ArticleScience advances2025
Determining sex differences in aortic valve myofibroblast responses to drug combinations identified using a digital medicine platform.
Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Addressing antimicrobial resistance: Current challenges, emerging strategies, and an AI-powered, community-driven approach.PNAS nexus · 2026Review
- Aortic valve stenosis serum IGFBP2 mediates female-specific Evogliptin resistance in valve myofibroblasts.Cell reports · 2026Article
- Spatial and Single-Cell Mapping Reveals Valvular Interstitial Cell and Macrophage Sex Differences in Calcific Aortic Valve Disease.Arteriosclerosis, thrombosis, and vascular biology · 2026Article
- Optimizing drug combinations to resurrect the potency of failed antibody therapy against emerging COVID-19 variants using IDentif.AI.Frontiers in digital health · 2026Article
- The double-edged sword effect of estrogen in kidney disease and its precision modulation.Frontiers in endocrinology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Aortic valve stenosis (AVS) is a sexually dimorphic disease where aortic valve leaflets develop fibrosis and calcification, leading to heart failure if untreated. Sex differences in AVS progression depend on valvular interstitial cells (VICs) activating to myofibroblasts that drive aberrant extracellular matrix remodeling. To date, no treatment strategies have leveraged cellular sex differences to determine drug combinations that target VIC myofibroblast activation. Here, we harnessed IDentif.AI, an artificial intelligence (AI)-derived platform, to optimize sex-biased synergistic drug combinations that may prevent and reverse VIC myofibroblast activation on hydrogel biomaterials. The results reveal that sex-specific drug response models can be used to predict sex biases in drug efficacy and combinatorial interactions. This study provides a framework for developing AVS treatments through the integration of high-throughput hydrogel cell culture platforms and AI-driven drug optimization. Designing targeted AVS drug combinations may help accelerate AVS drug development and address health disparities in AVS treatment outcomes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.