ArticleProceedings of the National Academy of Sciences of the United States of America2024
Logic-based mechanistic machine learning on high-content images reveals how drugs differentially regulate cardiac fibroblasts.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 22 citations in OpenAlex.
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- AI-based Predictive Signaling Pathway Profiling in Cardiac Fibrosis Suggests a Novel Combinatorial Treatment Strategy.bioRxiv : the preprint server for biology · 2025Article
- Rewiring the scar: translational advances in cardiac fibrosis.The Korean journal of physiology & pharmacology : official journal of the Korean Physiological Society and the Korean Society of Pharmacology · 2025Review
- Determining sex differences in aortic valve myofibroblast responses to drug combinations identified using a digital medicine platform.Science advances · 2025Article
- Dressed in Collagen: 2D and 3D Cardiac Fibrosis Models.International journal of molecular sciences · 2025Review
- Logic-based machine learning predicts how escitalopram attenuates cardiomyocyte hypertrophy.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Secreted Cytokines From Inflammatory Macrophages Modulate Sex Differences in Valvular Interstitial Cells on Hydrogel Biomaterials.Journal of biomedical materials research. Part A · 2025Article
- State of the ART: Drug Screening Reveals Artesunate as a Promising Anti-Fibrosis Therapy.Journal of respiratory biology and translational medicine · 2025Article
- Multiscale computational model predicts how environmental changes and treatments affect microvascular remodeling in fibrotic disease.PNAS nexus · 2025Article
- Natural products for anti-fibrotic therapy in idiopathic pulmonary fibrosis: marine and terrestrial insights.Frontiers in pharmacology · 2025Review
- Advances in induced pluripotent stem cell-derived cardiac myocytes: technological breakthroughs, key discoveries and new applications.The Journal of physiology · 2024Review
- Guidelines for mechanistic modeling and analysis in cardiovascular research.American journal of physiology. Heart and circulatory physiology · 2024Review
- Modular Multiwell Viscoelastic Hydrogel Platform for Two- and Three-Dimensional Cell Culture Applications.ACS biomaterials science & engineering · 2024Article
- Multiscale computational model predicts how environmental changes and drug treatments affect microvascular remodeling in fibrotic disease.bioRxiv : the preprint server for biology · 2024Article
- Modular multiwell viscoelastic hydrogel platform for two- and three-dimensional cell culture applications.bioRxiv : the preprint server for biology · 2023Article
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4 authors at 2 institutions in 1 country.
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Abstract
Fibroblasts are essential regulators of extracellular matrix deposition following cardiac injury. These cells exhibit highly plastic responses in phenotype during fibrosis in response to environmental stimuli. Here, we test whether and how candidate anti-fibrotic drugs differentially regulate measures of cardiac fibroblast phenotype, which may help identify treatments for cardiac fibrosis. We conducted a high-content microscopy screen of human cardiac fibroblasts treated with 13 clinically relevant drugs in the context of TGFβ and/or IL-1β, measuring phenotype across 137 single-cell features. We used the phenotypic data from our high-content imaging to train a logic-based mechanistic machine learning model (LogiMML) for fibroblast signaling. The model predicted how pirfenidone and Src inhibitor WH-4-023 reduce actin filament assembly and actin-myosin stress fiber formation, respectively. Validating the LogiMML model prediction that PI3K partially mediates the effects of Src inhibition, we found that PI3K inhibition reduces actin-myosin stress fiber formation and procollagen I production in human cardiac fibroblasts. In this study, we establish a modeling approach combining the strengths of logic-based network models and regularized regression models. We apply this approach to predict mechanisms that mediate the differential effects of drugs on fibroblasts, revealing Src inhibition acting via PI3K as a potential therapy for cardiac fibrosis.
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