three deep learning models after self-supervised pretraining and fine-tuning. The diagnostic task used ECGs recorded within 14 days after symptom onset, regardless of reperfusion status. We conducted a four-phase reader study. Phases 1-3 compared unaided interpretation, a reference sheet, and additional AI assistance. In Phase 4, readers evaluated a new ECG set after randomization to reference-sheet support alone, with AI predictions, or with AI predictions plus gradient-weighted class activation mapping (Grad-CAM) heatmaps. Diagnostic correctness was analyzed using generalized linear mixed-effects models. Exploratory analyses examined differences by cardiologist status and experience. Results: Development and external-validation cohorts, including healthy controls, comprised 832 and 95 participants, respectively. For Takotsubo-STEMI discrimination, external-validation accuracy was 0.914, with areas under the receiver operating characteristic and precision-recall curves of 0.970 and 0.984. Seventy healthcare providers completed the reader study. The estimated probability of correct diagnosis increased from 0.632 without assistance to 0.864 with AI assistance (odds ratio [OR], 3.71; P<0.001). In randomized Phase 4, AI assistance improved accuracy vs reference-sheet support alone (OR, 4.28; 95% CI, 3.08-5.95; P<0.001), and Grad-CAM provided additional benefit (OR, 1.53; 95% CI, 1.04-2.25; P=0.033). Exploratory analyses showed greater improvement among less experienced readers; with AI assistance, non-cardiologists outperformed cardiologists. AI-assisted readers remained less accurate overall than the model alone. Conclusions: An ECG image-based ensemble differentiated Takotsubo syndrome from anterior STEMI and improved reader accuracy. Visual explanations provided additional benefit, while experience-related differences highlight the importance of effective human-AI interaction.

Background: Epidermal Growth Factor Receptor (EGFR) tyrosine kinase inhibitors (TKIs) are widely used for EGFR-mutated non-small cell lung cancer (NSCLC) but have distinct toxicity profiles across generations. Aims: To investigate relationships between EGFR-TKI physicochemical, pharmacokinetic and pharmacological properties and drug-specific adverse drug reactions (ADRs) using national and global pharmacovigilance data. Methods: ADRs for erlotinib, afatinib and osimertinib were extracted from the UK MHRA Yellow Card scheme and WHO VigiAccess. Disproportionality analysis used reporting odds ratios (RORs). Signals were defined as ROR >2, lower 95% confidence interval >1 and >3 cases. Drug properties were curated from ChEMBL, emc, SmPC and EMA sources. Results: VigiAccess contained 88,662 individual case safety reports (163,619 ADRs) and Yellow Card contained 752 reports (1,814 ADRs). Four System Organ Class (SOC) signals were identified in VigiAccess and three in Yellow Card, with five additional Yellow Card Preferred Term signals. Eye disorders showed the strongest consistent association with erlotinib (VigiAccess ROR 4.33; Yellow Card ROR 4.18). Osimertinib was associated with pneumonitis (ROR 7.67) and pulmonary embolism (ROR 3.94). Afatinib showed psychiatric disorder signals in both databases (ROR 3.2-3.3) and diarrhoea (ROR 2.79). Neoplasm-related signals likely reflected confounding by indication. Conclusions: EGFR-TKIs demonstrate generation-specific pharmacovigilance profiles. Integration with drug properties supports mechanistic plausibility for several signals, while the atypical afatinib psychiatric association warrants further investigation. Findings are hypothesis-generating and require confirmation in controlled observational or mechanistic studies.

