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Abstract WE578: Early Bystander Resuscitation in the Workplace: Insights and Implications
Introduction: Out-of-hospital cardiac arrest (OCHA) remains a major burden, with an estimated incidence rate of around 50/100,000 person-year in Europe. Survival is still low and early bystander cardiopulmonary resuscitation (CPR) and defibrillation remain key determinants. Workplaces have historically implemented CPR and automated external defibrillators (AED) training programs earlier than in the general population. This study aimed to compare bystander resuscitation and survival across locations, focusing on workplace environments. Methods: Data was extracted from the Paris sudden death expertise center registry, including all OHCA within Paris and its suburbs. Descriptive summary of characteristics, multi-adjusted models as well as time trends for bystander CPR initiation, AED use and survival by location were computed over a 10-year period. Results: OHCA incidence remained stable over the study period, with 4000 cases per year overall and 80 cases per year in workplaces. Workplace patients were younger (52.5 ± 12.5 years vs 59.3 ± 18.7 years) and had fewer cardiovascular comorbidities than in other public locations. In workplaces, bystanders were more likely to perform CPR (OR=1.38, p=0.005) and use AED (OR=2.24, p<0.001) independently of adjustment covariates. Compared to other locations, bystander CPR initiation rate remained stable and higher in workplaces (77% to 86%). AED use increased across all locations but remained higher at work (increasing from 16% to 32%). Survival was stable over 10 years and consistently twice as high in workplaces compared to other public locations (respectively 20%-27% vs 13%-16%). Conclusion: Workplace cardiac arrests were characterized by a stable incidence over time, with early CPR and AED use significantly more frequent, leading to consistently higher survival rates. These findings identify workplace environments as a benchmark for community response, emphasizing the need for public health policies aiming to achieve similar outcomes across all public settings.
Senolytic treatment induces oligodendrocyte dysfunction and demyelination in the corpus callosum
Aging is a primary risk factor for disease progression in multiple sclerosis (MS). Because of this, treatments that can reduce the consequences of molecular aging, like senescence, have been proposed as a strategy to address disease progression. However, the effects of senolytics, a class of drugs which selectively ablate senescent cells, on the central nervous system are largely unknown. Here, we examined the effects of senolytic treatment on myelination and oligodendrocyte function in vivo using C57BL6/J mice and in vitro using primary rat oligodendrocyte cultures. Initial data showed that naïve young (3 to 4 mo) and aged (22 mo) C57BL6/J mice treated with dasatinib and quercetin (D+Q) developed significant demyelination compared to vehicle-treated controls, though no cell death was observed in the brain. In vitro, oligodendrocyte progenitor cells treated with D+Q in differentiation media exhibited significantly reduced myelin basic protein protein and morphological complexity, also without inducing cell death. Bulk RNA sequencing and ingenuity pathway analysis of D+Q treated oligodendrocytes identified differentially expressed genes associated with endoplasmic reticulum stress. These data suggest that D+Q evokes the unfolded protein response in oligodendrocytes, causing oligodendrocyte dysfunction and myelination failure. Due to the resemblance between oligodendrocytes treated with D+Q and those found in MS lesions, D+Q treatment offers a potential method to model an aspect of oligodendrocyte dysfunction relevant to MS. Therefore, understanding the mechanism by which D+Q perturb oligodendrocyte function may provide insight into some of the pathological features contributing to disease progression in MS.
Unveiling the deformation and crack mechanism of glass nanostructure embossing: A molecular dynamics study at experimental scale
Glass nanostructure embossing is a critical manufacturing process for producing high-precision glass components used in optics and electronics. However, controlling the deformation and fracture mechanisms of glass during embossing remains a significant challenge due to its complex behavior, which can vary between solid and liquid-like states under different conditions. To investigate these mechanisms, this study employs large-scale molecular dynamics (MD) simulations that mirror experimental conditions. The simulations reveal how compressive forces near the mold interface lead to densification and lateral flow of the glass, while tensile stresses at the edges can promote crack formation. Additionally, the study examines the role of strain rate in crack propagation, showing that higher strain rates accelerate failure. These findings offer a deeper understanding of the atomic-level behavior of glass during embossing, highlighting key factors such as stress distribution, energy evolution, and material flow. By bridging the gap between molecular simulations and experimental observations, this work provides valuable insights into optimizing embossing conditions. The results can be applied to improve the quality of glass nanostructures, reducing defects and ensuring the mechanical robustness of glass-based devices.
