Magnetic Resonance Imaging

BACKGROUNDMild traumatic brain injury (mTBI) is a signature injury in civilian and military populations that remains invisible to detection by conventional radiological methods. Diffusion MRI has been identified as a potential clinical tool for revealing subtle microstructural alterations associated with mTBI. OBJECTIVEThis study evaluates whether a comprehensive and powerful diffusion MRI (dMRI) technique called mean apparent propagator (MAP) MRI can detect sequelae of mTBI. METHODSWe analyzed data from 417 participants of the GE/NFL prospective mTBI study which included 143 matched controls (mean age, 21.9 {+/-} 8.3 years; 76 women) and 274 patients with acute mTBI and GCS [≥]13 (mean age, 21.9 {+/-} 8.5 years; 131 women). All participants underwent MRI exams at up to four visits including structural high-resolution T1W, T2W, FLAIR-T2W, and dMRI, in addition to clinical assessments of post-concussive physical symptoms (RPQ-3), psychosocial functioning and lifestyle symptoms (RPQ-13), and postural stability (BESS). The dMRI data for each subject were co-registered across all visits and analyzed using the MAP-MRI framework to measure and map the distribution of net microscopic displacements of diffusing water molecules in tissue and ultimately compute the microstructural MAP-MRI tissue parameters including propagator anisotropy (PA), Non-Gaussianity (NG), return-to-origin probability (RTOP), return-to-axis probability (RTAP), and return-to-plane probability (RTPP). We quantified voxel-wise and region-of-interest (ROI)-based changes in these parameters across all four visits. RESULTSMAP-MRI parameter values were within the expected ranges and showed relatively little variation across visits. We found no significant differences in the longitudinal trajectories of these parameters between mTBI patients and controls. At acute post-injury timepoints, RPQ-3 and RPQ-13 scores were increased in mTBI patients relative to controls, while BESS scores were not significantly different between groups. Analysis of dMRI metrics and clinical mTBI markers showed significant correspondence between MAP-MRI metrics in cortical gray matter, caudate and pallidum and BESS scores. CONCLUSIONWe developed and tested a state-of-the-art quantitative image processing pipeline for sensitive analysis and detection of subtle tissue changes in longitudinal clinical diffusion MRI data. The absence of a significant statistical difference between populations in the dMRI parameters in this study suggests that the mTBI corresponded to acute post-injury clinical symptoms but that the injury was not severe enough to cause detectable microstructural damage/alterations, and that increased diffusion sensitization combined with improved analysis techniques may be needed. CLINICAL IMPACTThese findings suggest that acute mTBI (GCS[≥]13) may not be detectable with diffusion MRI. TRIAL REGISTRATIONClinicalTrials.gov NCT02556177

The SAFE MRI ECMO (NCT05469139) study established the safety of ultra-low-field 64mT MRI in patients receiving extracorporeal membrane oxygenation (ECMO) in the setting of intensive care and demonstrated that these images were highly sensitive in detecting acquired brain injuries. This retrospective analysis of prospectively collected observational data sought to expand on these findings in light of the crucial need for neurological monitoring while patients receive ECMO by evaluating the feasibility of volumetric analyses derived from ultra-low-field MR images. T2-weighted scans from thirty patients who received ultra-low-field MRI while undergoing ECMO at Johns Hopkins Hospital were analyzed using a volumetric pipeline to determine whole brain volume and volumes of total grey matter, total white matter, subcortical grey matter, ventricles, left hemisphere, right hemisphere, telencephalon, left and right lateral ventricles, the total intracranial volume, and the cerebellum. Segmented brain volumes in patients undergoing ECMO were comparable to measurements obtained using conventional field and ultra-low-field MRI in the absence of ECMO instrumentation. The subgroup analysis demonstrated subtle volumetric differences between patients supported with venoarterial ECMO and those receiving venovenous ECMO. These data provide the first evidence that ultra-low-field MRI provides volumetric measurements comparable to conventional field-strength MRI, even in the presence of ECMO circuitry, supporting its feasibility for neuroimaging in critically ill patients.

Background: Developing generalizable neuroimaging models is often hindered by limited labeled data which has led to an increased interest in unsupervised inverse learning. Existing approaches often neglect geometric principles and struggle with diverse pathologies. We propose a symmetry-informed inverse learning foundation model to address these shortcomings for robust and efficient anomaly detection in brain MRI. Methods: Our framework employs a reconstruction-to-embedding pipeline, trained exclusively on healthy brain MRI slices. A 2D U-Net uses a novel, symmetry-aware masking strategy to reconstruct a disorder-free slice. Difference maps are embedded into a 1024-dimensional latent space via a Beta-VAE. Anomaly scoring is performed using Mahalanobis distance. We evaluated generalization by fine-tuning on external lesion datasets, BraTS Africa (SSA), and the ADNI-derived Alzheimer disease cohort (Alz). Results: On the source metastasis (Mets) dataset, the framework achieved high performance (AB1+MSE: 99.28% accuracy, 99.79% sensitivity). Generalization to the external lesion dataset (SSA) was robust, with the Symmetry ROC configuration achieving 91.93% accuracy. Transfer to the Alzheimer dataset (Alz) was more challenging, achieving a peak accuracy of 70.54% with a high false-positive rate, suggesting difficulty in separating subtle, diffuse changes. Conclusion: The symmetry-informed inverse learning framework establishes a robust foundation model for neuroimaging, showing strong performance for focal lesions and successful generalization under domain shift. Limitations in diffuse neurodegeneration underscore the necessity for richer representations and multimodal integration to improve future foundation models.

