International Journal for Parasitology

Tick-borne disease risk reflects the combined influence of vector abundance, pathogen prevalence, human exposure, and seasonal activity, yet these components are rarely integrated at the county level. We developed species-specific ecological risk scores for three medically important tick species (Acari: Ixodidae): Amblyomma americanum (L.), Dermacentor variabilis (Say), and Ixodes scapularis Say, across all 102 Illinois counties using data from 2019 to 2022. County-level predicted tick abundance and pathogen prevalence were scaled and combined using equal weights to generate primary vector-level risk scores. Robustness to the equal-weight assumption was evaluated by systematically varying the relative weights assigned to abundance and pathogen prevalence, while a separate sensitivity analysis incorporated reported tick-bite incidence where available. Associations with human disease were evaluated using negative binomial regression of tick-borne disease case counts on the corresponding risk scores, with county population included as an offset. Monthly phenology indicators were constructed by integrating human disease cases, reported tick bites, and sampled tick abundance and were evaluated in relation to temperature and precipitation. Seasonal risk was estimated by combining county-level vector risk with species-specific monthly phenology, generating monthly risk surfaces that were deployed through an interactive R Shiny application. Higher risk scores were significantly associated with greater disease case rates for each tick species. County rankings were highly stable under moderate changes in abundance and prevalence weighting. Seasonal activity differed among species, with A. americanum and D. variabilis showing concentrated warm-season risk and I. scapularis exhibiting a broader seasonal profile. These county-level seasonal risk maps identify where and when relative tick-borne disease risk is elevated in Illinois, supporting targeted prevention, surveillance, and clinical awareness.

Vegetation plays a critical role in shaping fine-scale tick density by structuring local microclimates, habitat resources, and host interactions that largely determine tick survival and activity, with implications for tick-borne disease transmission. Tick burden in the United States continues to increase, with annual reported tick-borne disease cases more than doubling from 2004 through 2019. These trends call for a broader scope of tick-mitigation strategies that go beyond traditional prevention measures that focus on personal protection; and there is an opportunity to inform habitat-level interventions. Here, we quantify fine-scale vegetation structure across 48 subplots at tick surveillance sites in Western Massachusetts to assess local habitat features associated with Ixodes scapularis density and potential for human-tick contact risk. In assessing understory and overstory vegetation attributes, this study identified life stage-specific differences in predicted tick density, with higher adult densities in areas with deeper leaf litter and presence of invasive plant species and nymphs associated with high presence of ferns. Both adult and nymphal Ix. scapularis were predicted at higher densities in relatively low basal area forests (18.9 to 26.9 m2/hectare). This study design provides a simple, low-cost framework for organizations looking to incorporate tick-informed forest measurement ecology into their public health tick surveillance protocols with minimal training.

Artemisinin partial resistance (ART R) associated Plasmodium falciparum Kelch13 mutations is expanding across Africa. However, their population level consequences remain poorly understood, particularly in settings of moderate to high malaria transmission. We investigated associations between Kelch13 and partner drug mutation prevalence and monthly confirmed malaria incidence across 16 Ugandan districts from 2017 to 2022, using integrated molecular, epidemiological, climatic, malaria control, and antimalarial resistance data and negative binomial regression. Combined prevalence of WHO validated and candidate Kelch13 mutations increased over the study period. Each 10 percentage point increase in Kelch13 prevalence was associated with a 13.1% higher incidence after multivariable adjustment (aIRR 1.131, 95% CI 1.090 to 1.174). Furthermore, each 10% increase in pfcrt K76T was associated with a 24% increase in malaria transmission. As expected, ITN distribution >80%, IRS coverage >90%, and higher altitude were associated with lower incidence, whereas temperatures of 25 to 30C, relative humidity of 60 to 80%, and higher precipitation were associated with higher incidence. The persistence of the Kelch13 and pfcrt K76T association after adjustment suggests that expanding ART R associated parasite populations are independently associated with malaria incidence. The relationship may be bidirectional. These findings support interpreting ART R within its ecological and intervention context and integrating molecular, epidemiological, and malaria control surveillance to safeguard antimalarial efficacy.