Abstract TU266: Impact of Sleep Health on Mortality with Blood Pressure Variability and Race as Modifiers
Introduction: Multidimensional sleep health (MDSH) is an important but understudied determinant of mortality. We evaluated whether blood pressure variability (BPV) and race/ethnicity modify the association between MDSH and all-cause and cardiovascular mortality. Hypothesis: Poorer MDSH is associated with higher mortality, with stronger associations among individuals with high BPV and across race/ethnic groups. Methods: We analyzed NHANES 2005–2008 and 2015–2018 linked to mortality through 2020 in adults ≥20 y (n=10,279). MDSH (score 0-4) incorporated sleep duration, latency, disorder, and sleepiness. BPV was the SD of three BP readings, categorized into tertiles. Adjusted cox proportional hazard model assessed for associations of MDSH score with cardiovascular and all-cause mortality. Additional analyses further evaluated for effect modification by BPV tertiles or ethnicity. Results: Poorer MDSH was associated with higher all-cause mortality (HR 2.47, 95% CI 1.37–4.45, p=0.031 for 0–1 vs 4; HR 1.17 per unit decrease, 95% CI 1.07–1.29, p=0.001). Sleepiness showed the strongest association with cardiovascular mortality (HR 1.71, 95% CI 1.12–2.61, p=0.014). BPV modified associations, with poor MDSH linked to increased all-cause mortality in the high BPV group (HR 3.02, 95% CI 1.07–8.53, p=0.038). Race/ethnicity modified associations: Non-Hispanic Black adults had elevated cardiovascular risk with moderate MDSH (HR 2.17, 95% CI 1.06–4.46, p=0.035), while Hispanic adults had lower risk with poor MDSH (HR 0.25, 95% CI 0.08–0.75, p=0.015). Conclusions: Poorer MDSH, especially sleepiness, is associated with higher all-cause mortality. BPV amplifies risk among those with high variability, and race/ethnicity modifies these associations. Improving sleep health may help reduce mortality, particularly in racially diverse populations with unstable BP.
Abstract TH948: Neighborhood problems, Identity Vitality Pathology, and Hypertension: A Race-Stratified Analysis
Introduction: Perceived neighborhood problems (PNP), including concerns about dilapidation and safety, have been linked to elevated hypertension risk through chronic stress pathways. The Identity Vitality-Pathology framework proposes a novel modifiable identity-based resilience construct. Identity vitality, capturing inclusive self-concept, status-independent self-worth, and compassionate orientation, is theorized to buffer the health impact of social stressors by influencing stress appraisal. We hypothesized that identity vitality would mitigate the impact of PNP on hypertension. Methods: Using 2025 data from 2,008 Black and White women and men in the HARI study, we employed logistic regressions to estimate the cross-sectional association between PNP and self-reported hypertension. Models, controlling for age, education, perceived social support, and financial strain, were stratified by the four race-gender groups. Interaction terms between PNP and identity vitality (both measured using validated scales) assessed whether the PNP-hypertension association varied by levels of identity vitality. Results: Among Black women, the mean age=48.1 ± 5.5 and 32.4% were hypertensive; Black men, mean age=46.4 ± 8.3, 23.7% hypertensive; white women, mean age=50.7 ± 9.5, 28.4% hypertensive; and white men, mean age=47.2 ± 8.4, 29.8% hypertensive. Among those with the highest compared to lowest PNP, a 1-SD increase in identity vitality was associated with lower odds of hypertension in all groups except white men, although estimates were largest and most precise among Black women (adjusted odds ratio = 0.46, 95% CI= 0.23, 0.96). Conclusion: We found that a novel construct of identity-based resilience, identity vitality, moderates the impact of PNP on hypertension, particularly among Black women. This evidence suggests opportunities for novel culturally tailored interventions to mitigate the increased risk of hypertension among subjugated populations living in disadvantaged neighborhoods.
