Citations

Abstract The aging process is universal, and it is characterized by a progressive deterioration and decrease in physiological function leading to decline on the organismal level. Nevertheless, a number of genetic and nongenetic interventions have been described, which successfully extend healthspan and lifespan in different species. Furthermore, a number of clinical trials have been evaluating the feasibility of different interventions to promote human health. The goal of the annual Biological Sciences Section of the Gerontological Society of America meeting was to share current knowledge of different topics in aging research and provide a vision of the future of aging research. The meeting gathered international experts in diverse areas of aging research including basic biology, demography, and clinical and translational studies. Specific topics included metabolism, inflammaging, epigenetic clocks, frailty, senescence, neuroscience, stem cells, reproductive aging, inter-organelle crosstalk, comparative transcriptomics of longevity, circadian clock, metabolomics, and biodemography.

ABSTRACTBackgroundThe factors contributing to sustained ventricular arrhythmias (VAs) >30 days after left ventricular assist device (LVAD) implantation are not well‐established.ObjectivesThis study aimed to predict the factors associated with late sustained VAs after LVAD implantation and develop a predictive score to identify patients with an increased risk of late sustained VAs after the procedure.MethodsWe performed a retrospective cohort study on a training cohort of 623 patients and a validation cohort of 157 patients who underwent LVAD implantation at the Mayo Clinic (Rochester, Phoenix, and Jacksonville) from January 1, 2000, to December 30, 2020. Late sustained VAs were defined as ventricular tachycardia (VT) and ventricular fibrillation (VF) occurring >30 days after the LVAD procedure. Detailed chart reviews of the electronic health records within the Mayo Clinic and outside medical records were performed.ResultsA total of 780 patients were included in our study. Late sustained VAs occurred in 30% (n = 232) of the patients. The significant factors associated with late sustained VAs after LVAD were the history of VAs prior to LVAD (34.1% vs. 23.0%, p < 0.01), implantable cardiac defibrillator (ICD) (87.9% vs. 77.6%, p < 0.01) or cardiac resynchronization therapy (CRT) in situ (43.5% vs. 33.6%, p = 0.008), VT ablation prior to LVAD (5.2% vs. 1.8%, p = 0.010), use of amiodarone (49.1% vs. 38.7%, p = 0.007), use of mexiletine (15.5% vs. 5.7%, p < 0.01), and higher left ventricular end‐diastolic diameter (LVEDD) on echocardiography prior to LVAD implantation (71.4 vs. 68.7 mm, p = 0.002). During follow‐up, the patients who developed late sustained VAs after LVAD had lower survival than those who did not (HR = 1.96, 95% CI:156–2.4, p < 0.001). The average time from LVAD to orthotopic heart transplant was longer among late sustained VAs patients (23 vs. 14 months, p < 0.01). The “VIN” risk score was created to identify four risk groups: low (scores 0), intermediate (score 1), high (score 2), and very high (score 3). The rates of late VA's in the training cohort at 1 year were 9.5%, 14%, 18%, and 25% which was almost similar to the risk of late VA's at validation cohort 10%, 12%, 20%, and 63%, respectively.ConclusionsLate sustained VAs occurred in 30% of the patients who received LVAD and were associated with lower survival. The VIN risk score was developed and validated to stratify patients into low, intermediate, high, and very high risk of late sustained VAs.

Abstract The prevalence of steatotic liver disease (SLD) is rising globally, presenting a significant public health challenge. While non-contrast computed tomography (CT) scans hold promise for the opportunistic detection of SLD, their full potential has not been systematically explored. Clinical indicators, such as serum data, are crucial for monitoring the progression of SLD. We introduce a novel Multimodal AI for Opportunistic Steatotic Liver Disease Screening (MAOSS), which integrates demographic data, serum tests, conventional CT biomarkers, and deep learning-derived CT image features to enhance model performance and explainability. MAOSS employs an innovative learning strategy, trained on a large-scale dataset (n = 1,783) encompassing both histopathologically-confirmed SLD and radiologically-reported steatosis cases. The model underwent extensive retrospective validation using steatosis grades derived from both histology and MRI-PDFF across internal and external datasets (n = 913), as well as real-world patient data (n = 18,504). It accurately detected mild to severe steatosis (≥ S1) with AUCs ranging from 0.903 to 0.929. Notably, MAOSS significantly improved the overall AUC for radiologists (n = 11) from 0.709 to 0.798 (p < 0.001). Furthermore, MAOSS was applied to optimize the standard clinical pathway for a simulated primary risk screening of SLD patients (n = 1,192), resulting in the identification of 31% more patients at risk of steatohepatitis and liver fibrosis progression, highlighting its potential to enhance SLD detection and management.

Background/Objectives: Stereotactic body radiation therapy (SBRT) for skull base reirradiation is particularly challenging, as patients have already received substantial radiation doses to the region, and nearby normal organs may have approached their tolerance limit from prior treatments. In this study, we reviewed the characteristics and capabilities of four advanced external beam radiation delivery systems and four modern treatment planning systems and evaluated the treatment plan quality of each technique using skull base reirradiation patient cases. Methods: SBRT plans were generated for sixteen skull base reirradiation patients using four modalities: the GK plan for the Elekta Leksell Gamma Knife Perfexion/ICON, the CyberKnife (CK) plan for the Accuray CyberKnife, the intensity-modulated proton therapy (IMPT) plan for the Hitachi ProBeat-FR proton therapy machine, and the volumetric-modulated arc therapy (VMAT) plan for the Varian TrueBeam STx. These plans were evaluated and compared using two novel gradient indices in addition to traditional dosimetry metrics for targets and organs at risk (OARs). The steepest border gradient quantified the percent prescription dose fall-off per millimeter at the boundary between the target and adjacent critical structures. This gradient index highlighted the system’s ability to spare nearby critical OARs. The volume gradient assessed the extent of dose spread outside the target toward the patient’s body. Results: All plans achieved comparable target coverage and conformity, while IMPT and VMAT demonstrated significantly better uniformity. The GK plans exhibited the highest border gradient, up to 20.9%/mm, followed by small-spot-size IMPT plans and CK plans. Additionally, IMPT plans showed the benefit of reduced dose spread in low-dose regions and the lowest maximum and mean doses to the brainstem and carotid artery. Conclusions: The advanced external beam radiotherapy modalities evaluated in this study are well-suited for SBRT in skull base reirradiation, which demands precise targeting of tumors with highly conformal doses and steep dose gradients to protect nearby normal structures.

