Citations

AbstractThe intricate role of the autonomic nervous system (ANS) in regulating cardiac physiology has long been recognized. Aberrant function of the ANS is central to the pathophysiology of cardiovascular diseases. It stands to reason, therefore, that neuroscience‐based cardiovascular therapeutics hold great promise in the treatment of cardiovascular diseases in humans. A decade after the inaugural edition, this White Paper reviews the current state of understanding of human cardiac neuroanatomy, neurophysiology and pathophysiology in specific disease conditions, autonomic testing, risk stratification, and neuromodulatory strategies to mitigate the progression of cardiovascular diseases. image

ABSTRACTIntroductionVon Willebrand factor (VWF) multimer analysis is essential for diagnosing and classifying von Willebrand disease (VWD) but requires expert interpretation and is subject to inter‐rater variability. We developed an automated image analysis pipeline using deep learning to improve the reproducibility and efficiency of VWF multimer pattern classification.MethodsWe trained a YOLOv8 deep learning model on 514 gel images (6168 labeled instances) to classify VWF multimer patterns into 12 classes. The model was validated on 192 images (2304 instances) and tested on an independent set of 94 images (1128 instances). Images underwent preprocessing, including histogram equalization, contrast enhancement, and gamma correction. Two expert raters provided ground truth classifications.ResultsThe model achieved 91% accuracy compared to Expert 1 (macro‐averaged precision = 0.851, recall = 0.757, F1‐score = 0.786) and 87% accuracy compared to Expert 2 (macro‐averaged precision = 0.653, recall = 0.653, F1‐score = 0.641). Inter‐rater agreement was very high between experts (κ = 0.883), with strong agreement between the model and Expert 1 (κ = 0.845) and good agreement with Expert 2 (κ = 0.773). The model performed exceptionally well on common patterns (F1 > 0.93) but showed lower performance on rare subtypes.ConclusionAutomated VWF multimer analysis using deep learning demonstrates high accuracy in pattern classification and could standardize the interpretation of VWF multimer patterns. While not replacing expert analysis, this approach could improve the efficiency of expert human review, potentially streamlining laboratory workflow and expanding access to VWF multimer testing.

Abstract Determining the balance between DNA double strand break repair (DSBR) pathways is essential for understanding treatment response in cancer. We report a method for simultaneously measuring non-homologous end joining (NHEJ), homologous recombination (HR), and microhomology-mediated end joining (MMEJ) and show that HR and MMEJ are therapeutically-targetable treatment resistance mechanisms in glioblastoma. Using a targeted screen of clinically relevant small molecules, we identify the ATM kinase inhibitor, AZD1390, as a potent dual HR/MMEJ inhibitor. Mechanistic studies in GBM cell lines show that AZD1390 suppresses DSB end resection and blocks radiation-induced phosphorylation of DSBR proteins including nibrin, Rad50, and Mettl16. Interestingly, AZD1390 enhances the cytotoxic effects of TMZ and radiation in both treatment-naïve and treatment-resistant GBM samples harboring mutations in the TP53 gene. We show that TP53 mutation is associated with upregulation of ATM pathway genes in GBM patient samples along with heightened ATM-dependent HR and MMEJ in GBM cell lines. Finally, we show that TP53-mutant GBMs fail to arrest in G2 phase after radiation/AZD1390 or TMZ/AZD1390 combinations and instead attempt mitosis, leading to mitotic cell death. Expression of the mitotic DSBR factor, RHINO1, is associated with poor prognosis in patients with TP53-mutant GBMs, suggesting that factors that promote efficient mitotic DSBR protect TP53-mutant GBMs from treatment-induced cell death. This report identifies ATM-dependent HR and MMEJ as targetable resistance mechanisms in TP53-mutant GBM and establishes ATM inhibition as a potential strategy for overcoming intrinsic and acquired treatment resistance in TP53-mutant GBMs. Citation Format: Daniel J Laverty, Shiv Gupta, Gary Bradshaw, Jiajia Chen, Brett L Carlson, Nery Matias Calmo, Shulan Tian, Jann N Sarkaria, Zachary D Nagel. ATM inhibitors exploit checkpoint defects and ATM-dependent double strand break repair to induce mitotic cell death in TP53-mutant glioblastoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Functional and Genomic Precision Medicine in Cancer: Different Perspectives, Common Goals; 2025 Mar 11-13; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(5 Suppl):Abstract nr A011.