Background and Objectives: Normal appearing white matter (NAWM) may already harbor subtle microstructural alterations not yet visible on conventional MRI. Quantitative Multi-Parametric Mapping (qMPM) such as Magnetization Transfer saturation (MTsat), longitudinal relaxation rate (R1), and Proton Density (PD) offer new possibilities for analyzing NAWM which are sensitive to demyelination, axonal loss, and edema. We aimed to characterize these alterations within white matter hyperintensities (WMH) and the perilesional NAWM (pNAWM), to gain insights into the underlying process of lesion progression. We also investigated their association with cerebrovascular risk factors (CVRF) and long-term cognitive performance. Methods: This investigation included the cerebral MRI data of 245 participants from the prospective Berlin Longterm Observation of Vascular Events (BeLOVE) study. Furthermore, 121 participants cognitive performance was evaluated at baseline and longitudinally at 2 years follow-up using Montreal Cognitive Assessment (MoCA). Regions of interest (ROIs) of WMH, pNAWM at 1, 2, 3 mm were assessed in comparison to the mirrored contralesional white matter (cWM). Linear mixed effects models were employed to demonstrate the pairwise comparisons between each region using estimated marginal means and the association of MPM metrics with CVRFs. Linear regression was used to assess the association with cognitive performance. Results: In 245 participants, (mean age 62 years, SD: 12 years; 29.8% females), MPM metrics demonstrated a clear spatial gradient of microstructural injury. MTsat and R1 values were lower in WMH compared to cWM (lower case Greek beta = -0.48 (-0.52 - -0.44) and lower case Greek beta = -0.07 (-0.08 - -0.06), p<0.001, respectively) and showed gradual recovery with increasing distance indicating a microstructural gradient in pNAWM. Conversely, PD values were higher in WMH and decreased peripherally (lower case Greek beta = 2.32 (2.05 - 2.61, p<0.001). No substantial associations were found between MPM parameters and CVRFs in our cohort. At baseline and 2-year follow-up, cognitive performance was associated with higher pNAWM R1 values, whereas MTsat were only moderately associated. Discussion: Quantitative MPM reliably detects microstructural alterations not only within WMH, but also in pNAWM, confirming the high sensitivity of qMPM to subtle tissue pathology and support its utility as a promising biomarker for longitudinal studies and monitoring therapeutic effects.

Background and Purpose: 2-[18F] fluoro-2-deoxy-D-glucose positron emission tomography (static PET) has mixed specificity and sensitivity in targeting epileptic zones in the noninvasive stage of epilepsy surgery evaluations. We compared the signal quality of static PET compared to a method of interictal dynamic PET (iD-PET). Materials and Methods: We calculated the signal quality of static PET and iD-PET obtained from a cohort of patients with focal epilepsy. We developed a Bayesian regional estimated signal quality (BRESQ) technique to objectively compare signal-to-noise ratios (SNRs) by region of interest (ROI) within subjects. Results: Adjusted for ROI size and neighboring regions, iDPET was superior to sPET with probability >95% in 8/36 regions; >90% in 21/36 regions; >80% in 29/36 regions. The top five regions with the largest adjusted SNR differences (greatest magnitude of iDPET superiority) were the Temporal Mesial (Left and Right), Occipital Lateral (Left and Right), and the Left Frontal Inferior Base. Conclusions: We found that iDPET yielded a superior SNR in most ROI. BRESQ offers a scalable and generalizable method to quantify signal quality between brain mapping modalities.

BackgroundQuantitative cerebral blood flow (CBF) measured with [15O]water positron emission tomography (PET) is the reference standard for quantifying brain perfusion. However, clinical interpretation of individual CBF measurements is limited by the absence of large normative datasets accounting for physiological variability across the adult lifespan. Long-axial field-of-view PET enables high-sensitivity quantitative [15O]water perfusion imaging without arterial blood sampling, allowing normative characterization of cerebral perfusion at unprecedented scale. The aim of this study was to establish normative and covariate-adjusted models of cerebral blood flow across the adult lifespan using total-body [15O]water PET. MethodsQuantitative CBF measurements were obtained in 302 neurologically healthy adults (age 21-86 years) using total-body [15O]water PET. Linear mixed-effects models were used to evaluate the effects of age, sex, body mass index (BMI), and blood hemoglobin concentration on CBF and to generate normative prediction models across the adult lifespan. Between-subject and within-subject variability were estimated from repeated scans in a subset of participants (n=51). ResultsMean grey matter CBF was 46.1 mL/(min*dL), with substantial inter-individual variability but high within-subject reproducibility (intraclass correlation coefficients 0.78-0.89). Advancing age was associated with a decline in CBF of approximately 7% per decade (p_FDR < 10-12). Higher BMI was associated with lower CBF (approximately -6% per 10 kg/m2; p_FDR < 0.01). Women exhibited higher CBF than men (approximately 7.5%), but this difference was largely explained by lower blood hemoglobin concentration in women. Covariate-adjusted models were used to generate normative predictions and prediction intervals describing expected CBF across adulthood. ConclusionThis study establishes a normative database of quantitative cerebral blood flow across the adult lifespan using high-sensitivity [15O]water PET. Age, BMI, and hemoglobin are major determinants of inter-individual variability in CBF. The resulting generative models provide a quantitative reference framework for interpreting cerebral perfusion measurements and may enable automated detection of abnormal brain perfusion in clinical PET imaging.