Background: Visceral leishmaniasis (VL) is the most severe form of leishmaniasis and is caused by parasites from the Leishmania donovani complex. VL is endemic in 54 countries, with East Africa (EA) accounting for [~]70% of the global burden. Therefore, there is a pressing need to prioritize VL research in EA. Transcriptomics analysis in rodent models and patients following treatment have shown that immune homeostasis is not restored by the end of treatment. However, comprehensive proteomic studies in VL remain scarce, and the few available studies were conducted outside EA. Methodology/Principal Findings: As a part of ImmStat@cure consortium, we used the Olink Reveal proximity extension assay to profile circulating proteins in VL patients from Ethiopia, Kenya and Sudan. By comparing patients at admission and 17 days after treatment with SSG-PM, we have identified a systemic Th1-cytotoxic inflammatory profile at admission, characterized by high abundance of IFN{gamma}, IL-1B, IL-6, and the granzymes A and B. Chemokines with high abundance included CXCL8/10/11, CCL3, CCL4, CCL8, CXCL8 and CCL20, consistent with the recruitment of monocytes, macrophages, T cells, and NK cells. There were also evidence of immune regulation/exhaustion, with high levels of PD1, PD-L2, IDO1 and KYNU. Although the immune profiles were similar at admission, country specific differences were observed after treatment. Kenyan patients exhibited a sustained inflammatory profile and signatures of myeloid recruitment, characterized by high levels of IL-1B, IL-6 , IL-12A, CXCL8, CCL2, CCL3, CCL4, CCL7 and CEBPB. Sudanese patients showed signatures associated with lymphocyte activation and immune regulation. Conclusions/Significance: These results highlight the complexity of the immune changes associated with VL, identifying both core conserved profiles at admission and country-specific profiles after treatment. The data provided here will provide a valuable resource for future comparative studies across more diverse different geographic regions, for linkage studies that assess the impact of parasite genotype on immune / metabolic response and for use during the evaluation of new therapies against VL.

Background: Severe malaria remains a major cause of hospitalization in malaria-endemic sub-Saharan Africa, and anemia is among its most frequent severity criteria. Data on the impact of anemia on hospital length of stay (LOS) among adults with severe malaria remain limited in Central Africa. We assessed the impact of anemia on LOS among adults hospitalized for severe malaria in Brazzaville, Republic of Congo. Methods: We conducted a cross-sectional, descriptive, and analytic study of medical records from adult patients ([&ge;]18 years) diagnosed with severe malaria (WHO criteria) and admitted to four hospitals in Brazzaville between January 2020 and December 2024. We dichotomized LOS as short (<5 days) or prolonged ([&ge;]5 days). Multivariable logistic regression, using a backward stepwise procedure, identified factors independently associated with prolonged LOS; isolated hemoglobinuria served as the reference severity category. Results: Among 523 patients hospitalized for severe malaria, 296 met the inclusion criteria. Median age was 25.5 years (IQR 20-40); 51.7% were female, and 82.1% had a low socioeconomic status. Median hemoglobin was 10.55 g/dL, and median LOS was 4 days (IQR 3-5). In multivariable analysis, prolonged LOS was independently associated with delay to consultation (aOR 1.25/day, 95% CI 1.09-1.44), isolated anemia (aOR 7.07, 1.23-40.55), convulsions (aOR 5.86, 1.81-18.97), prostration (aOR 4.42, 1.21-16.2), and impaired consciousness (aOR 4.29, 1.17-15.7). The strongest associations involved combined severity criteria: anemia with prostration (aOR 8.58), anemia with jaundice or hemoglobinuria (aOR 16.21), and impaired consciousness with anemia (aOR 33.31). Conclusions: Anemia is a major, potentially modifiable determinant of prolonged hospitalization in adults with severe malaria, with a markedly amplified effect when combined with neurologic impairment. Early anemia screening, improved access to safe blood transfusion, and reduced delays to care could shorten hospital stays and ease the burden on health systems in this setting.

Background. Nigeria's reported Lassa fever case fatality ratio (CFR) rose from 18.9% at week 23 of 2025 to 25.0% in 2026, prompting concerns over failing clinical care. Because surveillance artefacts can also alter CFRs, candidate mechanisms that published data can resolve were identified and evaluated. Methods. This ecological study extracted weekly state-level counts from 474 Nigeria Centre for Disease Control and Prevention situation reports (2017-2026). Per a pre-specified plan, years were compared at phase-matched points, year-on-year CFR changes were decomposed into within-state and between-state components, and tipping-point ascertainment shifts calculated. Weekly incident and cumulative published totals were compared post hoc. Findings. Of 11 candidate mechanisms, 2 could be evaluated fully and 5 in part. On weekly incident counts, 2026 did not differ from 2025 at the phase-matched midpoint (+0.3 percentage points, 95% CI -5.0 to 7.6); within-state (-1.1, 95% CI -4.7 to 3.0) and between-state (+0.5, -2.0 to 2.9) components spanned zero. Conversely, the published cumulative CFR was 5.4 to 6.2 percentage points higher because 70 deaths were added retrospectively by week 36 outside weekly reports. Reconciling cumulative figures would require 279 missed survivors (6% of suspected cases not confirmed). Interpretation. The 2026 CFR rise came from deaths added to cumulative totals outside the weekly counts, and published data cannot attribute it to care. Endemic zoonotic CFRs cannot serve as clinical outcome measures unless testing volumes, deaths added late, and post-mortem sampling are published alongside case counts. Funding. US NSF-NIH-NIFA EEID; UK BBSRC; Birgitta Sintring Fellowship (Uppsala University).