Background. In people with type 2 diabetes (T2D), postprandial glucose weighs on glycaemic control, and carbohydrate counting is difficult. Patients can describe their meal but rarely quantify it. Objective. To assess (1) whether a small open large language model (LLM), fine-tuned on public data, estimates the carbohydrate content of a meal described in words, and (2) what this carbohydrate adds to the prediction of the postprandial glucose rise in two public cohorts. Methods. Step 1: the Qwen3-4B LLM was fine-tuned with QLoRA on Nutrition5k dishes and compared with an automatically matched USDA food composition table and with Qwen3-4B and Qwen3-8B used without training, on test dishes (internal control) and on 100 real meals of ShanghaiT2DM patients, whose reference carbohydrate was computed from the recorded quantities. Step 2: the maximum glucose rise between 0 and 120 minutes ({Delta}Gmax) was predicted by personalised gradient boosting (M2), compared with a spline linear regression and with the Chronos-2 foundation model, using only information available at meal start and person-level cross-validation, in ShanghaiT2DM (people with T2D recruited in two Shanghai hospitals; carbohydrate estimated by the LLM) and CGMacros (free-living adults in Santa Barbara, California; carbohydrate entered in the dataset, no text). Step 3: the model was transferred between datasets. 95% confidence intervals (CI) were obtained by cluster BCa bootstrap (2,000 resamples). Results. On the 100 real meals, the carbohydrate mean absolute error (MAE) of the fine-tuned model was 12.2 [9.9, 15.2] g, almost half that of the table (22.6 g; paired difference -10.5 [-16.8, -6.0] g) and nearly a third of that of the same model without fine-tuning (34.3 g), with a bias of -10.3 g; on test dishes it was 2.2 [2.0, 2.5] g. Personalised gradient boosting (M2) reached a correlation between predicted and observed rises of r = 0.63 [0.55, 0.69] in CGMacros (1,286 meals, 45 adults) and 0.49 [0.42, 0.54] in ShanghaiT2DM (2,339 meals, 99 people with T2D), about twice the linear reference (r = 0.32 and 0.23); for a rise above 50 mg/dL, its area under the ROC curve (AUROC) was 0.80 and 0.74, versus 0.64 and 0.68 with pre-meal glucose alone. Adding carbohydrate to pre-meal glucose changed r by 0.095 [0.068, 0.128] in CGMacros and by 0.004 [-0.010, 0.017] in ShanghaiT2DM; difference between datasets: 0.091 [0.060, 0.126]. Applied from one dataset to the other, the model lost correlation ({Delta}r = -0.11 [-0.17, -0.05] towards ShanghaiT2DM and -0.12 [-0.19, -0.04] towards CGMacros). The full "text [-&gt;] LLM [-&gt;] glucose" chain was evaluated in ShanghaiT2DM only. Conclusion. An open 4-billion-parameter LLM, fine-tuned with QLoRA on public data and usable offline, almost halves the error of carbohydrate counting for real meals described in words compared with an automatically matched table, with an underestimation of large meals. Personalised gradient boosting, based on pre-meal glucose and the person's usual response, doubles the correlation of a linear reference for predicting the glucose rise in both cohorts. Carbohydrate improved this prediction in CGMacros but not in ShanghaiT2DM; the two datasets differ in many respects, and the cause of this gap is not established.

Mitochondrial disease arises from variants in either the mitochondrial or nuclear genome that impair mitochondrial oxidative phosphorylation. Complex III (ubiquinol:cytochrome c oxidoreductase, CIII2) is a key enzyme of the mitochondrial respiratory chain, catalyzing electron transfer from reduced coenzyme Q10 (ubiquinol) to complex IV, via cytochrome c. CIII2 has one subunit encoded by mitochondrial DNA, the remainder being nuclear encoded. Individuals with CIII2 deficiency present with significant clinical heterogeneity, on account of pathogenic variants in genes encoding structural CIII2 subunits or assembly factors. UQCC1 (GenBank: NM_018244.5) encodes the mitochondrial complex III assembly factor Ubiquinol-cytochrome c reductase complex assembly factor 1, which is currently not associated with human disease. Here we describe nine subjects from eight unrelated families harboring biallelic UQCC1 variants with heterogeneous, early-onset mitochondrial disease presentations and lactic acidosis. Subject-derived fibroblasts demonstrated a decrease in the steady-state levels of UQCC1 and its interacting partner UQCC2, with structural modelling supportive of variant pathogenicity. BN-PAGE and quantitative proteomics demonstrated decreased CIII2 abundance whilst mass spectrometry (MS)-complexome profiling corroborated these findings, identifying impaired respiratory supercomplex formation and a delay in the incorporation of newly synthesized CIII2 subunits into native assemblies. Lentiviral transduction experiments in subject-derived fibroblasts restored the levels of both UQCC1 protein and CIII2 activity. Collectively, these findings provide convergent genetic, biochemical, proteomic and functional evidence that bi-allelic UQCC1 variants disrupt CIII2 assembly, establishing UQCC1 deficiency as a cause of mitochondrial CIII2 deficiency.

Schizophrenia spectrum disorders (SSD) have been linked to immune dysregulation and altered intestinal barrier function, although findings across studies remain inconsistent. The present study investigated circulating markers of intestinal permeability and immune activation in individuals with early-stage SSD and healthy controls and examined their associations with clinical outcomes. Serum concentrations of intestinal fatty acid-binding protein (iFABP), zonulin, soluble CD14 (sCD14), bactericidal/permeability-increasing protein (BPI), and lipopolysaccharide-binding protein (LBP) were measured in 36 patients with SSD at baseline and one-year follow-up and in 36 matched healthy controls. Linear mixed-effects models adjusted for age, sex, and body mass index (BMI) were used to evaluate group differences and longitudinal changes. No biomarker differences between patients and controls, and no longitudinal changes within patients, remained statistically significant after correction for multiple testing. Similarly, biomarker concentrations were not associated with symptom severity, global functioning, or neutrophil-to-lymphocyte ratio (NLR). Exploratory analyses identified a robust positive association between BMI and zonulin concentrations and additional associations among iFABP, LBP, and sCD14. Exploratory mixed-effects models identified a negative non-significant association between iFABP and sCD14 after adjustment for age, sex, and BMI. Overall, the findings do not support a generalized alteration of gut permeability or immune activation markers in SSD. Instead, they suggest that variation in gut-related biomarkers may be more strongly influenced by metabolic and individual factors than by diagnosis or current symptom severity.