Predicting response to induction chemotherapy (IC) and overall survival (OS) is critical for optimizing treatment in patients with locally advanced nasopharyngeal carcinoma (LANPC). This study aimed to develop and validate a multi-task deep learning model integrating pretreatment MRI and whole slide images (WSIs) to predict IC response and OS in LANPC. Pretreatment MRI and WSIs from 404 patients with LANPC were retrospectively collected to construct a multi-task model (MoEMIL) for the simultaneous prediction of early IC response and OS. MoEMIL employed multi-instance learning to process WSIs, PyRadiomics and a convolutional neural network (ResNet50) to extract MRI features, and fused multimodal features through a multi-gate mixture-of-experts architecture. Clustering-constrained attention multiple instance learning and gradient-weighted class activation mapping were applied for visualization and interpretation. MoEMIL effectively stratified patients into good and poor IC response groups, achieving areas under the curve of 0.917, 0.869, and 0.801 in the train, validation, and test sets, respectively, and outperformed the deep learning radiomics model, the pathomics model and TNM staging. The model also stratified patients into high- and low-risk OS groups (P < 0.05). MoEMIL shows promise as a decision-support tool for early IC response prediction and prognostication in LANPC. Author SummaryWe have developed a deep learning model that integrates two types of medical images, including magnetic resonance imaging (MRI) and digital pathological slices, to simultaneously predict response to induction chemotherapy and prognosis in patients with locally advanced nasopharyngeal carcinoma. Current treatment decisions primarily rely on traditional tumor staging (TNM), which often fails to comprehensively reflect the complexity of the disease. Our model, named MoEMIL, was trained and tested on data from 404 patients across two hospitals and consistently outperformed both single-model approaches and TNM staging methods. By identifying patients who exhibit poor response to induction chemotherapy or higher prognostic risk, our tool can assist clinicians in achieving personalized treatment, enabling intensified management for high-risk patients and avoiding unnecessary side effects for low-risk patients. Additionally, we visualize the models reasoning process through heat map generation, which highlights the image regions exerting the greatest influence on prediction outcomes. This work represents a step toward more precise treatment for nasopharyngeal carcinoma; however, larger-scale prospective studies are required before the model can be integrated into routine clinical practice.

Neurodegenerative diseases such as Mild Cognitive Impairment (MCI), Multiple Sclerosis (MS), Parkinson s Disease (PD), and Amyotrophic Lateral Sclerosis (ALS) are becoming more prevalent. Each of these diseases, despite its specific pathophysiological mechanisms, leads to widespread reorganization of brain activity. However, the corresponding neurophysiological signatures of these changes have been elusive. As a consequence, to date, it is not possible to effectively distinguish these diseases from neurophysiological data alone. This work uses Magnetoencephalography (MEG) resting-state data, combined with interpretable machine learning techniques, to support differential diagnosis. We expand on previous work and design a Riemannian geometry-based classification pipeline. The pipeline is fed with typical connectivity metrics, such as covariance or correlation matrices. To maintain interpretability while reducing feature dimensionality, we introduce a classifier-independent feature selection procedure that uses effect sizes derived from the Kruskal-Wallis test. The ensemble classification pipeline, called REDDI, achieved a mean balanced accuracy of 0.81 (+/-0.04) across five folds, representing a 13% improvement over the state-of-the-art, while remaining clinically transparent. As such, our approach achieves reliable, interpretable, data-driven, operator-independent decision-support tools in Neurology.

BackgroundThe World Health Organization has developed several global template protocols for epidemiological investigations, including for household transmission investigations (HHTIs). These investigations facilitate rapid characterisation of novel or re-emerging respiratory pathogens and support evidence-based public health actions. Beyond technical readiness, community buy-in is central to the feasibility and acceptability of HHTIs. Research is needed to determine the perceived legitimacy among the community to inform local protocol adaptation and development of implementation plans that consider community attitudes and needs. MethodsIn 2025, we conducted a convenience survey of community members living in Victoria, Australia to explore: their understanding of emerging respiratory diseases; their willingness to take part in public health surveillance activities such as HHTIs; the acceptability of clinical and epidemiological data collection and respiratory/blood sample collection as main components of HHTIs, and; participant comfort towards including their companion animals in HHTIs. ResultsWe received 282 survey responses, of which 235 were included in the analysis dataset. Compared to the general Victorian population, our participants included a higher proportion of participants who reported being female, tertiary-educated, of Aboriginal and/or Torres Strait Islander heritage, born in Australia and speaking only English at home. Participants indicated overall high levels of comfort and acceptability towards participation in HHTIs, particularly in relation to clinical and epidemiological data collection, with lesser but still high levels of comfort with providing multiple respiratory specimens in a 14-day period. Participants were least comfortable with other specimens such as urine and blood. Involving companion animals in HHTIs was similarly acceptable as human-focused components. ConclusionsDespite our survey population being non-representative of the general Victorian population, our findings provide valuable descriptive insights into the acceptability of HHTIs in Victoria, Australia from which to benchmark future local and international surveys and community engagement activities.

