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Verônica Assalin Zorgetto-Pinheiro
Federal University of Mato Grosso do Sul (UFMS)
Author
Alexandre Meira de Vasconcelos
Federal University of Mato Grosso do Sul (UFMS)
Author
Rafael Sanaiotte Pinheiro
Federal University of Mato Grosso do Sul (UFMS)
Author
Danielle Bogo
Federal University of Mato Grosso do Sul (UFMS)
Author
Iandara Schettert Silva
Federal University of Mato Grosso do Sul (UFMS)
Author
Rheumatoid arthritis is an autoimmune and chronic pathological condition characterized by an inflammatory process of the joints It is a complex and multifactorial, involving genetic, epigenetic and environmental factors and the use of experimental models is required to better understand its pathology and for drug testing. The aim of this study was to perform a systematic literature review on experimental models in rheumatoid arthritis using IRAMUTEQ, a software that analysis, qualitatively and quantitatively, text fragments, as a methodological tool. After searching for articles published in the last five years on Scopus database and applying the exclusion criteria, we ended with 84 articles. The most commonly employed experimental models was the arthritis induction by inoculation of the Complete Freund's Adjuvant (CFA), followed by the use of combined methodologies and the collagen-induced arthritis (CIA). The analyses of abstracts by the IRAMUTEQ software provided a classification according to their textual elements in four classes, which were grouped into three main themes: in vivo models (class 1), clinical practice and traditional medicine (classes 2 and 3) and in vitro models (class 4) and it was also possible to build a similarity tree of the terms present in the abstracts and a word cloud with the most cited terms. Thus, the use of the IRAMUTEQ software as a methodological tool has been satisfactory, since it was possible to identify the main experimental models used, keywords, pathological processes and molecules involved in the pathogenesis of rheumatoid arthritis free of the researchers’ bias, in addition to being a tool for visual and intuitive results.
Copyright (c) 2020 Verônica Assalin Zorgetto-Pinheiro, Alexandre Meira de Vasconcelos, Rafael Sanaiotte Pinheiro, Danielle Bogo, Iandara Schettert Silva

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