Publications by Year: 2026

BACKGROUND & AIMS: Patients with metabolic dysfunction-associated steatotic liver disease (MASLD) and high cardiovascular risk often have advanced liver fibrosis, but data on associations and outcomes are limited. The aim of this study was to evaluate the relationships between cardiovascular risk categories and liver fibrosis severity, liver fibrosis progression, and liver-related events (LREs) in MASLD.

METHODS: Patients with MASLD from the VCTE-Prognosis cohort were stratified into low, intermediate, and high cardiovascular risk categories using the Framingham Risk Score (FRS), Primary Care Equivalents (PCE), or Predicting Risk of Cardiovascular Disease EVENTs (PREVENT) scores. Outcomes included the prevalence of advanced fibrosis (liver stiffness ≥10 kPa), liver stiffness progression (≥20% increase and Baveno category upshift), and LRE (hepatocellular carcinoma, hepatic decompensation, liver transplantation, or liver-related mortality). Associations were assessed using multivariable logistic regression and Fine-Gray competing-risks models.

RESULTS: Among 9312 patients with MASLD (mean age, 54.4 ± 11.0 years; 56.8% male; 87.4% Asian), advanced fibrosis prevalence increased with cardiovascular risk: adjusted odds ratios (ORs) were 2.72 (95% confidence interval [CI], 2.25-3.28; P < .001) for FRS, 1.83 (95% CI, 1.46-2.29; P < .001) for PCE, and 2.93 (95% CI, 2.33-3.69; P < .001) for PREVENT. Over a median follow-up of 4.5 years, liver stiffness progression occurred in 5.0% of patients, more frequently in high-risk groups (adjusted subdistribution hazard ratio [SHR], 1.56; 95% CI, 1.14-2.15; P = .006 for PCE and adjusted SHR, 1.85; 95% CI, 1.33-2.56; P < .001 for PREVENT). LREs occurred in 1.4% of patients, with higher incidence in high-risk groups (adjusted SHR, 2.12; 95% CI, 1.19-3.77; P = .010 for FRS; adjusted SHR, 2.01; 95% CI, 1.08-3.74; P = .027 for PCE; and adjusted SHR, 2.80; 95% CI, 1.40-5.61; P = .004 for PREVENT).

CONCLUSIONS: Higher cardiovascular risk is associated with greater prevalence of advanced liver fibrosis, liver stiffness progression, and LRE incidence in MASLD.

IMPORTANCE: With the availability of multiple classes of advanced therapies for the treatment of Crohn disease (CD), understanding the comparative safety of different therapies can inform treatment positioning.

OBJECTIVE: To compare the risk of serious infections, venous thromboembolism (VTE), and major adverse cardiovascular events (MACE) with different advanced therapies in patients with CD.

DESIGN, SETTING, AND PARTICIPANTS: This retrospective comparative effectiveness research study was conducted between January 1, 2016, and December 31, 2022, with a mean (SD) follow-up of 26.9 (2.4) months until July 1, 2024. Using an administrative claims database (OptumLabs Data Warehouse), commercially insured patients with CD, who initiated treatment with tumor necrosis factor-α (TNF) antagonists, anti-integrin agents (vedolizumab), interleukin (IL)-12/23p40 antagonists (ustekinumab), IL-23p19 antagonists (primarily risankizumab), or Janus kinase inhibitors (upadacitinib) between 2016 and 2022 and had follow-up for at least 1 year before and after treatment initiation, were included.

EXPOSURE: TNF antagonists vs anti-integrin agents (vedolizumab) vs IL-12/23p40 antagonists (ustekinumab) vs IL-23p19 antagonists (risankizumab) vs Janus kinase inhibitors (upadacitinib).

MAIN OUTCOMES AND MEASURES: The risk of serious infections, VTE, and MACE was compared with various advanced therapies through multinomial propensity score-based inverse probability treatment weighting, with propensity scores estimated through generalized boosted models, accounting for disease characteristics, health care utilization, comorbidities, and prior and concomitant medications, and through competing risk of mortality. Cause-specific hazard ratios (HRs) and 95% CIs for multiple treatment comparisons were calculated.

RESULTS: This study included 12 245 patients with CD (mean [SD] age, 46.5 [17.5] years; 6642 females [54.2%]), who were treated with TNF antagonists (n = 5274), vedolizumab (n = 2716), ustekinumab (n = 3544), risankizumab (n = 559), or upadacitinib (n = 152). Serious infection incidence rates ranged from 5.46 (95% CI, 4.86-6.07) to 9.02 (95% CI, 6.38-11.89) per 100 person-years across therapies. After adjusting for confounding variables, there were no statistically significant differences in the risk of serious infections across different agents, including between risankizumab and ustekinumab (HR, 1.14 [95% CI, 0.78-1.67]), risankizumab and TNF antagonists (HR, 1.00 [95% CI, 0.68-1.47]), or ustekinumab and TNF antagonists (HR, 0.88 [95% CI, 0.74-1.04]). The incidence of VTE (incidence rate, 0.90 [95% CI, 0.71-1.10] to 2.33 [95% CI, 1.06-3.82] per 100 person-years) and MACE (0.68 [95% CI, 0.51-0.85] to 1.49 [95% CI, 0.43-2.76] per 100 person-years) was low, without any significant differences across agents.