Introduction Despite the significant burden of Shigellosis, routine surveillance systems in resource-limited settings lack predictive capabilities to guide proactive public health responses. Consequently, we developed and evaluated the accuracy, uncertainty and computational cost of multi-horizon forecasting models for Shigella incidence among children <5 years in rural western Kenya using 16-year longitudinal incidence time-series. Methods We estimated monthly Shigella incidence using data from three pediatric enteric studies (2008-2024), supplemented with Kenya Health Information System during inter-study gaps. Incidence estimates incorporated sampling, healthcare-seeking, stool-testing, and pathogen-specific weights, with bootstrap-derived 95% confidence intervals. Predictors included Google Trends health-related indicators, climate, temporal trends, and seasonality. Forecasts at 1-, 3-, and 6-month horizons were evaluated using rolling-origin validation. Following horizon-specific predictor selection using Boruta, 14 state-space, machine-learning, and hybrid models were compared using point-forecast and probabilistic metrics, bootstrap confidence intervals, and Model Confidence Sets. Adaptive conformal prediction recalibrated prediction intervals, while Shapley Additive exPlanations assessed predictor contributions. Results Mean monthly Shigella incidence was 2.51 per 100 child-years (standard deviation=1.85). Shigella dynamics in Kenya can be forecast beyond seasonal persistence alone for up to six months reducing absolute errors by ~ 33%. However, optimal model architectures and predictor sets shift systematically across forecasting horizons. Temporal trend and recent incidence were the dominant predictors, while predictor importance shifted with forecast horizon toward syndromic, pharmaceutical, seasonal, and lagged environmental signals. Extreme Gradient Boosting performed best at 1 month (Root mean squared error [RMSE]=1.86), remained competitive at 3 months (RMSE=1.89), whereas exponential smoothing (ETS) performed best at 6 months (RMSE=2.05). Forecast accuracy declined with increasing horizon. ETS and TBATS provided the best-calibrated prediction intervals, whereas machine-learning models generally under-covered. Model Confidence Sets demonstrated horizon-dependent model distinguishability. Conclusion Horizon-specific model selection balancing predictive accuracy, uncertainty calibration, and computational feasibility could strengthen operational early warning systems for shigellosis.

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

Wolbachia-based interventions were less effective in achieving introgression in Rio de Janeiro than other settings. Reduced introgression occurred in locations where dengue was historically high, raising concerns of inequity. We examined factors affecting Wolbachia introgression in Rio through trajectory modeling, spatiotemporal Bayesian models, and Ae. aegypti abundance estimation. During the intervention (2017-2020), Wolbachia introgression was 26% (median; IQR,14-44%), with four distinct trajectories. Despite receiving more releases, densely populated areas with low socioeconomic status had lower introgression. In spatiotemporally explicit multivariable regressions, higher Ae. aegypti abundance, temperature, population density and lower socioeconomic status were associated with reduced introgression. Improved characterization of Ae. aegypti abundance and other structural/environmental predictors of introgression could be used to calibrate release doses to ensure equitable benefits from Wolbachia interventions.

Background: TB vaccine development is hampered by the natural history of M. tuberculosis: most infected people rarely progress to disease, so trials must be very large and long to accrue sufficient disease endpoints. Current trials enrol IGRA-positive participants (IGRA: Interferon-Gamma Release Assays), but IGRAs remain positive for many years and cannot distinguish recent from remote infection. Tests for recent infection are now in development, and we argue they could make trials substantially more efficient. Here, we investigate how screening participants prior to enrolment with a test for recent M.tb infection could impact the total number of enrollees required for an adequately-powered TB vaccine trial. Methods: Using a statistical model of vaccine trial recruitment, we estimated the number needed to contact, test, and enrol to achieve an 'effective' trial (defined as 50 disease endpoints), under IGRA-gated enrolment (life-long duration of positivity) vs. enrolment with a test for recent infection. We considered five recruitment strategies: non-test-based enrolment for ages 15-49, ages 12-34, and household contacts of recent cases; and test-based enrolment using IGRA, and a test for recent infection with two-year duration of positivity. The model explored trial recruitment in South Africa, Kenya, and India. Results: Compared with an extended-positivity test, a test for recent infection reduced the median number needed to enrol by 4.2- to 6-fold under favourable conditions. It also outperformed non-test-based strategies, including enrolling household contacts. This comes at the cost of substantially more testing, but crude estimates suggest recency-based enrolment would still be cheaper overall provided the new test does not cost more than roughly 5-10 times an IGRA. Conclusions: Diagnostics for recent M.tb infection have the potential to improve vaccine trial efficiency, but more research is now needed to understand test characteristics and to evaluate their use in this setting. Our Viewpoint sets out the test attributes that would need to be established, such as time to positivity, duration of positivity, sensitivity, and specificity, before such tests could be used in vaccine trials.