Abstract MPTU05: Explainable Stroke Risk Prediction Using Machine Learning and Large Language Models: Toward a Mobile-Enabled Clinical Decision Support Application
Background: Stroke is the second leading cause of death worldwide, accounting for approximately eleven percent of all deaths. Effective prevention depends on early identification of at-risk individuals and clear communication of modifiable risk factors. Traditional risk calculators often lack transparency and adaptability for diverse clinical settings. Advances in artificial intelligence now allow integration of machine learning and natural language generation to enhance both prediction accuracy and patient communication. Therefore, we investigated the use of machine learning and LLM-based natural language generation to evaluate stroke risk prediction performance and the effectiveness of model-driven patient communication. Methods: A dataset of 5,110 patient records containing demographic, behavioral, and clinical variables such as age, hypertension, heart disease, body mass index, glucose level, and smoking status was analyzed. Multiple machine learning algorithms (logistic regression, decision tree, random forest, gradient-boosted trees) were trained and compared for stroke prediction. Model interpretability was assessed using SHAP-based feature attribution to identify key predictors. Large language models (e.g., GPT, Claude, Gemini) were used to generate patient-friendly explanations, providing reasoning and context alongside predictions. Semantic consistency and differences across LLM explanations were compared. A mobile-responsive prototype tool was developed, allowing participants to enter individual variable values and receive risk prediction and interpretive feedback via QR code. Results: Random Forest achieved the highest performance with 97% accuracy, 97% precision, 97% recall, and 97% F1-score, followed by Decision Tree (94% accuracy, 94% precision, 94% recall, 94% F1-score), Voting Classifier (91% accuracy, 91% precision, 91% recall, 91% F1-score), and Logistic Regression (87% accuracy). Feature attribution highlighted the most influential clinical and behavioral predictors. LLMs successfully generated individualized, understandable explanations of predicted risk, enabling patients to grasp modifiable factors. Comparative analysis of LLM outputs revealed subtle differences in reasoning and communication style. Conclusions: This work presents an explainable and accessible stroke prediction framework combining machine learning and LLMs. This approach enhances patient engagement, promotes early intervention, and supports equitable stroke prevention.
Origin of eukaryotic plasmalogen biosynthesis by horizontal gene transfer from myxobacteria
Plasmalogens are a unique class of glycerophospholipids defined by a distinctive vinyl ether bond. While these lipids are abundant in animals and important for human health, their evolutionary history remains enigmatic, mostly due to their absence in some major eukaryotic lineages like plants. Here, we resolve the origin and evolution of the aerobic plasmalogen biosynthesis pathway in eukaryotes. Through comprehensive phylogenomic analysis and experimental validation of enzyme activity and plasmalogen presence, we demonstrate that the essential desaturase plasmanylethanolamine desaturase 1 (PEDS1)—and likely the fatty acyl-CoA reductase (FAR) and glycerone phosphate O -acyltransferase (GNPAT) enzymes also critical in the pathway—were acquired by an early eukaryotic ancestor through horizontal gene transfer (HGT) from myxobacteria. Our data show that this bacterial pathway was retained in the Amorphea and Discoba supergroups but lost or replaced in others. The findings yield insights into how HGT shaped metabolic pathways in early eukaryotes.
Temporal and geographic analyses of colorectal cancer screening during and after the COVID-19 pandemic in a federally qualified health center
Background The COVID-19 pandemic caused reductions in cancer screening services. We assessed the pandemic’s impact on colorectal cancer screening in a large diverse federally qualified health center (FQHC) in Los Angeles, CA. Methods We used interrupted time series regression to estimate trends in monthly colorectal cancer screening rates for four relevant COVID-19 pandemic periods: pre-pandemic (March 2018 – February 2020); early-pandemic (March – December 2020); vaccine-era (January 2021– May 2023); and post-pandemic (June 2023 – May 2024). We plotted spatial distribution patterns of screening across census tracts. Results Participants were 83,430 unique individuals (55% male; 80% Hispanic) ages 50–75. Average monthly colorectal cancer screening rates dropped from 9.3% pre-pandemic to 5.9% early-pandemic. Monthly screening rates in the vaccine era (7.5%) never returned to pre-pandemic levels and further declined in the post-pandemic era (6.7%; p trend = 0.09). Screening rates were consistently higher for males, ages 65–75, Hispanic individuals, and Spanish-preferring individuals in both pre-COVID (March 2018-Feb 2020) and post-COVID (July 2020-May 2024) periods. Increases in stool-based testing aligned with mailed outreach campaigns. Conclusions Monthly post-pandemic screening rates never reached pre-pandemic levels and declined from 2023 to 2024. Sharp increases in stool-based testing coincided with mailed outreach events, highlighting the importance of home-based screening methods during disruptive events. Impact Our findings can help shape healthcare response strategies to reduce screening delays in the context of future natural disasters.
