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Usage Information

Fibrosis: ultimate and proximate causes
Victor J. Thannickal, … , Amit Gaggar, Steven R. Duncan
Victor J. Thannickal, … , Amit Gaggar, Steven R. Duncan
Published November 3, 2014
Citation Information: J Clin Invest. 2014;124(11):4673-4677. https://doi.org/10.1172/JCI74368.
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Review

Fibrosis: ultimate and proximate causes

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Abstract

Fibrotic disorders account for an increasing burden of disease-associated morbidity and mortality worldwide. Although numerous risk factors have been recognized, the etiologies of many of these clinical syndromes have not been identified, and they are often termed idiopathic or cryptogenic. Here, we provide an evolutionary perspective on fibrosis aimed at elucidating its etiopathogenesis. By asking the ultimate question of “why” this process evolved in multicellular organisms, we hope to uncover proximate explanations for “how” it causes disease in humans. We posit that physiological fibrosis-like reactions evolved as an essential process in host defense against pathogens and in normal wound healing. Based on this premise, we reason that pathological fibrosis is related to one or more of the following: unidentified infectious or noninfectious antigens, autoimmunity, impaired regenerative responses, and the antagonistically pleiotropic action of genes involved in wound healing or development. The importance of genetic susceptibility, epigenetics, aging, and the modern-day environment are highlighted. Consideration of both ultimate and proximate causation goes beyond philosophical cogitations, as it will better inform pathobiological mechanisms of disease and aid in the prevention and treatment of fibrotic diseases.

Authors

Victor J. Thannickal, Yong Zhou, Amit Gaggar, Steven R. Duncan

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Usage data is cumulative from May 2024 through May 2025.

Usage JCI PMC
Text version 1,312 210
PDF 136 54
Figure 94 4
Citation downloads 99 0
Totals 1,641 268
Total Views 1,909
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Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

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