Abstract Purpose To evaluate the test–retest repeatability of a rapid, free‐breathing two‐dimensional (2D) MR elastography (MRE) technique and to assess the reliability of the liver‐stiffness measurements compared with conventional breath‐hold MREs. Methods Fifteen and 115 participants were enrolled in the technical repeatability and measurement equivalence assessment cohorts, respectively. All participants underwent rapid free‐breathing and conventional breath‐hold 2D MRE (twice in repeatability cohort) on 1.5T scanners. Both methods have four phase offsets over one harmonic motion cycle at 60 Hz; one and 10 cycles were collected and processed in breath‐hold and free‐breathing MREs, respectively. The liver stiffness measurements of free‐breathing (LS F ) and breath‐hold MRE (LS B ) were calculated from manually drawn regions of interest. The repeatability coefficients and Spearman correlation were used to assess technical repeatability and measurement agreement between LS F and LS B . Univariable and multivariable linear regressions were performed to identify potential influencing factors, including age, sex, body mass index, and fat fraction, in the measurement agreement between LS B and LS F . Results The repeatability coefficient of free‐breathing 2D MRE is comparable to breath‐hold MRE (LS F : 20.8%, LS B : 20.4%). LS F showed a strong agreement and significant correlation with LS B (LS F = 1.01 × LS B , ρ = 0.94, p < 0.001). The measurement agreement between LS F and LS B was only significantly affected by sex ( p = 0.047) after adjusting for confounding factors of age, body mass index, and fat fraction. Conclusions The nongated, free‐breathing, multislice 2D MRE technique can provide reliable liver stiffness measurements compared with conventional breath‐hold 2D MRE. It could provide a comfortable alternative method with reliable liver stiffness measurements for patients who have difficulty in suspending respiration.

ABSTRACTAnetumab ravtansine, like other ADC drugs, has high inter‐patient variability in its pharmacokinetic (PK) and pharmacodynamic (PD) outcomes, which raises concerns about whether current dosing regimens are optimal for patients. The objective of this study was to evaluate covariates, especially body habitus and the innate immune system (IIS), which may affect anetumab ravtansine PK and PD as part of two clinical trials in patients with ovarian cancer and mesothelioma. Biomarkers of Fcγ receptors(FcγR) CD64 on IIS cells, total body weight (TBW), body surface area (BSA), and other covariates, such as sex and age, were analyzed for an association with anetumab ravtansine PK. Higher FcγR CD64, TBW, and BSA were associated with higher clearance (CL) of anetumab ravtansine (p < 0.05). However, there was no relationship between TBW or BSA and FcγR CD64. Female patients had a lower anetumab ravtansine CL (0.030 ± 0.007 L/h) compared to male patients (0.042 ± 0.006 L/h) (p < 0.05). In both studies, patients with stable disease (SD) and partial response (PR) had higher anetumab ravtansine AUC0‐inf compared to patients with progressive disease (PD). Individualizing the dose of anetumab ravtansine and potentially other ADCs based only on TBW is not optimal, whereas precision dosing of an ADC based on the inclusion of novel metrics of IIS biomarkers, body habitus, and sex may be more appropriate to reduce variability in PK exposure, reduce toxicity, and improve response.

Abstract Introduction COVID-19, a global health crisis, prompted rapid vaccine development. Bivalent vaccines by Pfizer-BioNTech and Moderna target both original and Omicron strains. Despite vaccination efforts, the persistence of adverse events underscores the importance of ongoing safety monitoring. Method We collected COVID-19 bivalent vaccine adverse event reports from the Vaccine Adverse Event Reporting System (VAERS) (September 15, 2022, to September 1, 2023). The Medical Dictionary for Regulatory Activities (MedDRA) categorized reported symptoms into corresponding concepts. Statistical analyses included zero-truncated Poisson regression for estimating symptom rates, logistic regression for identifying risk factors, and Spearman correlation for assessing non-parametric relationships between adverse events in different System Organ Classes (SOCs). Results Our analysis of COVID-19 bivalent vaccine adverse events identified significant correlations between SOCs. Notably, a positive correlation (ρ = 0.3) linked Infections (SOC 1) with Respiratory disorders (SOC 13), while a negative correlation (ρ=-0.3) connected Investigations (SOC 23) with Injury (SOC 24). Zero-truncated Poisson modeling estimated an average of 6.179 symptoms per individual, varying by age, gender, and vaccine. Gender and age significantly influence reported adverse events associated with COVID-19 bivalent vaccines. Females generally experienced higher odds for most SOCs compared to males, except for cardiac and product-related issues. Older adults showed a higher likelihood of symptoms across various SOCs, while children and adolescents had distinct susceptibility patterns. Additionally, Moderna and Pfizer vaccines were associated with different SOCs, with Moderna linked mainly to immune and skin disorders and Pfizer associated primarily with cardiac and metabolic issues. Conclusion In conclusion, our study aligned self-reported items with widely-accepted medical terminology and rigorously analyzed adverse events following COVID-19 bivalent vaccine using advanced statistical methods. The significant findings provide crucial insights, guiding evidence-based strategies and interventions for vaccine safety.