Abstract TH804: Understanding Cardiovascular Health Relevance Among Black Breast Cancer Survivors: Insights from the Exploring Cardiovascular Health Outcomes (ECHO) Project
Background: Black breast cancer survivors experience disproportionate cardiovascular disease (CVD)-related mortality compared to White survivors. Healthy lifestyle behaviors (e.g., physical activity, balanced diet) are central to survivorship care and can reduce both cancer recurrence and CVD risk. The American Heart Association’s Life’s Essential 8 (LE8) provides a comprehensive measure of cardiovascular health (CVH); however, its use as a behavioral and educational tool in cancer survivorship is largely unexplored, particularly among Black survivors. The Exploring Cardiovascular Health Outcomes (ECHO) study examined how survivors perceived CVH and CVD risk across survivorship and engaged in recommended health behaviors. Methods: A descriptive, qualitative design was employed. Self-identified Black breast cancer survivors participated in semi-structured focus groups exploring knowledge, beliefs, and behaviors related to CVH and CVD risk. Biometric and self-reported data were collected for LE8 components (blood pressure, glucose, cholesterol, weight, physical activity, diet, smoking, sleep) and sociodemographic characteristics. Focus groups were audio-recorded, transcribed verbatim, and analyzed using thematic analysis with consensus among three coders. Themes were validated by a community advisory board of Black survivors. Descriptive statistics summarized quantitative data. Preliminary Findings: Seventeen survivors participated in three focus groups. Participants were predominantly middle-aged (mean age = 59.7), educated (65% some college or more), employed (53%), and had moderate CVH. Four themes emerged: (1) informational disconnect between cancer and CVD risk; (2) waning motivation for lifestyle modification through long-term survivorship despite awareness of benefit; (3) complex life circumstances as barriers to sustained health behavior change; and (4) readiness for empowerment and co-creation of focused interventions to support optimal survivorship. Conclusions: Findings reveal that while survivors value prevention, CVD risk education is rarely included in survivorship care. Knowledge of CVD risk becomes relevant only when survivors receive clear information, measurable goals, and structured support to sustain behaviors. LE8 may serve not only as a metric describing CVH but also as a behavioral scaffold for empowering Black breast cancer survivors to live heart-healthy long after treatment.
Abstract WE494: Sex-Based Disparities in Access and Psychosocial Health Among Adults with Premature Atherosclerotic Cardiovascular Disease
Introduction: Premature atherosclerotic cardiovascular disease (ASCVD) is a growing public health concern, particularly among women and socioeconomically vulnerable adults. Data on sex differences in healthcare access and psychosocial well-being in this population remain limited. Hypothesis: We hypothesized that women with premature ASCVD experience greater psychosocial burden and barriers to healthcare access compared with men, independent of socioeconomic and clinical characteristics. Methods: We analyzed pooled Behavioral Risk Factor Surveillance System (BRFSS) data from 2020–2023 using survey design–based methods. ASCVD was defined by self-reported myocardial infarction, coronary heart disease, or stroke; premature ASCVD as onset before age 55 years. Psychosocial burden was assessed using three validated BRFSS indicators: diagnosed depression, poor self-rated health, and low emotional support. Access outcomes included lack of insurance and cost-related care barriers. All estimates incorporated sampling weights, strata, and primary sampling units. Sex-based differences were evaluated with design-adjusted chi-square tests, and multivariable survey-weighted logistic regressions estimated adjusted odds ratios (ORs) and 95% confidence intervals (CIs) controlling for age, race/ethnicity, income, education, diabetes, hypertension, and physical activity. Results: Among 1,632,884 respondents (representing ≈245 million U.S. adults), 10.4% reported ASCVD (≈28 million), and 23.7% had premature onset (<55 years; ≈6.7 million). In the overall ASCVD cohort, women had higher odds of depression (OR 1.93, 95% CI 1.83–2.04), fair/poor health (OR 1.29, 1.23–1.36), and cost barriers (OR 1.18, 1.09–1.28) but lower odds of lacking emotional support (OR 0.77, 0.60–0.99). Uninsurance rates were similar (6.2%). In premature ASCVD, disparities were most pronounced: nearly half of women (49.3%) reported depression versus one-third of men (34.3%) (OR 1.87, 1.66–2.10), and women remained more likely to report poor self-rated health (OR 1.25, 1.11–1.41). Conclusions: Nearly one in four adults with ASCVD develop the disease prematurely, representing over 6 million Americans, roughly half of whom are women. Despite similar insurance coverage, women with premature ASCVD experience greater psychosocial burden, driven by higher depression and poorer self-perceived health. Integrating behavioral health screening and reducing cost barriers are essential to achieving cardiovascular health equity.