BackgroundTimely cancer diagnosis in children and adolescents is critical to improving outcomes, yet substantial variation in diagnostic intervals persists across cancer types and care settings. We aimed to quantify time to diagnosis and assess variations by patient, demographic, and system-level factors. MethodsWe conducted a retrospective population-based study of children and adolescents aged 0-19 years diagnosed with one of 12 common cancers between 2010 and 2022 in Quebec, Canada. The diagnostic interval was defined as the time from first cancer-related healthcare encounter to diagnosis. We calculated medians and interquartile ranges (IQR) overall and by cancer type and used multivariable quantile regression to identify factors associated with time to diagnosis at the 25th, 50th, and 75th percentiles. ResultsAmong 2,927 individuals with cancer, diagnostic intervals varied by cancer type and age. Median intervals were longest for carcinomas (100 days; IQR 33-192) and shortest for leukemias (8 days; IQR 3-44). Compared with children living in Montreal, living in regional areas and other large urban centres was associated with longer 50th and 75th percentiles of time to diagnosis for hepatic and central nervous system (CNS) tumours. Diagnostic intervals were shorter in the post-pandemic period (2020-2022) across several cancer sites, with CNS tumours showing reductions across all quantiles. InterpretationDiagnostic timeliness differed by cancer type, age, and rurality, but not by sex, material, or social deprivation. The shorter diagnostic intervals observed in the post-pandemic period suggest that pandemic-related changes in care pathways may have expedited diagnosis for some cancers.

ObjectivesWe determined the frequency of sexually transmitted infection (STI) testing among people accessing sexual health services (SHS) in England. MethodsWe assessed STI testing frequency in face-to-face and online SHSs in England using data from the GUMCAD STI surveillance system. We quantified different combinations of tests (e.g. single chlamydia test or full STI screen), number of tests completed in 2024 and test positivity by sociodemographic and behavioural characteristics, as well as clinical setting and outcomes. ResultsOverall, there were 2,222,028 attendances at SHS in England in 2024 that involved tests for chlamydia, gonorrhoea, syphilis and/or HIV. Most of these attendances involved tests for all four of these STIs. Most people accessing SHS in England tested once (80.1%), and a small minority (1.9%) tested at least quarterly (4+ times). Some groups had a comparably larger proportion of quarterly testers; these included gay, bisexual, and other men who have sex with men (GBMSM) (6.7%), London residents (3.6%), online testers (2.5%), people using HIV-PrEP (13%), and people with 5+ partners in the previous 3 months (10.6%). Only 10.5% of GBMSM reporting higher-risk sexual behaviours tested quarterly despite recommendations for quarterly testing in this group. ConclusionsThe majority of those who tested for STIs in England in 2024 only tested once. The minority who tested at least quarterly had a higher proportion of GBMSM, people using HIV-PrEP, London residents and people reporting higher risk behaviours. Quarterly testing often appears to be aligned with current testing recommendations in England; however, we also observed that only a low proportion of behaviourally high-risk GBMSM and HIV-PrEP users are meeting these recommendations. It is important to acknowledge groups with lower or higher testing frequency when developing interventions and updating guidelines related to STI testing. WHAT IS ALREADY KNOWN ON THIS TOPICThe effectiveness of asymptomatic testing for chlamydia and gonorrhoea in gay, bisexual and other men who have sex with men (GBMSM), and the potential impact of the consequent increased antibiotic use on rising antimicrobial resistance and individual harm has recently been questioned. Testing and treatment remains a key pillar of STI prevention and management; despite this, there is limited evidence of STI testing frequency within sexual services (SHS) on a national level. WHAT THIS STUDY ADDSThis analysis shows that the majority of people attending SHSs in England in 2024 tested once, and only a small proportion of behaviourally high-risk people tested frequently. HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICYAwareness of groups that are behaviourally high risk but testing infrequently is important to guide interventions and messaging regarding STI testing. The low levels of frequent testing, even among those who would be recommended quarterly testing under UK guidelines, provides important context for wider discussion around asymptomatic STI screening.

Wearable-derived physiological features have been associated with disease risk, but most current studies focus on single conditions, limiting understanding of cross-disease patterns. This study adopts a trans-diagnostic approach to examine whether wearable data capture shared and condition-specific physiological signatures across multiple chronic conditions spanning physical and mental health, and then evaluates the utility of these features for disease classification. A total of 9,301 patients with at least 21 days of consecutive FitBit data from the All of Us Controlled Tier Dataset version 8 were analyzed. Disease subcohorts included cardiovascular disease (CVD), diabetes, obstructive sleep apnea (OSA), major depressive disorder (MDD), anxiety, bipolar disorder, and attention-deficit/ hyperactivity disorder (ADHD), chosen based on prevalence and relevance. Logistic regression and XGBoost models were fitted for each disease subcohort versus the control cohort. We found that compared to using just baseline demographic and lifestyle features, incorporating wearable-derived features enabled improved classification performance in all subcohorts for both models, except for ADHD where improvement was mainly observed for ROC-AUC in logistic regression model likely due to the smaller sample size in ADHD subcohort. The largest performance gains were observed in MDD (increase in ROC-AUC of 0.077 for Logistic regression, 0.071 for XGBoost; p < 0.001) and anxiety (increase in ROC-AUC of 0.077 for logistic regression, 0.108 for XGBoost; p < 0.001). This study provides one of the first comprehensive transdiagnostic evaluations of wearable-derived features for disease classification, highlighting their potential to enhance risk stratification in the real-world setting as a practical complement to clinical assessments and providing a foundation to explore more fine-grained wearable data. Author summaryWearable devices such as fitness trackers and smartwatches are becoming increasingly popular and affordable, providing continuous measurements of heart rate, physical activity, and sleep. Alongside the growing digitization of health records, this creates new opportunities for large-scale, real-world health studies. In this study, we analyzed wearable-derived physiological patterns across a range of chronic conditions spanning both physical and mental health to better understand how these signals relate to disease risk. We found that incorporating wearable-derived heart rate, activity and sleep features improved disease risk classification across several conditions, with particularly strong gains for major depressive disorder and anxiety. By examining how individual features contributed to model predictions, we also identified meaningful associations between physiological signals and disease risk. For example, both duration and day-to-day variation of deep and rapid eye movement (REM) sleep were associated with increased risk in certain conditions. Our study supports the development of real-time, automated tools to assess disease risk alongside clinical care.

