Citations

Abstract Background While the radiation dose to left anterior descending (LAD) artery is associated with overall survival (OS) in NSCLC patients, manual segmentation is labor‐intensive. Several auto‐segmentation models were developed on average 4DCT with promising geometric agreement, yet their feasibility in clinical outcome analysis on lung CT remains unclear. Purpose This study evaluates whether automated LAD segmentation can reproduce, at the group level, the established dose‐survival association in a multi‐institutional clinical trial dataset. Methods Three deep learning‐based auto‐segmentation (DLAS) models for automatic segmentation of the LAD coronary artery were applied to 460 patients from the NRG Oncology/RTOG 0617 dataset. Kaplan–Meier curves and Cox proportional hazard ratio (HR) were calculated using each model's segmentation. The LAD V15 Gy was used to stratify patients into high‐and low‐risk groups, and the cut‐off values were determined by minimizing mean absolute error (MAE) between DLAS‐derived and manual OS curves. Results All three models demonstrated significantly different OS curves between the high risk and low risk groups ( p < 0.05). The HR was 1.40 (95% CI: 1.02–1.93; p = 0.0381; MAE = 7.1%), 1.32 (95% CI: 1.03–1.68; p = 0.0258; MAE = 9.6%), and 1.37 (95% CI: 1.03–1.84; p = 0.0331; MAE = 7.9%) for the three models using a common V15 Gy ≥ 10% cut‐off. After optimizing the cut‐off, one model aligned well with what was derived from manual segmentation (MAE = 4.3%). Conclusion Among the evaluated models, one DL model showed the strongest performance of survival groups separation and achieved group‐level overall survival stratification comparable to that previously reported using manual contours in the multi‐institutional cohort. Further validation with paired manual contours and pre‐specified cutoffs is warranted.

Importance Elevated low-density lipoprotein cholesterol (LDL-C) is a modifiable risk factor for cardiovascular disease, the leading cause of premature death worldwide. Assessing the LDL-C–related burden is critical for guiding prevention and treatment strategies. Objectives To estimate the global, regional, and national burden of ischemic heart disease and ischemic stroke attributable to elevated LDL-C (relative to 35-54 mg/dL) from 1990 to 2023 and to quantify the contributions of population growth, aging, risk-deleted burden, and exposure changes to burden trends. Design, Setting, and Population This comparative risk assessment, part of the Global Burden of Disease Study 2023, estimated population-level LDL-C exposure and associated health loss in 204 countries and territories. Mean LDL-C levels were estimated using spatiotemporal gaussian process regression based on 806 studies across 161 countries. Relative risks were derived from meta-analyses of 38 randomized clinical trials. Population-attributable fractions for deaths and disability-adjusted life-years (DALYs) were estimated by age and sex for adults aged 25 years or older from 1990 to 2023, with 95% uncertainty intervals. Exposure Population-level LDL-C concentrations. Main Outcomes and Measures Population-attributable fractions, counts, and rates (all ages and age standardized per 100 000) of LDL-C–attributable deaths and DALYs from ischemic heart disease and ischemic stroke, with uncertainty intervals. Results In 2023, elevated LDL-C accounted for 3.6 million deaths (95% uncertainty interval, 2.2-5.4 million; 6.0% of global mortality) and 90.7 million DALYs (95% uncertainty interval, 58.9-123.3 million; 3.2% of DALYs). Although global all-ages rates remained stable, age-standardized death and DALY rates decreased by 45.6% and 39.5%, respectively, since 1990. In 2023, age-standardized LDL-C–attributable DALY rates were highest in Eastern Europe and lowest in high-income Asia-Pacific. One-third of the global LDL-C burden occurred in India and China. Population growth and aging drove the increasing burden, with notable regional disparities in LDL-C exposure and risk-deleted DALY rates shifting toward middle-sociodemographic settings. Conclusions and Relevance Despite declining age-standardized rates, the absolute LDL-C burden has increased since 1990 due to demographic changes and has shifted toward middle-sociodemographic countries. Measurement and surveillance gaps persist. Strengthened prevention, diagnosis, and treatment access strategies are essential to mitigate the health burden of LDL-C.