Abstract TU264: Smartphone-based Digital Phenotyping as a Scalable Approach to Measure Sleep Health in Emerging Adults
Background. Sleep is a key lifestyle factor for cardiometabolic health, but most epidemiologic studies rely on self-reported measures of sleep that are limited by recall bias and low temporal resolution. Smartphone-based digital phenotyping—using passive sensor data to capture real-world behavior—offers a scalable, low-burden alternative for collecting objective, high-frequency sleep data. However, its feasibility, acceptability, and concordance with self-reported sleep data in emerging adults remain underexplored. Methods: We used a customized smartphone app to collect passive sensor data (GPS, accelerometer, screen state) and nightly self-reported sleep data over eight days from 548 participants enrolled in the smartphone substudy of the Economic and Educational Contributors to Emerging Adults’ Oral and Cardiometabolic Health Study (The 3E Study). Sleep measures, including bedtime and wake time, were assessed using both smartphone passive sensor data and self-reported survey data. Data completeness was defined as the proportion of participants with valid sleep estimates over the study period, and concordance was assessed using Spearman rank correlation. On day nine, participants completed a survey assessing comfort, behavioral changes, and perceived burden of smartphone data collection. Results: Across eight days, we collected over 2.7 billion raw sensor data points (~5 million observations per participant), including 22.1 million GPS, 1.4 billion accelerometer, and 2.1 million screen state observations. Preliminary smartphone-derived sleep data were 67% more complete than self-reported data and showed moderate concordance with self-reported sleep (ρ=0.4, p<0.001). The majority of participants identified as Latine (39%) or Asian (35%), and 58% as female. Over 78% of participants reported being comfortable with data collection and found it non-intrusive; 72% reported little to no changes in daily behavior. Conclusions: Smartphone-based digital phenotyping appears to be a feasible and acceptable approach for capturing objective sleep data in emerging adults, with moderate concordance to self-reported measures. By enabling high-resolution, continuous assessment of real-world behaviors, this approach may advance understanding of how sleep and other lifestyle factors contribute to cardiometabolic health.
Three-dimensional high-content imaging of unstained soft tissue with subcellular resolution using a laboratory-based X-ray microscope
With increasing interest in studying biological systems across spatial scales—from centimeters down to nanometers—histology continues to be the gold standard for tissue imaging at cellular resolution, providing an essential bridge between macroscopic and nanoscopic analysis. However, its inherently destructive and two-dimensional nature limits its ability to capture the full three-dimensional complexity of tissue architecture. Here, we show that phase-contrast X-ray microscopy can enable three-dimensional virtual histology with subcellular resolution. This technique provides direct quantification of electron density without restrictive assumptions, allowing for direct characterization of cellular nuclei in a standard laboratory setting. By combining high spatial resolution and soft tissue contrast, with automated segmentation of cell nuclei, we demonstrated virtual Hematoxylin and Eosin (H&E) staining using machine learning-based style transfer, yielding volumetric datasets compatible with existing histopathological analysis tools. Furthermore, by integrating electron density and the sensitivity to nanometric features of the dark field contrast channel, we achieve stain-free, high-content imaging capable of distinguishing nuclei and extracellular matrix.
Design of fault water-resisting coal pillars based on deep-beam analysis: A comparison of two analytical methods
The rational design and mechanical assessment of fault water-resisting coal pillars are essential for effective disaster prevention and mitigation. In the mechanical analysis of water-resisting coal (rock) pillars, deep-beam effects can significantly influence stress distribution, yet the applicability of existing analytical methods under deep-beam conditions has not been systematically compared or clearly defined. Classical elastic beam theory is widely used to evaluate pillar stresses, but it can yield substantial errors at non-slender geometries. Its limitations become pronounced when interlayer shear transfer and vertical compression cannot be neglected, which typically occurs when h/L > 0.2 (equivalently, h/L < 5).The aim of this paper is to compare the applicability and accuracy of analytical methods for deep-beam problems. We develop a layered deep-beam decomposition method, where the coal pillar–floor system is idealized as a simply supported rock beam under a uniformly distributed hydraulic load and discretized through the thickness into interacting shallow-beam layers to account for interlayer shear transfer and vertical compression. Based on a deep-beam model of the faulted floor, analytical solutions are obtained using both the classical elastic stress-function method and the proposed layered deep-beam decomposition method, and are validated against FLAC3D numerical simulations. Representative comparisons show that, for h/L = 0.3–1.0, the proposed approach (using 10, 16, and 20 layers) predicts mid-span normal stresses with relative errors of 6.0%–9.9%. In contrast, the classical elasticity solution deteriorates rapidly as h/L increases: the relative error can exceed 100% at larger h / L , and the solution fails to capture the downward migration of the neutral axis. Application to an engineering case from a deep coal mine in northern Anhui Province further indicates that, after incorporating a safety factor, the predicted pillar width is consistent with empirical design guidelines, supporting the method’s engineering applicability. Overall, this study focuses on the comparison of applicability and computational accuracy between the two analytical methods, which helps to clarify the applicable conditions and advantages of each method for deep-beam models in water-resisting coal pillar analysis.
Abstract TH889: Equol or equol producer - which is more important for cognition?