Childhood socioeconomic position (SEP) can have lifelong effects on health. Many studies have used adult height as a surrogate marker for early-life conditions. In this study, we derived the non-genetic component of height, calculated as the residual from sex-specific standardized height regressed on genetically predicted height, as a surrogate for childhood SEP, using data from the Hispanic Community Healthy Study/Study of Latinos (2008-2011). A positive residual would indicate favorable early-life conditions promoting growth, while a negative residual indicates early-life adversity that may stunt the development. The height residual was associated with early-life variables such as parental education, year of birth, US nativity and age at first migration to the US (50 states/DC), supporting the validity of height residual as a surrogate for early-life conditions. Furthermore, a height residual was positively associated with better cardiovascular health (CVH) and cognitive function among middle-aged and older adults. Interestingly, among <35 years old, the height residual was negatively associated with the "Lifes Essential 8" clinical CVH scores. These results suggest the non-genetic component of height as a surrogate for childhood environment, with predictive value for CVH and cognitive function.

BackgroundAccelerometer-derived behavioral phenotype captures multidimensional aspects of human behavior extending well beyond physical activity, encompassing light exposure, step counts, physical activity patterns, sleep, and circadian rhythms. Whether these five domains constitute a unified behavioral architecture underlying cancer risk and whether circadian organization and light exposure confer incremental predictive value beyond movement volume alone remains to be comprehensively established. MethodsWe conducted an accelerometer-wide association study (AWAS) encompassing the complete accelerometer-derived behavioral exposome across five behavioral domains in UK Biobank participants with valid wrist accelerometry data. Incident solid cancers were designated as the primary endpoint, with prespecified site-specific solid cancers and hematological malignancy as secondary outcomes. Cox proportional hazards models with age as the timescale were used. The minimal covariate set served as the primary reporting tier, followed by sensitivity analyses additionally adjusting for adiposity/metabolic factors, independent activity patterns, shift work history, and accelerometry measurement quality. Nominal statistical significance was defined as two-sided P < 0.05 ResultsAmong 89,080 participants, 6,598 incident solid cancer events were observed over a median follow-up of 8.39 years. In the minimally adjusted model, the pan-solid-tumor association atlas was dominated by signals from activity volume, inactivity fragmentation, and circadian rhythm. Higher overall acceleration (HR per SD: 0.91, 95% CI: 0.89-0.94) and higher daily step counts (HR: 0.93, 95% CI: 0.90-0.95) were independently associated with reduced solid cancer risk, while inactivity fragmentation metrics were consistently linked to higher risk. Notably, circadian rhythms, most prominently cosinor mesor (Midline Estimating Statistic of Rhythm under cosinor model), emerged as leading inverse risk signals, underscoring the independent contribution of circadian behavioral architecture. Site-specific analyses revealed pronounced heterogeneity across tumor sites. Lung cancer exhibited a robust inverse activity-risk gradient, while breast cancer showed reproducible associations with MVPA. Most strikingly, nocturnal light exposure demonstrated a tumor-site-specific association confined to pancreatic cancer, a signal absent across all other sites examined. Associations for uterine cancer were predominantly inactivity-related and substantially attenuated following adjustment for adiposity and metabolic factors. ConclusionsAcross five accelerometer-derived behavioral domains, solid cancers as a whole were most consistently associated with a high-movement, low-fragmentation, and circadian-coherent behavioral profile. While site-specific heterogeneity exists, the broad cancer risk landscape is dominated by movement volume, inactivity fragmentation, and circadian rhythmicity. Light exposure, although more localized in its contribution, demonstrates a potentially novel and specific association with pancreatic cancer risk. These findings support a five-domain behavioral exposome framework for cancer epidemiology and, importantly, position circadian rhythm integrity and nocturnal light exposure as critically understudied dimensions warranting dedicated mechanistic investigation.

