Citations

Abstract SV40 Large T antigen (LT) is essential for viral replication and a key determinant of host range. This host-range function is mediated by the C-terminal domain (LT-C) through binding to the host serine protease FAM111A, but the underlying mechanism has remained unclear. Here, we report the X-ray crystal structure of the FAM111A serine protease domain in complex with LT-C, revealing the structural basis for direct inhibition of FAM111A. LT-C uses a previously unrecognized zinc-binding motif and a P1-like phenylalanine residue to engage the FAM111A active site through a substrate-mimicking mechanism while avoiding proteolytic cleavage and covalent complex formation. Mutations disrupting either feature abolish FAM111A inhibition and impair SV40 propagation in cells. Consistent with this mechanism, SV40 host restriction requires FAM111A protease activity, which must be antagonized by LT-C for productive infection. Together, these findings define a zinc-dependent, cleavage-avoiding mechanism of protease inhibition that highlights an evolutionary arms race between SV40 and host antiviral proteases.

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 Objective To describe the development and implementation of an automated platform for genomic risk prediction that integrates multiple data types. Materials and methods Using the REDCap infrastructure, we constructed the R4 (Recruitment, Results, and Risk Reduction) platform to intake data from clinical sites, partner laboratories, participant surveys, and electronic health record (EHR) data across 13 institutions. Results The R4 Portal successfully integrated data to generate genome-informed risk assessments (GIRAs) across 11 conditions for a 23 840 person cohort. Testing phases and quality control led to network-wide protocols ensuring consistency and accuracy. Discussion As the science of estimating disease risk evolves, standardized and high-throughput methods of collecting and manipulating complex data are required. Platforms should be open-source, modular, and reusable, ensuring flexibility, security, and integration across healthcare environments. Conclusion The electronic MEdical Records and GEnomics (eMERGE) network successfully generated and returned comprehensive risk profiles using logic and data specific to 11 conditions in a secure and semi-automated fashion employing a customized REDCap database.

Inflammatory bowel disease (IBD) is driven by a breakdown in immune regulation and epithelial barrier function, yet the contribution of eosinophils to this process has remained poorly defined and controversial. While eosinophils infiltrate the intestinal mucosa during both flares and remission, their role in shaping disease outcomes is unclear. Our RNA-seq analyses of colonic eosinophils isolated from dextran sulfate sodium (DSS)-treated mice revealed a significant upregulation of cyclooxygenase (COX)-2 (gene name, Ptgs2 ). Eosinophil-specific deletion of COX-2 (Ptgs2 fl/fl eoCre +/− ) reduced IL-22 production and exacerbated DSS- and trinitrobenzene sulfonic acid (TNBS)-induced colitis, characterized by greater weight loss, higher disease activity, colon shortening, and epithelial injury. Administration of recombinant IL-22 reversed these phenotypes. Mechanistically, eosinophil-derived COX-2 enhanced IL-22 production by type 3 Innate lymphoid cells (ILC3s) through prostaglandin E2 (PGE 2 ) signaling. Consistently, Ptgs2 fl/fl eoCre +/− mice exhibited reduced colonic PGE 2 levels, while PGE 2 analog treatment restored IL-22 production and mucosal protection. Our findings identify eosinophil-derived COX-2 and PGE 2 as a critical regulator of IL-22 production during colitis, uncovering a eosinophil–ILC3 cross talk that safeguards the intestinal barrier and represents a promising therapeutic target in IBD.

ABSTRACT Immediate early genes (IEGs) encode master transcription factors, including EGR1 , FOS , JUN , and MYC genes that drive robust transcription in the G1 phase of cell cycle. Our previous studies indicate that topoisomerase IIβ (TOP2B) critically regulates IEG transcription and that the activities of TOP2B are dynamically controlled through post-translational modifications by BRCA1-BARD1 and ERKs. Here, we show that two E2 enzymes, UBCH5b and UBC13/MMS2, differentiate the effects and functions of TOP2B ubiquitination by BRCA1-BARD1. Comprehensive transcriptomics, proteomics, and biochemical and molecular cellular analyses revealed a close relationship between BARD1 and key mitogen-activated protein kinase pathway genes and identified activated ERK2 as a novel kinase that phosphorylates BARD1 at S391, a previously reported mitotic phosphorylation site, whose genetic mutation has been linked to tumorigenesis. Mechanistically, the catalytic activity of ERK2 stimulates TOP2B ubiquitination mediated by BRCA1-BARD1 in complex with UBCH5b and UBC13/MMS2, which controls the binding and function of TOP2B and BARD1 for transcriptional activation at representative IEGs. Taken together, our data propose that there is a functional regulatory circuit involving TOP2B, BARD1, and ERK2, three key transcriptional activators for IEG transcription, in which the gene association and catalytic activity of TOP2B are regulated through E2-differentiated ubiquitination by BRCA1-BARD1 and the phosphorylation of BARD1 by ERK2 for productive transcription.