Exposure to armed conflict can leave persistent effects on mental health, yet its neurophysiological correlates remain poorly characterized, particularly in populations exposed to prolonged violence outside narrowly defined post traumatic stress disorder samples. Here we examined resting state electroencephalographic activity in 122 Colombian adults, including 74 participants exposed to armed conflict and 48 controls. Eyes closed EEG was analysed for 240 seconds per participant. We quantified absolute and relative spectral power across delta, theta, alpha and beta bands and regional functional connectivity using weighted phase lag index in theta, alpha and beta. Group comparisons were adjusted for age, education, sex and assessment year, with correction across 78 EEG contrasts. Median occipital and global alpha power was lower in exposed participants, although adjusted estimates were close to the null and confidence intervals were broad. Temporal theta relative power was lower in exposed participants at nominal significance, but this association did not survive Holm correction. No spectral power or regional connectivity contrast remained significant after multiple testing correction. Exploratory associations between EEG measures and MoCA performance were modest in participants with confirmed scores. These findings provide a systematic characterization of resting EEG after exposure to armed conflict in a population shaped by prolonged violence and displacement. They also indicate that large or widespread alterations in resting spectral power and connectivity were not detectable with the current sample and analytical framework, while defining candidate signals and methodological priorities for larger studies of conflict related brain health.

Fetal development is highly sensitive to environmental influences, including maternal smoking during pregnancy (MSDP) and air pollution. The placenta may play a central role in mediating these effects through epigenetic mechanisms, including small non-coding RNAs (sncRNAs). While most studies have focused on microRNAs (miRNAs), other sncRNA classes remain poorly characterized. Here, we characterized the placental sncRNA landscape and investigated its associations with prenatal exposure to MSDP and air pollution. The sncRNA expression profile of 390 chorionic villi samples from the Barcelona Life Study Cohort (BiSC) was measured using small RNA sequencing and the seqBuster/seqCluster pipeline. MSDP was assessed via questionnaire, and prenatal exposure to black carbon (BC), particulate matter [&le;]2.5 m (PM2.5), and nitrogen dioxide (NO2) was estimated using hybrid dispersion-land-use regression (LUR) spatiotemporal models. Associations were evaluated using linear regressions adjusted for relevant covariates. We identified 979 placental sncRNA clusters, assigned primarily to miRNAs (33.2%), piRNAs (26.4%), snoRNAs (12.2%), tRFs (7.8%), and others (20.4%). MSDP was associated with the downregulation of miR-421 and the upregulation of multiple snoRNAs from the imprinted DLK1-DIO3 locus (SNORD113-4, SNORD114-2, SNORD114-3, and SNORD114-17), as well as the piR-26394. No sncRNAs remained significantly associated with air pollution after multiple-testing correction, although several miRNAs showed suggestive associations. Overall, this study provides a comprehensive characterization of placental sncRNAs and identifies previously unreported smoking-associated sncRNAs within the imprinted DLK1-DIO3 locus, expanding our understanding of placental epigenetic responses to prenatal environmental exposures.

Estimating the correlation between subject-specific rates of change is a common objective in longitudinal studies. A natural approach is to fit ordinary least squares regressions per subject and correlate the resulting slope estimates directly. Under complete data, this slopes-first estimator is algebraically equivalent to a contrast-based plug-in estimator derived from the joint variance-covariance matrix of the two signals across time. Under independent dropout, however, the slopes-first approach implicitly applies heterogeneous weights across missing-data patterns, introducing bias whenever the cross-covariance between the two signals is not constant over time. We formalise this result and propose an unbiased alternative that estimates the joint covariance matrix before applying the contrast. We further extend our results to include covariates as well. Simulations confirm that the slopes-first estimator is biased under non-constant cross-covariance while the proposed alternative remains unbiased. Further, we show in a real-world example that the two estimators can lead to different scientific conclusions and recommend that researchers working with longitudinal data inspect the missing data pattern to make an informed decision about the estimator of choice.