Background: Dengue is rapidly emerging in parts of Europe. How households value vector control attributes, and whether inferences depend on decision models or message framing, is unclear. Methods: We conducted a split-ballot online experiment among adults in Italy and France, as well as a hotspot subsample from Marche, Italy. National samples included 1,505 respondents in Italy and 1,501 in France; 183 respondents were recruited in Marche. Participants were randomised to a discrete choice experiment (random utility maximisation) or a regret-based choice experiment (random regret minimisation) and to one of three pre-task messages (control, loss aversion, community values). Each respondent completed 12 choice tasks comparing two dengue control programmes and an opt-out. We estimated mixed logit and mixed random-regret models with random parameters and treatment effects. Results: Across frameworks, nearby cases and high mosquito prevalence were the dominant drivers of programme uptake, whereas cost and operational burden were secondary. In pooled analyses, loss-aversion messaging increased the weight on high mosquito prevalence in both models (from 0.483 to 0.547 in the utility model; from 0.478 to 0.557 in the regret model). Cost effects were small nationally but larger in the hotspot subsample. Conclusions: Risk salience dominates preferences for dengue vector control in these European settings. Random utility and random regret models yield consistent rankings of attributes but differ in behavioural interpretation and some secondary effects; messaging effects were modest and context dependent.

BackgroundFamily-based HIV index case testing identifies family members with unknown HIV status and links them to care. Data are limited in southern Ethiopia. MethodsA facility-based cross-sectional study was conducted among 377 adults on antiretroviral therapy (ART) in Wolaita Zone, Southern Ethiopia, from November 2022 to May 2023. Participants were selected using systematic random sampling. Data were collected via interviewer-administered semi-structured questionnaire. Multivariable logistic regression identified factors associated with index case family testing. Adjusted odds ratios (AOR) with 95% confidence intervals (CI) were calculated, and statistical significance was declared at p < 0.05. ResultsThe proportion of index case family testing for HIV was 84.9% (95% CI: 81.2- 88.6). In multivariable analysis, urban residence (AOR = 2.8; 95% CI: 1.16-6.75), duration on ART greater than 12 months (AOR = 13.0; 95% CI: 4.6-36.9), disclosure of HIV status to family members (AOR = 5.6; 95% CI: 1.9-16.5), discussion of HIV status with family members (AOR = 6.6; 95% CI: 1.9-23.2), and being counselled by health professionals to bring families for testing (AOR = 6.3; 95% CI: 2.1-19.0) were significantly associated with index case family testing. ConclusionThe prevalence of family-based HIV index case testing in Wolaita Zone was 84.9%, below the national 95% target. Health professionals should strengthen counselling on ART adherence, status disclosure, family discussion, and active referral to improve testing uptake among family members of people living with HIV.

Study questionWhat are the characteristics and treatment outcomes of women who undertook planned egg freezing (PEF) in Australia and New Zealand between 2009 and 2023? Summary answerThere has been an average yearly increase in the uptake of PEF of 35%, with most women undergoing a single PEF procedure in their mid-thirties. Given ten years follow-up a little over one in four women return, with nearly half of those using donor sperm and one-third achieving a live birth. What is known alreadyPEF, where women freeze their eggs as a strategy to preserve fertility, has increased dramatically in high income countries in the last decade. Despite the rapid uptake of PEF, there remains limited information to guide women, clinicians and policy makers regarding the characteristics of women undertaking this procedure and treatment outcomes. Study design, size, durationA retrospective population-based cohort study of all women who undertook PEF in Australia and New Zealand between 2009 and 2023, including their subsequent return to thaw their eggs and treatment outcomes. Where women returned to utilise their eggs, all subsequent embryo transfer procedures were linked enabling calculation of live birth rates per woman. Participants/materials, setting, methods20,209 women who undertook PEF in Australia and New Zealand between 2009 and 2023 including 1,657 women who returned to thaw their eggs. Main results and the role of chanceThere has been a huge increase in uptake of PEF, from 55 women in 2009 to 4,919 in 2023. Women who freeze their eggs are typically aged 34-38 years (interquartile range) and nulliparous (98.6%). For women with at least 10 years follow-up (i.e. undertook PEF in 2009-13; N=514), 27.9% returned and thawed their frozen eggs (average time to return: 4.9 years). This reduced to 22.1% in those with at least 5 years follow-up (i.e. undertook PEF in 2009-2018; N=4,288). Of those who used their frozen eggs, 47% used donor sperm. After at least two years follow up, 33.9% had a live birth, rising over time to 37.8% for eggs thawed between 2019-2021. Limitations, reasons for cautionIn the timeframe 2009-2019 we did not have information on whether egg freezing occurred because of a cancer diagnosis, a cohort we wished to exclude from the study. As a result, for this timeframe we weighted observations by the probability that egg freezing occurred due to cancer, with the prediction model developed on the years 2020-2023. Wider implications of the findingsThis study provides recent and comprehensive data on PEF to guide prospective patients and clinicians and inform policy. The exponential growth in PEF in Australia and New Zealand mirrors trends in other high-income countries, suggesting a doubling time of 2-3 years. Study findings highlight the need for setting realistic expectations about the likelihood of returning to use frozen eggs and live birth rates. Study funding/competing interest(s)2020-2025 MRFF Emerging Priorities and Consumer Driven Research initiative: EPCD000014