We describe the design and results from the BraTS 2023 Intracranial Meningioma Segmentation Challenge. The BraTS Meningioma Challenge differed from prior BraTS Glioma challenges in that it focused on meningiomas, which are typically benign extra-axial tumors with diverse radiologic and anatomical presentation and a propensity for multiplicity. Nine participating teams each developed deep-learning automated segmentation models using image data from the largest multi-institutional systematically expert annotated multilabel multi-sequence meningioma MRI dataset to date, which included 1000 training set cases, 141 validation set cases, and 283 hidden test set cases. Each case included T2, FLAIR, T1, and T1Gd brain MRI sequences with associated tumor compartment labels delineating enhancing tumor, non-enhancing tumor, and surrounding non-enhancing FLAIR hyperintensity. Participant automated segmentation models were evaluated and ranked based on a scoring system evaluating lesion-wise metrics including dice similarity coefficient (DSC) and 95% Hausdorff Distance. The top ranked team had a lesion-wise median dice similarity coefficient (DSC) of 0.976, 0.976, and 0.964 for enhancing tumor, tumor core, and whole tumor, respectively and a corresponding average DSC of 0.899, 0.904, and 0.871, respectively. These results serve as state-of-the-art benchmarks for future pre-operative meningioma automated segmentation algorithms. Additionally, we found that 1286 of 1424 cases (90.3%) had at least 1 compartment voxel abutting the edge of the skull-stripped image edge, which requires further investigation into optimal pre-processing face anonymization steps.

Peroxisomes are vital but often overlooked metabolic organelles. We found that excessive interferon signaling remodeled macrophage peroxisomes. This loss of peroxisomes impaired inflammation resolution and lung repair during severe respiratory viral infections. Peroxisomes were found to modulate lipid metabolism and mitochondrial health in a macrophage type-specific manner and enhanced alveolar macrophage-mediated tissue repair and alveolar regeneration after viral infection. Peroxisomes also prevented excessive macrophage inflammasome activation and IL-1β release, limiting accumulation of KRT8 high dysplastic epithelial progenitors following viral injury. Pharmacologically enhancing peroxisome biogenesis mitigated both acute symptoms and post-acute sequelae of COVID-19 (PASC) in animal models. Thus, macrophage peroxisome dysfunction contributes to chronic lung pathology and fibrosis after severe acute respiratory syndrome coronavirus 2 infection.

Importance High-quality evidence regarding suppressive valacyclovir treatment in herpes zoster ophthalmicus (HZO) is necessary to guide care. Objective To determine whether suppressive valacyclovir compared with placebo delays the occurrence of new or worsening stromal keratitis (SK), endothelial keratitis (EK), iritis, or dendriform epithelial keratitis (DEK) during 12 months of treatment and if treatment benefit persisted at 18 months (secondary end point). Design, Setting, and Participants The Zoster Eye Disease Study (ZEDS) was a randomized clinical trial conducted in 95 sites from November 2017 to June 2024. Immunocompetent, nonpregnant adults with a history of an HZO rash, documented active keratitis or iritis within 1 year, and an estimated glomerular filtration rate of 45 mL/min/1.73 m 2 or greater were eligible. After determined to be eligible, participants were randomized in 4 strata: age at onset (&amp;lt;60 years vs ≥60 years) and disease duration (&amp;lt;6 months vs ≥6 months). Interventions A total of 12 months of double-masked daily valacyclovir, 1000 mg, or placebo. Main Outcomes and Measures The primary outcome was time to first occurrence within 12 months of new or worsening SK, EK, iritis, or DEK. Results A total of 527 participants (median [IQR] age, 60 [50-68] years; 266 female [50.5%]; 266 in the valacyclovir group; 261 in the placebo group) were randomized in 4 strata; 481 completed 12 months, and 460 completed 18 months. Data were analyzed by intention to treat. At 12 months, primary end points occurred in 86 participants (33%) assigned to placebo and 74 (28%) assigned to valacyclovir, and at 18 months in 104 participants (40%) assigned to placebo and 86 (32%) assigned to valacyclovir. The hazard ratio (HR) of the primary end point at 12 months was 0.77 for participants taking valacyclovir vs placebo (HR, 0.77; adjusted 95% CI, 0.56-1.05; P = .09) and 0.73 at the secondary end point at 18 months (HR, 0.73; adjusted 95% CI, 0.55-0.97; P = .03). There was a reduction of multiple other secondary end points at 12 months (HR, 0.70; 95% CI, 0.52-0.95; P = .02) and 18 months (HR, 0.72; 95% CI, 0.55-0.95; P = .02). Conclusions and Relevance Although the primary outcome did not show a benefit of suppressive valacyclovir treatment, secondary study outcomes showed treatment superiority at the 18-month end point and reduced number of multiple episodes of keratitis or iritis at both 12 and 18 months. These results support consideration of 1 year of suppressive valacyclovir treatment for HZO. Trial Registration ClinicalTrials.gov Identifier: NCT03134196