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• W4213191698 endingPage "121421" @default.
• W4213191698 startingPage "121421" @default.
• W4213191698 abstract "Autologous cardiac cell therapy is a promising treatment for combating the right ventricular heart failure (RVHF) that can occur in patients with congenital heart disease (CHD). However, autologous cell therapies suffer from low cell retention following injection and patient-to-patient variability in cell quality. Here, we demonstrate how computational methods can be used to identify mechanisms of cardiac-derived c-Kit+ cell (CPC) reparative capacity and how biomaterials can be designed to improve cardiac patch performance by engaging these mechanisms. Computational modeling revealed the integrin subunit αV (ITGAV) as an important mediator of repair in CPCs with inherently low reparative capacity (CPCslow). We could engage ITGAV on the cell surface and improve reparative capacity by culturing CPCs on electrospun polycaprolactone (PCL) patches coated with fibronectin (PCL + FN). We tested CPCs from 4 different donors and found that only CPCslow with high ITGAV expression (patient 956) had improved anti-fibrotic and pro-angiogenic paracrine secretion on PCL + FN patches. Further, knockdown of ITGAV via siRNA led to loss of this improved paracrine secretion in patient 956 on PCL + FN patches. When implanted in rat model of RVHF, only PCL + FN + 956 patches were able to improve RV function, while PCL +956 patches did not. In total, we demonstrate how cardiac patches can be designed in a patient-specific manner to improve in vitro and in vivo outcomes." @default.
• W4213191698 created "2022-02-24" @default.
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• W4213191698 date "2022-04-01" @default.
• W4213191698 modified "2023-10-14" @default.
• W4213191698 title "Using computational methods to design patient-specific electrospun cardiac patches for pediatric heart failure" @default.
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• W4213191698 doi "https://doi.org/10.1016/j.biomaterials.2022.121421" @default.
• W4213191698 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35219147" @default.
• W4213191698 hasPublicationYear "2022" @default.
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