1.Study questionDo singletons conceived by medically assisted reproduction (MAR) experience an elevated incidence of childhood cancers and are they at a greater risk of such cancers compared to naturally-conceived singletons? Summary answerWe found no strong evidence the adjusted risk of childhood cancers is increased for MAR-conceived singletons. What is known alreadyThere is longstanding concern children conceived via MAR may be at increased risk of childhood cancer. Current epidemiological evidence does not support such a relationship. Study design, size, durationWe conducted a retrospective population-based cohort study of 5,104,121 singletons born in Australia between 1991 and 2019. Median follow-up time varied from 4 to 10 years depending on mode of conception. Participants/materials, setting, methodsWe linked birth records to public medical insurance data of the mother to ascertain MAR conception. We classified treatment as ovulation induction/intrauterine insemination (OI/IUI) or assisted reproductive technology (ART; IVF/ICSI), with ART coded as either fresh embryo transfer or frozen embryo transfer. The cohort included 4,924,354 naturally-conceived singletons and 179,767 singletons conceived via MAR. We calculated standardised incidence ratios (SIRs) to ascertain differences in population incidence of childhood cancer, and generated hazard ratios (HRs) using flexible parametric survival models controlling for key confounders. We report absolute incidence and risk differences for both statistical approaches. Main results and the role of chanceThere was no increase in the incidence or risk of all childhood cancers combined for singletons conceived via MAR, either any MAR or specific MAR types. There was some evidence the incidence of leukemias, myeloproliferative diseases, and myelodysplastic diseases was increased after ART compared to the general population (SIR: 1.32, 95% CI 1.02-1.68; equating to 2.09, 95% CI 0.13-4.44 extra cancers per 100,000 person-years), but no increased risk after adjusting for available confounders (HR: 1.04, 95% CI 0.73-1.46). These cancers showed increased incidence and risk for those conceived via IVF (SIR: 1.54, 95% CI 1.01-2.26; HR: 1.77, 95% CI 1.06-2.95), but not ICSI (SIR: 1.27, 95% CI 0.83-1.85; HR: 0.76, 95% CI 0.48-1.22). Incidence of renal tumours was elevated after IVF (SIR: 2.37, 95% CI 1.02-4.67; equating to 1.83, 95% CI 0.03-3.99 extra cancers per 100,000 person-years) and frozen transfer ART (SIR: 2.52, 95% CI 1.09-4.97; equating to 2.12, 95%CI 0.12-5.53 extra cancers per 100,000 person-years), however risk was not elevated after adjusting for available confounders (HR: 1.06, 95% CI 0.47-2.38; and HR: 1.63, 95% CI 0.73-3.61 respectively). Limitations, reasons for cautionWe did not have information on parental cause of infertility, which could be a confounder for childhood cancer, although we did adjust for parental history of cancer. For many specific cancer types, fewer than 50 cases were observed in total. Given the number of comparisons reported and closeness of the lower-bound confidence interval to 1, we cannot exclude that a significant association between conception via IVF and leukemias, myeloproliferative diseases, and myelodysplastic diseases reflects a type I error. Wider implications of the findingsOur findings align generally with published meta-analyses on the risk of childhood cancers following MAR conception and reinforce the need for very large studies to increase confidence. Parents who have conceived via MAR and their offspring can be reassured there is not strong evidence the treatments increase the overall incidence or risk of childhood cancer. Study funding/competing interest(s)This work was funded by the National Health and Medical Research Council (NHMRC: APP1164852). Dr ARW declares that their involvement in this work was supported by employment at UNSW Sydney. Prof CMV declares payment to their institution from the National Health and Medical Research Council (APP1164852). Prof NH declares payment to their institution from the National Health and Medical Research Council (APP1164852); royalties and licenses for Berek and Hackets Gynecologic Oncology (Walters Kluwer); royalties and licenses for Hacker and Moores Essentials of Obstetrics and Gynecology (Elsevier); consulting fees from Darwin Hospital and Gold Coast University Hospital; support for attending the British Gynaecological Cancer Society meeting in Aberdeen, UK, Jun 2023; support for attending the Symposium on Gynaecological Cancer in Budapest, Hungary, Nov 2023; support for attending the International conference of the Rajiv Gandhi Cancer Centre in Delhi, India, Mar 2025; and membership of the Medical Advisory Committee for TruScreen (Australia and New Zealand). A/Prof SO declares that they received payment to their institution from the National Health and Medical Research Council (APP1164852); they received a grant from the European Society for Human Reproduction and Embryology (Open call 2022) including payment to their institution; and that they are a member of the Advisory Board of the Cervical Screening Program in Norway through The Norwegian Institute of Public Health (NIPH), for which they were reimbursed travel expenses to their institution. Prof MC declares support for Theramex European Society for Human Reproduction and Embryology registration and Fertility Society of Australia and New Zealand registration and accommodation. A/Prof USD declares that her involvement in this work was supported via an Early Career Fellowship from the Cancer Institute NSW (ID: 2020/ECF1163) and employment at UNSW Sydney. A/Prof USD also declares payment to their institution from the National Health and Medical Research Council (APP2035240) and the Medical Research Future Fund (APP2032214; APP2038377), and the Australian Research Council (DP240100072) as well as current grants from NSW Health, Prince of Wales Hospital Foundation, and unpaid involvement as an Associate Editor for the "Journal of Psycho-Oncology Research and Practice". Prof LJ declares payment to their institution from the National Health and Medical Research Council (APP1164852). Prof RJN declares they are the Chair of the Clinical Advisory Committee, Westmead Fertility; External mentor at VinMec hospital; Editorial Editor at the journal "Fertility and Sterility"; and has received funding from the National Health and Medical Research Council (NHMRC) for the NHMRC Centre for Research Excellence in Womens Health in Reproductive Life (CRE WHiRL). A/Prof CS declares stock or stock options associated with CSL Ltd, Sigma Healthcare Ltd, Resmed Inc, Medical Developments International Ltd, Vitrafy Life Sciences Ltd, Intuitive Surgical, and Steris PLC. Prof GMC declares payment to their institution from the National Health and Medical Research Council (APP1164852). Prof CV declares payment to their institution from the National Health and Medical Research Council (APP1164852); research grants receive from Merck KGaA and Ferring; payments for honoraria from Merk Ltd, Merk Sharpe & Dohme, Ferring, Organon, Gedeon-Richter for being an invited lecturer in scientific meetings/conferences on multiple occasions as well as member of advisory boards for these companies who have a commercial portfolio in the field of assisted reproduction technology (ART); and speaking fees from IBSA, Vianex, Sonapharm; travel support for their participation in scientific meetings/conferences both nationally and internationally, usually as an invited speaker for the following companies - Merck Ltd, Merck Sharpe & Dohme, Ferring, Organon, Gedeon-Richter; unpaid involvement as a Board member of the Hellenic Society of Fertility and Sterility, Member of the Editorial Board of the journal "Human Reproduction", Senior Deputy of the Coordination Committee of the Special Interest Group "Reproductive Endocrinology" of the European Society for Human Reproduction and Embryology, Member of the Editorial Board of the journal "F&S Reviews", Member of the Editorial Board of the journal "RBM Online", Member of the Editorial Board of the journal "Reproductive Biology & Endocrinology", Member of the Editorial Board of the journal "Frontiers in Endocrinology", and Member of the Editorial Board of the journal "Reproductive Sciences". SubjectReproductive epidemiology

