Descriptive vs mechanistic scientific approach to study wound healing and its inhibition: Is there a value of translational research involving human subjects?
The clinical field of wound healing is challenged by numerous hurdles. Not only are wound healing disorders complex and multifactorial, but the corresponding patient population is diverse, often elderly and burdened by multiple comorbidities such as diabetes, cardiovascular disease, etc. The care of such patients requires a dedicated, multi-disciplinary team of physicians, surgeons, nurses, and scientists. In spite of the critical clinical need, it has been over 15 years since a treatment received approval for efficacy by the FDA in the United States. Among the reasons contributing to this lack of effective new treatment modalities is poor understanding of mechanisms that inhibit healing in patients. Additionally, pre-clinical models do not fully reflect the disease complexity of the human condition, which brings us to a paradox: if we are to use a "mechanistic" approach that favors animal models, we can dissect specific mechanisms using advanced genetic, molecular, and cellular technologies, with the caveat that it may not be directly applicable to patients. Traditionally, scientific review panels, for either grant funding or manuscript publication purposes, favor such "mechanistic" approaches whereby human tissue analyses, deemed "descriptive" science, is characterized as a "fishing expedition" and is considered "fatally flawed". However, more emerging evidence supports the notion that the use of human samples provides significant new knowledge regarding the molecular and cellular mechanisms that control wound healing and contribute to inhibition of the process in patients. Here we discuss the advances, benefits, and challenges of translational research in wound healing focusing on human subject research. This article is protected by copyright. All rights reserved.
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 July 2018.
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#19,869,877
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#41
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