Background: Evidence from observational studies and short-duration randomized controlled trials (RCTs) suggests that equol, a gut-derived metabolite of soy isoflavone daidzein, may confer cognitive benefits through efficient blood-brain barrier permeability, high selective affinity to the estrogen receptor-beta, and anti-atherogenic properties. Only 20-30% of Westerners possess the ability to convert daidzein to equol as compared to 50-70% of East Asians. Cross-sectional studies conducted in Japan reported that equol producers exhibit fewer white matter lesions (WMLs) and better cognition. However, it is unclear whether equol or the equol producer phenotype as a surrogate for certain microbiome composition or both may protect against dementia. Objective: To delineate the effect of equol and equol producers by testing whether equol producers have fewer WMLs and better cognitive function than non-producers in an older population with very low soy consumption. Methods: The Arterial Stiffness, Equol, and Cognition (ACE) trial (NCT05741060) recruited dementia-free infrequent soy consumers aged 65-85 to test whether equol supplementation can slow the progression of arterial stiffness, WMLs, and cognitive impairment. This analysis included 362 ACE participants (mean age 72.0 ± 4.7 years; 52% female; 21% African American) who underwent brain magnetic resonance imaging (MRI) scans and NIH Toolbox Cognitive Battery assessments. Equol producer phenotype was defined as the urinary equol-to-daidzein ratio (log10 ≥ -1.75) after a three-day soy challenge. Associations of equol producer phenotype with WMLs normalized to total intracranial volume (WML%) and cognitive tests were assessed using gamma-distributed generalized linear regression and linear regression adjusting for demographics, APOE-e4 status, and cardiovascular risk factors. Results: 30% of the participants were equol producers (Table 1). There is no statistically significant difference in WML% (Table 2) or cognitive performance (Table 3) between equol producers and non-producers. Conclusions: Among infrequent soy consumers, equol producer phenotype is not associated with WMLs or cognitive performance. Without soy intake, equol producers do not show a similar cognitive advantage as observed in East Asians. The results suggest that equol is critical for the cognitive benefits.
Abstract WE441: Progression and Risk of Type 2 Diabetes Mellitus According to Glycemic Phenotypes
Background: Heterogeneity in prediabetes (preDM) etiology may influence progression to type 2 diabetes mellitus (T2DM). Despite its clinical importance, longitudinal data on progression to diabetes according to baseline glycemic status remain limited. Methods: We included Framingham Heart Study Generation 3 based cohorts, free of diabetes who participated in an oral glucose tolerance test (OGTT, n=2,965). Participants with preDM were classified into four glycemic phenotype groups: impaired fasting glucose (IFG-only, 100-125 mg/dl), impaired glucose tolerance (IGT-only, 140-199 mg/dl on OGTT), impaired HbA1c (IA1c-only, 5.7-6.4%), and multiple abnormalities (≥2). We used multivariable Poisson regression models to estimate the risk of developing T2DM for each phenotype group, compared to normoglycemia (referent). Model 1 was adjusted for age, sex, smoking, and education. Fully adjusted model further included waist circumference, systolic blood pressure, hypertension and lipid medication use, and non-HDL cholesterol. Progression of preDM phenotype categories was evaluated in participants who completed a mixed meal tolerance test upon follow-up (n=2,077). Results: Among 2,965 FHS participants (Women 54.06%), the average age was 46 years and 26% had only one marker for preDM at baseline (12% IFG, 3% IGT, 11% IA1c); 11% had multiple abnormalities. Over a median follow-up of 14 years, 219 participants (7%) developed T2DM. Having multiple glycemic abnormalities, compared to normoglycemia, was associated with the highest risk of developing T2DM, followed by IFG, IGT, and IA1c ( Figure 1A ). Individuals with multiple abnormalities had a 19-fold higher incidence rate than normoglycemic participants (IRR [95% CI] = 18.5 [12.7, 27.0], model 1). IFG showed a 6-fold higher risk, IGT a 5-fold higher risk, and IA1c a 4-fold higher risk of developing T2DM compared with normoglycemic participants (p < 0.001). All associations were attenuated but remained significant in the full adjustment model. Progression of preDM phenotypes among a subset of participants with two glycemic challenges in Figure 1B demonstrates substantial instability in glycemic phenotype group membership. Conclusions: Diabetes incidence among middle-aged U.S. adults varied significantly by baseline glycemic phenotypes. These findings suggest that phenotype-specific T2DM prevention strategies may lead to more effective interventions and improved public health outcomes.