Background: The enterotype concept proposed that gut microbiomes cluster into discrete types, but subsequent critiques demonstrated that such clustering depends on methodological choices, that the number of clusters is not fixed, and that faecal samples cannot capture spatial heterogeneity along the gastrointestinal tract. The stomach remains particularly understudied, and no systematic classification exists for gastric microbial community types. Methods: We assembled a multi-cohort dataset of 566 gastric mucosal samples spanning healthy controls to gastric cancer, with both Helicobacter pylori (HP)-negative and HP-positive individuals. Critically, we applied the key methodological lessons of the enterotype debate: we used a variational autoencoder (VAE) for dimensionality reduction to learn a continuous latent representation without forcing discrete structure, determined the optimal number of clusters using the Silhouette index (an absolute validation measure) across K=2 to K=10 rather than arbitrarily selecting a cluster number, and performed transparent evaluation of multiple clustering solutions. This VAE-plus-silhouette workflow directly addresses the critiques leveled against the original enterotype analysis. Results: Four gastotypes were identified, with K=4 achieving the highest mean silhouette score, indicating good cluster cohesion and separation. Two gastotypes (Variovorax-type and Trabulsiella-type) were significantly enriched in HP-positive samples, while two gastotypes (Bacteroides-type and Streptococcus-type) were significantly enriched in HP-negative samples. Random Forest and Gradient Boosting achieved excellent baseline performance for predicting HP infection (AUC = 0.990 and 0.993). Conclusions: The VAE-plus-silhouette workflow provides a robust, data-driven approach for identifying gastotypes without forcing discrete structure or arbitrarily fixing cluster numbers. Using this framework, we identified four gastotypes with significantly different HP infection rates. Variovorax-type and Trabulsiella-type showed strong HP-positive enrichment, while Bacteroides-type and Streptococcus-type showed strong HP-negative enrichment. These findings demonstrate that methodological advances from the enterotype controversy can be successfully transferred to the stomach, offering a reproducible taxonomy for stratifying HP infection status with potential clinical utility.

Background and Aims: Alterations in immunoglobulin G (IgG) N-glycosylation are implicated in inflammatory bowel disease (IBD); however, the robustness of IgG glycan signatures across IBD cohorts with diverse demographics and geographic origins remains underexplored. We aimed to determine whether compositional data analysis (CoDA) and machine learning (ML) can identify IBD-related IgG N-glycan signatures and whether these signatures capture disease-associated acceleration of biological aging. Methods: We analyzed the IgG glycome profiles of 1,367 plasma samples collected from healthy controls (HC), symptomatic controls (SC), and people with newly diagnosed Crohn's (CD), and ulcerative colitis (UC) across four cohorts (UK, Italy, United States, and Netherlands). IgG glycosylation was analyzed by ultra-high-performance liquid chromatography, yielding 24 total-area-normalized glycan peaks (GPs). Analyses were performed using cross-sectional data obtained at baseline. CoDA-powered association analyses were used to identify disease-related effects on GPs while controlling for demographic covariates. ML models were trained and evaluated to assess generalizability to unseen cohorts and demographic subgroups, with a focus on discrimination and reliability. Results: Across all cohorts, people with IBD demonstrated accelerated biological aging as quantified by the GlycanAge index. This was accompanied by consistent reductions in IgG galactosylation, with effects partially modulated by age. Classification models trained on glycomics and demographics achieved robust discrimination (AUROC~0.80) between non-IBD (HC+SC) and IBD across cohorts. Conclusion: These findings reveal accelerated biological aging in people with IBD and support the translational potential of IgG glycans as biomarkers and a novel route toward clinically interpretable personalized risk estimates.