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Current Status and Limitations of Myocardial Infarction Large Animal Models in Cardiovascular Translational Research

Establishing an appropriate disease model that mimics the complexities of human cardiovascular disease is critical for evaluating the clinical efficacy and translation success. The multifaceted and complex nature of human ischemic heart disease is difficult to recapitulate in animal models. This dif...

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Detalles Bibliográficos
Autores principales: Shin, Hye Sook, Shin, Heather Hyeyoon, Shudo, Yasuhiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8116580/
https://www.ncbi.nlm.nih.gov/pubmed/33996785
http://dx.doi.org/10.3389/fbioe.2021.673683
Descripción
Sumario:Establishing an appropriate disease model that mimics the complexities of human cardiovascular disease is critical for evaluating the clinical efficacy and translation success. The multifaceted and complex nature of human ischemic heart disease is difficult to recapitulate in animal models. This difficulty is often compounded by the methodological biases introduced in animal studies. Considerable variations across animal species, modifications made in surgical procedures, and inadequate randomization, sample size calculation, blinding, and heterogeneity of animal models used often produce preclinical cardiovascular research that looks promising but is irreproducible and not translatable. Moreover, many published papers are not transparent enough for other investigators to verify the feasibility of the studies and the therapeutics’ efficacy. Unfortunately, successful translation of these innovative therapies in such a closed and biased research is difficult. This review discusses some challenges in current preclinical myocardial infarction research, focusing on the following three major inhibitors for its successful translation: Inappropriate disease model, frequent modifications to surgical procedures, and insufficient reporting transparency.