Abstract WE440: Non-Hispanic Black Adolescents Show Highest Prediabetes Prevalence Among Normal Weight Adolescents: Evidence from NHANES 2011–2020
Background: Prediabetes is often associated with obesity, yet prevalence among normal-weight adolescents remains underexplored. We hypothesized that racial disparities in prediabetes persist independent of obesity status Methods: We analyzed pooled 2011–2020 NHANES data for U.S. adolescents aged 10–19 years (n = 4,927). Underweight adolescents, those who had diabetes, or used insulin/metformin were excluded. Prediabetes was defined as HbA1c 5.7–6.4%, and BMI was categorized per CDC growth charts (normal 5th–<85th percentile, overweight ≥85th–<95th, obese ≥95th). The primary exposure was self-reported race/ethnicity. Weighted logistic regression models, adjusted for age, sex, and BMI, estimated the odds of prediabetes.. Results: Prediabetes prevalence differed significantly across race/ethnicity (Chi-Square = 39.0, p < 0.001). Compared with Non-Hispanic White adolescents, odds of prediabetes were higher among Non-Hispanic Black (OR = 6.22, 95% CI 4.21–9.19), Other/Multiracial (OR = 2.82), Non-Hispanic Asian (OR = 2.29), and Hispanic (OR = 2.14) youth. Among normal-weight adolescents (Figure 1), disparities persisted (Chi-Square = 12.48, p < 0.001), with Non-Hispanic Black youth showing the highest prevalence (11.6%) and nearly fivefold greater odds versus Non-Hispanic Whites. Among overweight/obese adolescents, differences remained (Chi-Square = 23.91, p < 0.001), with Non-Hispanic Black youth again showing the greatest odds (OR = 7.41, 95% CI 4.40–12.49). Conclusion: Racial disparities in prediabetes are evident even among normal-weight adolescents, with Non-Hispanic Black youth at greatest risk. Screening strategies relying solely on obesity may overlook at-risk adolescents and should incorporate early, weight-independent prevention efforts.
Synthetic SIGLEC9-based chimeric switch receptor augments the efficacy of CAR macrophages against glioblastoma
Chimeric antigen receptor macrophage (CAR-M) therapy represents a promising therapeutic approach for treating glioblastoma multiforme (GBM). However, durable antitumorigenic macrophage phenotype of CAR-Ms is limited by the highly immunosuppressive tumor microenvironment (TME), wherein Siglec–sialic acid signaling directly drives macrophage polarization toward a protumorigenic phenotype. We here report an in situ synthetic SIGLEC9-based chimeric switch receptor (CSR) for diverting the inhibitory signal into positive ones, augmenting the sustained proinflammatory phenotype and tumoricidal immunity of CAR-Ms in the GBM niche. Specifically, our results showed that macrophage-targeted ionizable lipid nanoparticles efficiently introduce dual circRNAs into macrophages to generate CSR functionalized CAR-Ms in vitro and in vivo. The modified macrophages maintained a proinflammatory state, exhibited superior phagocytic activity, resulting in rapid and efficient eradication of IL13Rα2-positive tumor cells. Moreover, an injectable nanoparticle–hydrogel system for reprogramming macrophages surrounding the glioma resection cavity initiated a locoregional antitumor immune response and elicited robust long-term immunological memory, inhibiting tumor relapse in the postoperative GBM model. In sum, our findings establish that the engineered SIGLEC9-based CSR significantly promotes the maintenance of an antitumoral phenotype of CAR-Ms in the hypersialylated acidic TME, contributing to the improvement of engineered macrophage-based immunotherapy against GBM.
Ultrasound-triggered doxorubicin targeted delivery for liver cancer treatment: Reduced toxicity and improved efficacy
Liver cancer, especially hepatocellular carcinoma (HCC), remains a major global health challenge, causing high mortality worldwide. Conventional chemotherapy often results in severe side effects due to its systemic distribution, which limits its effectiveness in targeting cancer cells specifically. The development of targeted drug delivery systems can enhance the precision and efficacy of chemotherapeutic agents while reducing their side effects. In this context, we used lactobionic acid (LA) as a targeting moiety due to its ability to bind to the asialoglycoprotein receptor (ASGPR), which is highly expressed on the surface of hepatocytes (liver cells). Conjugating lactobionic acid to liposomes creates an efficient delivery system that specifically targets liver cancer cells, thereby ensuring a higher uptake of the drug by these cells. Ultrasound is used to further facilitate drug release by enhancing drug targeting, promoting accumulation at the tumor site, and triggering drug release, thereby making the treatment more effective and less toxic. This study successfully synthesized stable DOX-loaded liposomes conjugated with lactobionic acid (LL) on their surface, with a size range of 89.4 ± 0.9 nm and a polydispersity index of 13.06 ± 3.5. Successful LA-DSPE-PEG-NH 2 conjugation to the LL was confirmed via Fourier Transform Infrared spectroscopy. The sulfuric acid colorimetric assay quantified lactobionic acid conjugation as 14 ± 1.35% (w/w), while DOX encapsulation was measured at 40.1 ± 1.6%. LL exhibited strong absorption, fluorescence properties and good stability at 37 ˚C. LL showed controlled release via ultrasound, making it suitable for precise drug delivery. In vitro studies on HepG2 cells confirmed enhanced drug uptake and therapeutic efficacy. The effects of ultrasound-enhanced drug delivery to HepG2 cells demonstrated that the combination of ultrasound and targeted liposomes significantly increased the internalization of the drug (DOX) and triggered apoptosis in HepG2 cells, leading to cell death. Morphological observations on treated cells via phase contrast microscopy supported the signs of apoptosis, indicating LL’s potential to target liver cancer cells effectively.
