Dietary fat composition modulates host physiology and the gut microbiome, but the long-term effects of specific fat sources and the extent to which these changes resolve after dietary reversal remain incompletely defined. Here, we present a longitudinal multi-omic resource of mice maintained for one year on a purified control diet, seven high-fat diets differing in predominant fat source, or reversal regimens in which animals were switched from high-fat to control diet after 4 or 9 months. We further incorporated two cohorts with distinct pre-existing microbiome configurations to determine how baseline community structure shapes diet-induced remodeling of the gut microbiome ecosystem. By integrating longitudinal phenotyping, fecal metagenomics, fecal metabolomics, plasma metabolomics and lipidomics, and intestinal single-cell RNA sequencing, we defined the shared and dietary fat-specific responses across host and microbiome compartments. Baseline microbiome composition strongly influenced microbial responses to diet, indicating that pre-existing community structure is a major determinant of dietary ecosystem remodeling. Although many altered features shifted toward baseline after dietary reversal, only approximately half of diet-associated microbial changes recovered within the study window. A subset of taxa exhibited persistent alterations, including sustained depletion of Lactobacillus johnsonii and Bifidobacterium pseudolongum and sustained enrichment of Alistipes finegoldii, consistent with a "microbiome memory" of prior high-fat diet exposure. This memory effect is mirrored in the host, by sustained suppression of major histocompatibility complex class II (MHC-II) gene expression in intestinal epithelial cells after dietary reversal. These findings indicate that dietary fats leave a lasting imprint on the host-microbiome interactome that survives dietary intervention. Together, these data establish a resource for defining how dietary fat source, baseline microbiome composition, and dietary history shape host-microbiome states. The entire resource is available online as an RShiny app.

Hypoxic Ischemic Encephalopathy (HIE) represents a brain dysfunction, affecting approximately 1 to 5 per 1000 full-term neonates. The precise delineation and segmentation of HIE-related lesions in neonatal brain Magnetic Resonance Images (MRI) are pivotal in advancing outcome predictions, identifying patients at high risk, elucidating neurological manifestations, and assessing treatment efficacies. Despite its importance, the development of algorithms for segmenting HIE lesions from MRI volumes has been impeded by data scarcity. Addressing this critical gap, we organized the first BONBID-HIE challenge with diffusion MRI data (Apparent Diffusion Coefficient (ADC) maps) for HIE lesion segmentation, in conjunction with the MICCAI 2023. Totally 14 algorithms were submitted, employing a gamut of cutting-edge automatic machine-learning-based segmentation algorithms. Our comprehensive analysis of HIE lesion segmentation and submitted algorithms facilitates an in-depth evaluation of the current technological zenith, outlines directions for future advancements, and highlights persistent hurdles. To foster ongoing research and benchmarking, the annotated HIE dataset, developed algorithm dockers, and unified evaluation codes are accessible through a dedicated online platform (https://bonbid-hie2023.grand-challenge.org).

Nutrition insecurity is a major driver of poor cardiovascular health in Indigenous communities. Medically tailored meals may improve heart failure outcomes and quality of life. There is growing momentum among Indigenous communities to reclaim traditional precontact foods to improve cardiovascular health. In this context, utilizing community-based-participatory methods, we designed MUTTON-HF (Medically Utilized Tailored Traditional Foods to Optimize Nutrition in Heart Failure)-an Indigenous culturally and medically tailored meals program that locally sources Native produce and meat and incorporates traditional Diné (Navajo) foods and recipes. The MUTTON-HF trial is a 2-center, pragmatic, open-label randomized controlled trial to determine the efficacy and safety of MUTTON-HF among Diné patients with heart failure and hospitalization, or emergency room visit in the last 12 months. Two hundred and four subjects at 2 Indian Health Service sites will be randomized in a 1:1 stratified fashion by sex, age (<65 versus ≥65 years), and left ventricular ejection fraction (<50% versus ≥50%). Study subjects will receive either culturally and medically tailored meals that incorporate traditional Diné recipes and foods or usual dietary advice for 8 weeks. Data analysts will be blinded to group assignment until study completion. The primary efficacy end point is the proportion of patients with a hospitalization or emergency room visit (all-cause) within 90 days. Secondary outcomes will include hospitalizations or emergency room visits for heart failure specifically; Kansas City Cardiomyopathy Questionnaire scores for health-related quality of life; measures of food insecurity; Indigenous nourishment; diet quality; financial strain; and clinical biomarkers from study enrollment to 8 weeks. Community-based interventions that leverage the protective assets of Indigenous communities are needed to improve cardiovascular health among Native populations. This pragmatic randomized controlled trial will target a rural tribal population and be the first to evaluate the efficacy of an Indigenous food is medicine intervention to improve Indigenous cardiovascular health outcomes for patients with heart failure. URL: https://www.clinicaltrials.gov; Unique identifier: NCT06549699.