CONCLUSIONS AND RELEVANCE: In this comparative effectiveness research study of patients with CD, no significant differences in the risks of serious infections, VTE, or MACE across various advanced therapies were found. These findings support clinical decision-making on choice of advanced therapies for most individual patients with CD to be driven primarily by comparative treatment effectiveness rather than driven by concerns of serious adverse events.

IMPORTANCE: The ongoing consequences of settler colonialism produce adverse structural drivers, particularly nutrition insecurity, that contribute to cardiovascular health disparities among Indigenous populations. There is increased focus in Native communities to reclaim traditional precontact foods to improve health. Therefore, a locally sourced, Indigenous, medically tailored meal delivery program-MUTTON-HF (Medically Utilized Tailored Traditional Foods to Optimize Nutrition in Heart Failure)-was developed to improve health outcomes.

OBJECTIVE: To determine implementation outcomes, including feasibility and acceptability, as well as to explore preintervention vs postintervention health measures of a medically tailored meal program incorporating traditional foods and recipes for patients with heart failure in rural Navajo Nation.

DESIGN, SETTING, AND PARTICIPANTS: The single-arm pilot nonrandomized clinical trial was conducted from October 7, 2024, to February 3, 2025, to evaluate implementation and health outcomes of the MUTTON-HF program. Participants included adults (≥18 years) with a diagnosis of heart failure who were receiving care at one of 2 Indian Health Service sites in rural Navajo Nation.

INTERVENTION: Patients received 14 culturally and medically tailored meals weekly (2 meals daily) for 4 weeks.

MAIN OUTCOMES AND MEASURES: The primary outcomes were intervention feasibility and acceptability, assessed with surveys, qualitative interviews, and programmatic data at 30 days. Intervention feasibility was determined by evaluating the number and percentage of meal boxes successfully received by each patient. Acceptability was assessed using the Acceptability of Intervention Measure (AIM) (score range, 4-20), patient program ratings (range, 1-10), and the Net Promoter Score. Secondary outcomes, which were assessed via surveys and medical record review, included intervention adoption and fidelity, feasibility for community partners (including farmers and ranchers, using the Feasibility of Intervention Measure [score range, 4-20]), and preintervention vs postintervention health measures (eg, clinical biomarkers, food insecurity [based on the US Department of Agriculture 6-item Short-Form Food Security Survey Module], 12-item Kansas City Cardiomyopathy Questionnaire [KCCQ] scores, and Cultural Connectedness Scale [CCS] scores).

RESULTS: This study enrolled 20 American Indian patients (mean [SD] age, 58.2 [11.7] years; 13 were male [65.0%]) residing in communities exceeding a 136-km radius in Arizona and New Mexico. Patients had a mean (SD) left ventricular ejection fraction of 40.0% (16.0%). Of the 80 weekly meal boxes, 72 (90.0%) were successfully received by patients. The mean (SD) AIM score was 16.9 (3.1), the mean (SD) patient program rating was 8.6 (1.6), and the Net Promoter Score was 45.0%. Most patients (17 [85.0%]) reported they were likely to change their diet to be healthier moving forward. Mean (SD) Feasibility of Intervention Measure scores were 19.8 (0.5) for community farmers and ranchers and 20 (0) for community partners. Significant preintervention to postintervention improvements were observed for food security (the number of patients who were food secure increased from 8 [40.0%] to 17 [85.0%]), KCCQ physical limitation (mean [SD], from 59.6 [31.3] to 82.7 [21.9]) and social limitation (mean [SD], from 74.6 [24.1] to 83.8 [25.0]) scores, CCS Traditions subscore (mean [SD], from 7.2 [2.9] to 7.9 [3.0]), and weight change among patients with obesity (mean [SD], -2.3 [3.3] kg).

CONCLUSIONS AND RELEVANCE: In this nonrandomized clinical trial, the MUTTON-HF intervention incorporating Indigenous recipes and locally sourced Native food was feasible and acceptable for patients with heart failure in rural Navajo Nation. These findings will inform a future randomized clinical trial to evaluate the effectiveness of this intervention to advance Indigenous cardiovascular health and food sovereignty.

TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT06675331.