Abstract Introduction Mucosal immunization and respiratory IgA offer significant promise in protecting against airborne pathogens, including SARS-CoV-2. However, the conditions and mechanisms that lead to the robust induction of respiratory IgA responses following mucosal vaccination remain poorly understood. Methods In this project, we established SARS-CoV-2 breakthrough infection and mucosal adenovirus-based booster vaccination models. Using genetic mouse models and various in vivo and in vitro blockade or depletion approaches, we further investigated the mechanisms regulating respiratory IgA responses. Results Here we found that a mucosal adenovirus-based booster vaccination in mouse models revealed that respiratory booster immunization elicited markedly stronger and more durable respiratory IgA, T cell response, and protective immunity against SARS-CoV-2, supporting the promise of respiratory mucosal vaccination. Mechanistically, we identified that local CD4+ T cells support respiratory IgA production by promoting IgA+ B cell class switching, proliferation, and survival in situ. This T cell help depended on interactions between local Blimp-1+ T-bet+ Th1 cells and B cells, mediated through ICOS/CD40L/MHC-II engagement and IL-21 signaling. Furthermore, lung macrophages contributed to the mucosal IgA response via TGF-β production. Consequently, mucosal administration of SARS-CoV-2 Spike-encoding mRNA encapsulated in pulmonary surfactant (PS)- incorporated lipid nanoparticles designed to target lung macrophages elicited a stronger mucosal IgA response. Conclusion Our results uncover a local cellular network supporting enhanced mucosal IgA responses, with implications for the development of optimal mucosal immunization strategies against SARS-CoV-2 and other respiratory pathogens such as H5N1 influenza. Funding Source AI147394, AG069264, AI112844, HL170961, AI154598, AI176171 to J.S., AI67986, AI177467 to Hui.H; U54CA260582 to S.L.L; R01AI168684 to G. Z.; S.L.L was also supported by a fund provided by an anonymous private donor to The Ohio State University. Topic Categories Mucosal and Regional Immunology (MUC)

Abstract Introduction The underlying immunopathogenesis of inflammatory arthritis (IA) immune-related adverse event (irAE) remains obscure. Unlike rheumatoid arthritis (RA), where autoantibodies and B cell dysfunction are central features, the contribution of humoral immunity to IA-irAE is unclear. Methods Here, we performed immunophenotyping of peripheral blood from IA-irAE patients, and compared them with seronegative RA patients, ICI-treated patients without irAE, and healthy controls. Results IA-irAE was marked with increased cytotoxic gene expression and metabolic activation in T cells, and reduced CXCR3 and CCR6 expression in CD4+ T cells. Contrary to seronegative RA, IA-irAE patients displayed no significant elevation in autoantibody levels or atypical CD11c+CD21⁻ B cells. IA-irAE was further characterized by elevated levels of IL-6, IL-12, and type I IFN, which correlated with the T cell activation phenotypes. Conclusion Altogether, our findings define IA-irAE as a disease with certain immunological features distinctive from RA, representing a potentially T cell driven, autoantibody-independent autoimmunity. These results offer insights into immune tolerance breakdown and therapeutic targeting in irAEs. Funding Source National Institute of Arthritis and Musculoskeletal and Skin Diseases Mark E. and Mary A. Davis Initiative in Rheumatoid Arthritis Research Mayo Foundation for Medical Education and Research Topic Categories Basic Autoimmunity (BA)

Background Hearing impairment (HI) has been identified as a potentially modifiable risk factor for dementia, yet its relationship with Alzheimer's disease (AD) neuropathology and the temporal directionality remain unclear, particularly in late life. Objective To examine cross-sectional and longitudinal associations between HI, clinical cognitive status, and AD biomarkers in community-dwelling older adults. Methods We included 474 DRIVES Project participants (mean age 73.5 ± 5.2 years). Hearing was assessed using the NIH Toolbox Words-in-Noise (WIN) test. Clinical cognitive status was assessed using Clinical Dementia Rating (CDR). AD biomarkers included cerebrospinal fluid (CSF) Aβ 42 /Aβ 40 , t-tau/Aβ 42 , and p-tau/Aβ 42 ratios and amyloid PET imaging. Multivariable linear, logistic, Cox proportional hazards, and Fine–Gray competing-risk models were used. Results HI was more prevalent among participants with mild cognitive impairment (MCI; defined as CDR = 0.5) than cognitively normal individuals (50% versus 24%, p < 0.001), and MCI status was independently associated with worse baseline WIN thresholds (β = 1.55 dB SNR; 95% CI 0.72–2.37). HI was not cross-sectionally associated with CSF amyloid or tau ratios or amyloid PET positivity. Longitudinally, baseline MCI was associated with a higher risk of incident HI (Cox HR = 2.63, 95% CI 1.48–4.67; Fine–Gray sHR = 2.79, 95% CI 1.06–7.40), whereas baseline HI was not associated with subsequent CDR progression. Conclusions In older adults, HI was associated with MCI but not core AD biomarkers or future CDR progression, suggesting that late-life HI may reflect cognitive vulnerability or broader brain aging rather than independently driving AD pathology.

Abstract Epigenetic inheritance relies on the precise recycling of parental histones during DNA replication. The N-terminal region of Pol1, the catalytic subunit of DNA polymerase α, has previously been implicated in chaperoning parental histone recycling. In this study, we identify a single amino acid mutation in the C-terminal region of Saccharomyces cerevisiae Pol1 (pol1-F1396S) that destabilizes the protein and disrupts the transfer of parental histones to the lagging strand during DNA replication. As a primary consequence, pol1-F1396S cells exhibit decreased chromatin stability. Furthermore, we demonstrate that the cellular abundance—or dosage—of all three DNA polymerases (Pol α, Pol δ, and Pol ε) influences the distribution of parental histones between the leading and lagging strands, revealing a dosage-sensitive mechanism of epigenetic regulation during DNA replication.