Severe hypoglycemic events (SHEs) impose substantial clinical and economic burden on people with type 1 diabetes (pwT1D), yet real-world data describing this burden remain limited in the U.S. hospital setting. This study examined T1D-related complications and direct medical costs in pwT1D hospitalized or treated in the emergency department (ED) for hypoglycemia. IQVIA's PharMetrics Plus database was used to identify adults with T1D who experienced at least 1 hypoglycemic event requiring an inpatient hospitalization or ED visit from April 2016-April 2020. The SHE date was defined as the date of the first hospital-treated SHE: a claim with a hypoglycemia diagnosis and an inpatient hospitalization or ED visit. Patients were followed up until the end of continuous enrollment or end of the study period (April 30, 2022). Prevalence of T1D-related complications were descriptively summarized, and all-cause direct medical costs were calculated as per-patient-per-year (PPPY). The study was conducted during a period of early adoption of advanced diabetes technologies, such as hybrid closed-loop systems, and only included direct medical costs, potentially underestimating total costs. Among 4627 adults with T1D and hospital-treated SHEs, mean age was 41.4years, 57.3% were male, and 93.4% had commercial insurance. Common comorbidities included hypertension (24.6%), anxiety (9.5%), and depression (9.3%). Prevalence of retinopathy, neuropathy, chronic kidney disease (any stage), coronary artery disease, and peripheral vascular disease were 38.6%, 38.6%, 17.7%, 13.2%, and 11.4%, respectively. Total all-cause direct medical costs averaged $52,849 PPPY in 2022 USD ($59,719 in 2025 USD), driven primarily by inpatient hospitalization (mean-$22,981 in 2022 USD, $25,968 in 2025 USD). Among patients with a hospitalization, mean (SD) number of hospitalizations (PPPY) were 1.5 (3.6) and the average length of stay per patient (PPPY) was 5.0 (20.7) days. High T1D-related complication rates and elevated direct medical costs highlight the complexity of pwT1D who experienced hospital-treated SHEs.

High-deductible health plan (HDHP) members face relatively high out-of-pocket (OOP) costs for urgent care, high-acuity care, and secondary prevention. These costs could affect the timing of cardiometabolic disease diagnosis. To determine whether HDHPs are associated with delays in diabetes diagnosis and increases in health care costs in the period surrounding new diagnoses. Segmented survival with control group and pre-post with control group. Members aged 18 to 64years without diabetes at the beginning of the pre-index period. Characteristics of interest for stratified analyses comprised sex, income, and race/ethnicity. Employer-mandated transition from low-deductible health plan to HDHP. Time to first diabetes diagnosis; and total and OOP medical costs in the peri-diagnosis period (from 30days before to 90days after first diabetes diagnosis). In this sample of 346,492 HDHP members and 346,492 matched and weighted controls, the mean (SD) age was 42.3 (13.0) years, and 48.5% were women. The overall and female HDHP groups experienced delays in diabetes diagnosis in the post- versus pre-index period (adjusted hazard ratio, aHR: 0.93 [95% CI 0.88, 0.99] and 0.91 [0.83, 0.99], respectively), compared with controls. These hazard ratios corresponded to delays of 1.7 and 2.1months compared with median diagnosed control patients. Other HDHP subgroups did not have statistically significant delays. HDHP group members newly diagnosed with diabetes had relative post- versus pre-index increases in total and OOP peri-diagnosis medical costs of 20% (95%CI1%, 39%) and 51% (95%CI33%, 60%), respectively, versus controls. HDHP enrollment was associated with delayed diabetes diagnosis and substantially increased peri-diagnosis total and OOP medical costs. Female HDHP members might be especially at risk. Policymakers should consider reducing OOP costs for key health care services associated with diagnosing diabetes.

Pineoblastoma is a clinically aggressive childhood brain tumor composed of distinct molecular subgroups with divergent driver genes, demographics, and clinical outcomes. To identify developmental origins and mechanisms governing disease pathogenesis, we derive single-cell transcriptomes from pineal parenchymal tumors, aligning malignant cells with developmental counterparts to retrace cellular origins. Integrative computational analyses map pineoblastoma origins to transient, cycling pinealocyte progenitors during development. Lineage-specific perturbation of suspected drivers in the early pineal gland yields preclinical models representative of consensus molecular subgroups. Multi-omic characterization of patient tumors and these models uncover a tumor-associated photoreceptor signature (TAPS) common to pineoblastoma, retinoblastoma, and Group 3 medulloblastoma. Transcriptional activity of this signature within respective cellular origins establishes a developmental basis for molecular similarities between entities. Photoreceptor signature constituents are selective dependencies across these anatomically distinct central nervous system malignancies, motivating future studies evaluating developmentally encoded programs of malignancy as potential therapeutic liabilities.