The Cardiovascular Area research team is made up of the Scientific Director, Francisco Miguel Sánchez Margallo, the Coordinator of the Area, Verónica Crisóstomo Ayala, and other researchers, including Claudia Báez, who, along with the Coordinator, have been invited to co-edit the collection of video articles for JOVE.
This research team is affiliated to the Centro de Investigación Biomédica en Red Cardiovascular (CIBER-CV), dependent on the Instituto de Salud Carlos III and is part of the 40 research groups selected on the basis of their scientific excellence.
Have you ever tried to reproduce a methodology you have only read about on a paper? When we try it, we normally end up wishing we could see how the authors actually do it.
To date, very few Journals are available to accept video articles for submission/publication in our field, despite this type of articles being of paramount importance in translational cardiovascular research in order to share new techniques and approaches.
For this reason, we decided to start a Collection entitled Large Animal Models of Cardiovascular Disease, from Training to Translation on JoVE, whose purpose is to offer a comprehensive overview and a visual guide to how successfully reproduce cardiovascular disease models in large animals with the ultimate aim of bridging the gap from bench to bedside.
The Journal is currently indexed in the major databases, including PubMed, EMBASE, Scopus and Web of Science. The most recent Impact Factor for JoVE (ISSN 1940-087X) is 1.163 in JCR.
JoVE’s team takes care of the entire process of filming and producing the video: after submission, each manuscript will be editorially and peer reviewed, which is typically a 1-2 month process. Once a text article passes review, a script will be generated. Generally, a filming date will be scheduled within 4-8 weeks after acceptance. A videographer will be sent to the authors’ site to film the procedure.
If interested, please contact by email crisosto@ccmijesususon.com or cbaez@ccmijesususon.com or submit the abstract here: https://www.jove.com/methods-collections/1004
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