ABSTRACT Genes involved in the regulation of chromatin structure are frequently disrupted in cancer, contributing to an aberrant transcriptome and phenotypic plasticity. Yet, therapeutics targeting mutant forms of chromatin-modifying enzymes have yielded only modest clinical utility, underscoring the difficulty of targeting the epigenomic underpinnings of aberrant gene regulatory networks. Here, we sought to identify novel epigenetic vulnerabilities in diffuse large B-cell lymphoma (DLBCL). Through phenotypic screens and biochemical analysis, we demonstrated that inhibition of the H3K9 demethylases KDM4A and KDM4C elicits potent, subtype-agnostic cytotoxicity by antagonizing transcriptional networks associated with B-cell identity and epigenetically rewiring heterochromatin. KDM4 demethylases associated with the KRAB zinc finger ZNF587, and their enzymatic inhibition led to DNA replication stress and DNA damage-induced cGAS-STING activation. Broad surveys of transcriptional data from patients also revealed KDM4 family dysregulation in several other cancer types. To explore this potential therapeutic avenue, we performed high-throughput small molecule screens with H3K9me3 nucleosome substrates and identified novel KDM4 demethylase inhibitors. AI-guided protein-ligand binding predictions suggested diverse modes of action for various small molecule hits. Our findings underscore the relevance of targeting fundamental transcriptional and epigenetic mechanisms for anti-cancer therapy. HIGHLIGHTS Phenotypic screens identified JIB-04 as a potent anti-cancer agent for multiple subtypes of diffuse large B-cell lymphoma JIB-04 binds and inhibits KDM4 demethylases resulting in epigenomic rewiring of heterochromatin KDM4 demethylases cooperate with KRAB zinc fingers to limit DNA replication stress, and KDM4 inhibition instigates DNA-damage and cGAS-STING activation in several human cancers High-throughput small molecule screens with semi-synthetic nucleosome substrates and AI-guided molecular docking simulations identify novel KDM4 inhibitors

Abstract Single-cell RNA sequencing (scRNA-seq) enables high-resolution exploration of cellular diversity and gene regulation, yet analyzing such data remains challenging due to technical and methodological limitations. Existing task-specific deep generative models like Variational Auto-Encoder (VAE) and its variants struggle to incorporate external biological knowledge, while transformer-based foundational large Language Models (LLMs or large LaMs) face limitations in computational cost and applicability to tabular gene expression data. Here, we introduce sciL-aMA (single-cell interpretable Language Model Adapter), a novel representation learning frame-work that bridges these gaps by integrating static gene embeddings from multimodal LLMs with scRNA-seq tabular data through a paired-VAE architecture. Our approach generates context-aware representations for both cells and genes and outperforms state-of-the-art methods in key single-cell downstream tasks, including batch effect correction, cell clustering, and cell-state-specific gene marker and module identification, while maintaining computational efficiency. sciL-aMA offers a computationally efficient, unified framework for comprehensive single-cell data analysis and biologically interpretable gene module discovery. Source code is available at https://github.com/microsoft/sciLaMA

ObjectiveThe objective was to determine the mortality rate as well as the causes and predictors of death in antiphospholipid antibody (aPL)–positive patients with and without antiphospholipid syndrome (APS) classification.MethodsThe inclusion criterion for the multicenter international Antiphospholipid Syndrome Alliance for Clinical Trials and International Networking (APS ACTION) registry is positive aPLs according to the Revised Sapporo Classification Criteria tested within one year before enrollment. Patients are observed every 12 ± 3 months with clinical data and blood collection. For this prospective analysis, we first analyzed the causes of death for patients reported as “deceased.” Secondly, we analyzed risk factors for death using the adjusted Cox proportional hazards model and calculated survival probability using the Kaplan‐Meier model based on different age groups.ResultsOf 967 patients, 43 (5%) were deceased after a median follow‐up of 5.3 years. Based on the univariate analysis, deceased patients, compared to living patients, were more likely to be older and have a history of arterial thrombosis, catastrophic APS, concomitant systemic autoimmune diseases (SAIDs), and baseline cardiovascular disease (CVD) risk factors. Based on the Cox proportional hazards model adjusted for age and for each of the strongest predictors of death, arterial thrombosis (hazard ratio [HR] 2.94, 95% confidence interval [CI] 1.50–5.76), concomitant SAIDs (HR 2.97, 95% 1.56–5.63), and baseline any CVD risk factor (HR 2.43, 95% CI 1.05–5.71) were significantly associated with mortality.ConclusionIn our cohort of persistently aPL‐positive patients, the mortality rate was 5% after a median follow‐up of five years and was highest for patients ≥60 years old at registry entry. History of arterial thrombosis, concomitant SAIDs, and baseline any CVD risk factor independently predicted future death.