IMPORTANCE: Physician emigration from low- and middle-income countries to high-income countries is a major driver of inequitable distribution of health care and health outcomes across the world. World Health Organization (WHO) signatory countries unanimously signed the voluntary Global Code of Practice on the International Recruitment of Health Personnel (WHO Code) in 2010. The goal was to reduce health care workforce emigration by discouraging active recruitment of physicians from WHO-designated shortage countries and by promoting investment in the physician workforce in those countries. This study adds to the literature by providing evidence about whether the goal has been achieved 10 years after worldwide implementation of the WHO Code.

OBJECTIVE: To evaluate whether the WHO Code was associated with changes in physician emigration and physician density in WHO-designated shortage countries after 2010.

DESIGN, SETTING, AND PARTICIPANTS: A difference-in-differences design was used to examine trends in physician supply before and after 2010. The data (from 2000 through 2021) were collected by the Organization for Economic Co-operation and Development (OECD) and were used to examine physician outflow from 56 WHO-designated shortage countries vs 116 nonshortage countries. The data analysis took place October 2024 to September 2025.

EXPOSURES: Worldwide adoption of the 2010 WHO Code.

MAIN OUTCOMES AND MEASURES: The primary outcome was annual physician migration to OECD countries and the secondary outcome was physician density by country and year (per 1000 population using World Bank data) in the origin countries.

RESULTS: A total of 135 888 physicians emigrated from WHO-designated shortage countries during 2000 to 2021 and 516 030 physicians emigrated from nonshortage countries. Compared with nonshortage countries, there was a decrease in physician outflow by 47.03 physicians (95% CI, -92.29 to -1.76 physicians) per country per year after 2010 in WHO-designated shortage countries and the WHO Code was associated with a reduction of nearly 30% in the average annual outflow of physicians from these countries. However, there was a slight decrease in physician density in the WHO-designated shortage countries after 2010 (-0.22 [95% CI, -0.33 to -0.11] physicians per 1000 population) compared with the nonshortage countries.

CONCLUSIONS AND RELEVANCE: This study found that voluntary implementation of the WHO Code was associated with lower physician outflow from WHO-designated shortage countries without improvement in physician density in those countries.

Esophageal adenocarcinoma is a major global health concern, primarily arising from gastroesophageal reflux disease, with Barrett's esophagus being its main precursor. Although proton pump inhibitors are commonly used to manage the symptoms from gastroesophageal reflux disease, their role in preventing esophageal adenocarcinoma progression remains uncertain. The aim of this review is to summarize the current advances in the diagnosis of Barrett's esophagus and its progression, as well as to critically evaluate and compare the impact of antireflux surgery on Barrett's esophagus and its potential role in preventing its progression to esophageal adenocarcinoma. In conclusion, surgical intervention, particularly antireflux surgery, has been associated with reduced esophageal adenocarcinoma risk in some studies, offering better long-term symptom control and possibly preventing cancer progression. However, other authors suggest that the cancer risk does not decrease significantly with surgery, highlighting the need for further investigation into its long-term preventive benefits. Several novel strategies have been established over the last few years that will facilitate an early diagnosis of Barrett's esophagus in the future.

Brainstem white matter (WM) bundles are essential conduits for neural signals that modulate homeostasis and consciousness. Their architecture forms the anatomic basis for brainstem connectomics, subcortical circuit models, and deep brain navigation tools. However, their small size and complex morphology, compared to cerebral WM, makes mapping and segmentation challenging in neuroimaging. As a result, fundamental questions about brainstem modulation of human homeostasis and consciousness remain unanswered. We leverage diffusion MRI tractography to create BrainStem Bundle Tool (BSBT), which automatically segments eight WM bundles in the rostral brainstem. BSBT performs segmentation on a custom probabilistic fiber map using a convolutional neural network architecture tailored to detect small anatomic structures. We demonstrate BSBT's robustness across diffusion MRI acquisition protocols with in vivo scans of healthy subjects and ex vivo scans of human brain specimens with corresponding histology. BSBT also detected distinct brainstem bundle alterations in patients with Alzheimer's disease, Parkinson's disease, multiple sclerosis, and traumatic brain injury through tract-based analysis and classification tasks. Finally, we provide proof-of-principle evidence for the prognostic utility of BSBT in a longitudinal analysis of traumatic coma recovery. BSBT creates opportunities for scalable mapping of brainstem WM bundles and investigation of their role in a broad spectrum of neurological disorders.