Abstract WE565: Association of Stroke Subtypes With Sociodemographic, Modifiable, and Nonmodifiable Risk Factors in an Adult Asian Population: A Cross-Sectional Study
Introduction: Stroke incidence in Asia has nearly doubled over the past three decades, driven by demographic aging and lifestyle transitions. Yet, few studies have simultaneously examined how sociodemographic, modifiable, and nonmodifiable factors influence specific stroke subtypes. This study aimed to identify determinants associated with transient ischemic attack (TIA), ischemic stroke, and hemorrhagic stroke in an adult Asian cohort to inform population-specific prevention strategies. Methods: A hospital-based cross-sectional study was conducted among 238 adults with confirmed stroke at tertiary centers in Western India. Participants were categorized into TIA, ischemic, and hemorrhagic subtypes. Sociodemographic data and clinical risk factors were collected through structured interviews. Associations between variables and stroke subtypes were assessed using chi-square tests, with significance defined as p < 0.05. Results: Of 238 participants, 62.2% were male and 71.4% were aged > 60 years. Ischemic stroke was significantly associated with male sex, older age, and rural residence (all p < 0.05). Modifiable factors linked to ischemic stroke included obesity, tobacco use, dyslipidemia, and diabetes mellitus (p < 0.05 for each), while hypertension showed a stronger association with hemorrhagic stroke (p < 0.01). Among nonmodifiable variables, age > 70 years, positive family history, prior stroke, and ischemic heart disease were each significantly related to ischemic stroke (all p < 0.05). Conclusions: Distinct demographic and clinical profiles characterize stroke subtypes in Asian populations. Metabolic and lifestyle factors predominated in ischemic stroke, whereas hypertension remained the principal determinant of hemorrhagic events. These findings highlight the need for integrated, community-based screening and targeted modification of behavioral and metabolic risks to curb the growing stroke burden across low- and middle-income countries.
Abstract WE564: Identifying Sex Differences in Proteins Associated with Incident Ischemic Stroke in the UK Biobank
Background: Stroke remains one of the leading causes of death and morbidity worldwide, with a disproportionately higher burden among women. Recent advancements in omics, including proteomics, present a unique opportunity to uncover sex differences in pathways implicated in stroke. Methods: Using the OLINK platform, 2,911 proteins were measured in 24,041 men and 28,251 women from the UK Biobank, including 609 men and 445 women who developed ischemic stroke (IS). Median time from blood collection to IS was 8.6 years (IQR 5.0–11.3) in men and 9.1 years (IQR 5.5–12.0) in women. Each IS case was matched to 20 age-matched controls. Sex-specific associations between proteins and IS were assessed using conditional logistic regression (CLR) adjusted for demographic, clinical, and behavioral factors. Proteins significantly associated with IS (FDR p -value < 0.05) in at least one sex were used to derive sex-specific IS scores via LASSO logistic regression (70% training, 30% testing). Sex differences in protein–IS associations were evaluated using protein–sex interaction terms in CLR models that were fit to a combined sample of men and women. Results: 148 proteins were associated with incident IS in men (29 proteins), women (92 proteins), or both (27 proteins), meeting an FDR p -value < 0.05. No protein showed a significant protein-sex interaction at FDR p -value < 0.05. However, 9 proteins showed suggestive sex interactions ( p -value < 0.05; FDR p -value < 0.12). These proteins were involved in immune regulation, posttranslational modification, cell adhesion and signaling, and synaptic function. Cerebellin-4 was inversely associated with IS in women (odds ratio (OR) = 0.84, 95% CI: 0.77–0.93) but not in men (OR = 0.99, 95% CI: 0.91–1.07). Ribonuclease T2 and Desmocollin-2 were each positively associated with IS in both sexes, with stronger effects in women, while the remaining six proteins were significantly positively associated with IS in women only. The sex-specific IS scores remained significantly associated with IS after adjusting for risk factors, with ORs per 1 SD increase of 1.42 (95% CI: 1.18–1.70) in men and 1.58 (95% CI: 1.30–1.93) in women. Conclusion: This study identifies proteomic signatures associated with incident IS risk in men and women. Proteins having sex-specific associations were primarily involved in pathways related to immune response, intercellular signaling, post-translational modification, and synaptic function and plasticity.