Background: Treponema pallidum quantitative polymerase chain reaction (qPCR) positivity and cycle threshold (Ct) by rapid plasma reagin (RPR), disease stage, and other characteristics are poorly characterized in routine-care specimens, leaving it unclear when qPCR of such specimens is informative for diagnosis. Methods: This Japanese multicenter cross-sectional study explored qPCR positivity and Ct by these characteristics. Nonblood specimens collected during routine care underwent qPCR at a central laboratory for this study. Bayesian logistic and normal regressions modeled positivity and mean Ct of TP0574 and polA with stage-specific continuous automated RPR terms, patient characteristics, collection site, and facility random intercepts. Estimates were standardized over the analyzed specimens. Population-group predictions were instead averaged within each group. Results: Among 154 nonblood specimens from 145 patients (71.7% non-MSM men and women) at 14 facilities, 109 (70.8%) were qPCR positive. At RPR 1, adjusted positivity was 72.2% (95% credible interval, 60.9%--82.9%) in primary and 43.8% (16.7%--69.9%) in secondary syphilis. Positivity showed a modest downward trend with RPR in primary but increased in secondary syphilis, reflecting a stage-by-RPR interaction (secondary-to-primary ratio of odds ratios, 1.78; 1.25--2.65). Predicted positivity showed an upward trend with RPR values among MSM; adjusted positivity was relatively high for genital/urethral/urinary and anal/perianal/rectal specimens. Adjusted mean Ct increased with RPR in primary and followed an inverted-U pattern in secondary syphilis. Conclusions: In primary syphilis, nonblood qPCR positivity was high even at low RPR. When serologic findings remain inconclusive in this stage, qPCR is highly recommended for securing an early diagnosis.

Population genomic studies have revealed strong regional structure in Plasmodium knowlesi across Southeast Asia. To facilitate routine genomic surveillance, we developed a targeted amplicon sequencing panel that preserves the large- and small-scale population genetic structure. We screened published genomes for short, highly polymorphic targets and a 30-SNP barcode. We validated multiplexed amplification and sequencing using a portable Oxford Nanopore Technologies MinION sequencer on 28 clinical infections from four southern Thai provinces collected between 2018-2023. Twenty-seven loci yielded sequence data and 23 infections with data from at least eight loci were retained for analysis. Across the 23 Thai infections and 104 published Malaysian genomes, 586 diverse SNPs were observed. The amplicon panel and 30-SNP barcode retained the major population structure observed in genome-wide data, including a clear distinction between Bornean and Peninsular Malaysian infections and two clusters in Borneo. Across newly sequenced Thai infections, 25 loci were diverse and showed substantial diversity (mean expected heterozygosity = 0.69). All infections were effectively monoclonal. Pairwise identity-by-descent revealed substantial recent relatedness, with 46 of 253 pairs at or above 0.5. Two Thai genetic groups (n = 12 and n = 11) were observed, mirroring previously observed structure in peninsular Malaysia. Groups were not significantly associated with province or collection year. In conclusion, targeted sequencing can reveal geographically informative population structure across scales and thus support surveillance.

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.

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.

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.

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.

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.

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.

Introduction: This study aimed to characterize the neurochemical profile of Alzheimer s disease (AD) continuum stages using proton magnetic resonance spectroscopy (1H-MRS) data for brain metabolites and macromolecules. We used Orthogonal Projection to Latent Structures Discriminant Analysis (OPLS-DA) to classify diagnostic groups and assess feature importance. Methods: Our dataset consisted of 7 T short-echo time 1H-MRS spectra of the posterior cingulate cortex/precuneus of individuals diagnosed with AD (n = 27) or Mild Cognitive Impairment (MCI, n = 27) and Healthy Controls (HC, n = 31). Classification used 100-round Monte Carlo cross-validation based on metabolite concentrations and macromolecular peak intensities. Variable importance in projection (VIP) was assessed across classification models to identify the most relevant neurochemical features. The resulting metabolite rankings were compared with previous literature to evaluate their biological plausibility. Results: Classification was strongest for AD versus HC (AUC=0.88) and lower for comparisons involving MCI. Metabolites contributing most strongly to classification included myo-inositol, ascorbate, and choline-containing compounds, consistent with previous studies on AD-related neurochemical alterations. In addition, specific macromolecular components were identified as relevant features, suggesting a potential contribution of MM signals to the characterization of AD-related neurochemistry. Discussion: These findings support the use of short-echo-time 1H-MRS as a complementary tool for characterizing neurochemical changes in the AD continuum, with potential applications in disease characterization and monitoring, warranting validation in larger cohorts.