Continual learning (CL) enables animals to learn new tasks without erasing prior knowledge. CL in artificial neural networks (NNs) is challenging due to catastrophic forgetting, where new learning degrades performance on older tasks. While various techniques exist to mitigate forgetting, theoretical insights into when and why CL fails in NNs are lacking. Here, we present a statistical-mechanics theory of CL in deep, wide NNs, which characterizes the network's input-output mapping as it learns a sequence of tasks. It gives rise to order parameters (OPs) that capture how task relations and network architecture influence forgetting and anterograde interference, as verified by numerical evaluations. For networks with a shared readout for all tasks (single-head CL), the relevant-feature and rule similarity between tasks, respectively measured by two OPs, are sufficient to predict a wide range of CL behaviors on classic benchmark tasks. In addition, the theory predicts that increasing the network depth can effectively reduce interference between tasks, thereby lowering forgetting. For networks with task-specific readouts (multihead CL), the theory identifies a phase transition where CL performance shifts dramatically as tasks become less similar, as measured by another task-similarity OP. While forgetting is relatively mild compared to single-head CL across all tasks, sufficiently low similarity leads to catastrophic anterograde interference, where the network retains old tasks and interpolates new training data perfectly but completely fails to generalize new learning. Our results delineate important factors affecting CL performance and offer theoretical insights into common heuristics for mitigation of forgetting.

Aldehydes accumulating in response to reduced fatty acid oxidation in tumor-infiltrating lymphocytes damage mitochondria and drive T cell exhaustion.

BACKGROUND: Sleep disturbance, which is a common symptom in Long COVID, promotes a pro-inflammatory state and dysregulates lipid-derived specialized pro-resolving mediators (SPMs), presumably contributing to chronic unresolved inflammation. This study aimed to investigate the role of sleep disturbance in inflammatory resolution in Long COVID.

METHODS: We studied 39 participants (30F/9M, age range 22-68 years), including 31 individuals with Long COVID and 8 SARS-CoV-2-infected controls, who did not develop Long COVID. The study consisted of a 14-day at-home phase followed by a 1-day (24-h) in-laboratory stay. Sleep disturbance was assessed using PROMIS Sleep Disturbance T-scores. During the in-laboratory stay, a fasting morning blood sample was taken for assessment of lipid mediators. Data were analyzed using generalized linear mixed models.

RESULTS: Participants with Long COVID reported higher sleep disturbance than controls (p<.001). Pro-inflammatory lipid pathways were upregulated in Long COVID compared to control, as indicated by higher prostaglandin E2 (PGE2) levels (p<.05). Long COVID participants with high sleep disturbance (PROMIS Sleep Disturbance T-score ≥60) had lower SPM levels, including the precursor of D-series resolvins 17-hydroxydocosahexaenoic acid (17-HDHA), 17R/S-resolvin D1 (17R/S-RvD1), 15R-lipoxin B4 (15R-LXB4), and protectin D1n-3 DPA (PD1n-3 DPA) than those with low sleep disturbance (T-score <60) (p<.05).

CONCLUSIONS: This study suggests that sleep disturbance may contribute to chronic inflammation in Long COVID by compromising certain inflammatory resolution pathways. Promoting inflammatory resolution physiology in particular in those individuals with Long COVID suffering from sleep disturbance may serve as a mechanistic target to mitigate inflammation and symptom burden in Long COVID.

TRIAL REGISTRATION: ClinicalTrials.gov NCT05606211.

Diffusion MRI (dMRI) tractography is an advanced technique that uniquely enables in vivo mapping of brain fiber pathways. Traditional methods rely on tissue modeling to estimate fiber orientations for streamline propagation, which are computationally intensive and remain sensitive to noise and artifacts. Recent deep learning-based approaches enable data-driven fiber tracking by directly mapping dMRI signals to orientations, demonstrating both improved efficiency and accuracy. However, existing methods typically operate by either leveraging local signal information or learning global dependencies along streamlines. This paper presents DDTracking, a deep generative framework for tractography. One key innovation is the reformulation of streamline propagation as a conditional denoising diffusion process. To the best of our knowledge, this is the first work to apply diffusion models for fiber tracking. Our network architecture incorporates two new designs, including: (1) a dual-pathway encoding scheme that extracts complementary local spatial features and global temporal context, and (2) a conditional diffusion model module that integrates the spatiotemporal features to predict propagation orientations. All components are trained jointly in an end-to-end manner without any pretraining. In this way, DDTracking can capture fine-scale structural details at each point while ensuring long-range consistency across the entire streamline. We conduct a comprehensive evaluation across diverse datasets, including both synthetic and clinical data. Experiments demonstrate that DDTracking outperforms traditional model-based and state-of-the-art deep learning-based methods in terms of tracking accuracy and computational efficiency. Furthermore, our results highlight DDTracking's high generalizability across heterogeneous datasets, spanning varying health conditions, age groups, imaging protocols, and scanner types. Code is available at: https://github.com/yishengpoxiao/DDTracking.git.