The 2025 Voice AI Symposium represented a transition from conceptual research to clinical implementation in vocal biomarker science. Hosted by the NIH-funded Bridge2AI-Voice consortium, the meeting convened global experts to address the methodological, ethical, and translational challenges of integrating voice-based artificial intelligence (AI) into healthcare. This mini-review synthesizes symposium insights across six domains: multimodal integration, FAIR (Findable, Accessible, Interoperable, Reusable) and CARE (Collective Benefit, Authority to Control, Responsibility, Ethics) data governance, clinical translation, interdisciplinary training, and cross-sector innovation. Research presented demonstrated voice as a latent, multimodal biomarker reflecting neurological, cardiopulmonary, and psychological states, while discussions emphasized ethical data practices and human-centered design. The implementation-focused panels underscored the importance of workflow alignment and usability for adoption in real-world care. Collectively, the symposium reflects a field advancing toward translational readiness and ethical accountability, positioning voice AI as a scalable, inclusive tool for next-generation healthcare.

Anthracyclines are potent chemotherapeutic agents, yet their clinical use is hampered by their cardiotoxicity. Anthracyclines achieve potent anti- cancer effects primarily via TOP2A, but at the same time they induce a dose limiting cardiotoxicity through TOP2B. The use of a catalytic TOP2 inhibitors such as dexrazoxane (ICRF 187) significantly reduces the incidence of anthracycline-induced cardiotoxicity. However, dexrazoxane targets the highly conserved TOP2 dimer interface that is identical between TOP2A and TOP2B, fostering persisting concerns that its inhibition of TOP2A isoenzyme may interfere with anthracycline anticancer effects and augment anthracycline-induced myelosuppression. Thus, isoform- selective TOP2 inhibitors that can control the DNA damage caused by TOP2A vs TOP2B are a significant unmet clinical need. We have developed a new class of highly potent and TOP2B-selective catalytic inhibitors through rational design by building upon the general pharmacophore present in isolates from Calophyllum Brasiliense. Using X-ray crystallography, we demonstrate that our newly developed compounds occupy a previously unidentified druggable binding-site in the TOP2 ATPase domain and function as a physical barrier to block the conformational change triggered by ATP hydrolysis. We have named the class of inhibitors that target this site “obex”, the Latin word for obstacle. The obex binding site contains residues that differ between the TOP2A and TOP2B isoenzymes, based on which we rationally designed, prepared, and systematically evaluated a targeted panel of obex inhibitors. We have identified the lead molecule, namely, topobexin, as the first- in-class TOP2B-specific obex inhibitor that can prevent anthracycline-induced DNA damage. This first TOP2 isoform-specific inhibition underscores the broader potential to improve drug specificity and minimize adverse effects in various medical treatments.

Abstract Objectives To implementation an automated multi-institutional pipeline that delivers breast-cancer risk integrated with polygenic risk scores, monogenic variants, family history, and clinical factors, emphasizing operational challenges and their solutions. Materials and Methods A five-stage process was executed at ten sites. Data streams from REDCap surveys, PRS and monogenic reports, and MeTree pedigrees were normalized and forwarded through a REDCap plug-in to the CanRisk API. Results Integrated risk was returned to >10 000 women; 3.6% were ≥25 % lifetime risk and 0.9% carried pathogenic variants. Pipeline generated score aligns well with manual generated ones. Major barriers such as heterogeneous pedigree formats, missing data, edge-case handling, and evolving model versions were identified and resolved through mapping rules, imputations, and iterative testing. Discussion Cross-platform data harmonization and stakeholder alignment were decisive for success. Borderline-risk communication and model-version drift remain open issues. Conclusion Large-scale PRS-integrated breast-cancer risk reporting is feasible but requires robust interoperability standards and iterative governance.

Abstract Background The isocitrate dehydrogenase (IDH) mutation status is a key molecular marker in diagnosing and treating brain tumors. Currently, it is determined via invasive tissue biopsy. Recent advances in deep learning (DL) have offered promising non-invasive alternatives for determining IDH status. However, their clinical translation is hindered by a significant gap between DL predictions and their clinical applicability. The limited transparency of many DL-networks and inadequate evaluation metrics hinders trust and adoption, as clinicians require clear and validated insights for determining IDH status. These challenges highlight the need for robust validation and measures of predictive reliability to make DL-predictions clinically actionable. Methods We developed a unique approach for non-invasive prediction of IDH status using MRI. We combine a voxel-wise-segmentation network(MC-net) with Bayesian logistic regression (BLR) to provide an IDH status and estimate confidence scores. We utilized a comprehensive dataset of 2,481 glioma cases from eight institutions. Results Our framework(MC-net + BLR) demonstrated robust performance achieving 96.4% and 95.1% classification accuracies on diverse databases, with an AUC of 0.98. The BLR was implemented exclusively on held-out test data, ensuring that the derived confidence scores are independent of the training or validation phases. The derived confidence scores showed a low Brier score of 0.0125, highlighting its superior calibration and uncertainty quantification. Conclusion The developed framework provides an IDH status and a confidence score, offering clinicians an additional layer of assurance in prediction reliability. It bridges the gap between high-performing DL models and their clinical applicability by addressing the challenges in prediction reliability. Our framework is a significant advancement in non-invasive determination of IDH-status and confidence-informed therapeutic decision-making in neuro-oncology.