ORAL MUCOSAL ULCER INDUCTION METHODS IN RATS: A SYSTEMATIC REVIEW

Author:

ERIS NURUL RAHMADHINI ,WAHYUNI INDAH SUASANI

Abstract

Oral mucosal ulcers are a prevalent condition, but there are still limited drugs available to treat them. Varieties of induction techniques to obtain oral mucosal ulcer models in rats have frequently been used. This systematic review aimed to describe different approaches and to recommend the most effective method for oral mucosal ulcer induction methods in rats for anti-oral mucosal ulcer drug discovery. The PRISMA guidelines were used in the framework regarding this systematic review. The electronic databases PubMed, Science Direct, SCOPUS, and EBSCOhost-CINAHL Plus were used for article searching using specific keywords. The Risk of Bias Tool from Syrcle was used to undertake the evaluation of bias risk. Based on the analysis of 14 articles, the following findings were gathered: Wistar rats were frequently used mouse strains at an average of 8 w old and weighed between 120 and 300 g. Induction methods used to obtain ulcer models were acetic acid, biopsy punch, scalpel blade, thermal, and phenol. Acetic acid induction was the most commonly used compared to the other induction techniques. The ulcers were obtained by acetic acid identical to those that occur on the human oral mucosa and available at a reasonable price. However, the ulcer formation takes longer compared with biopsy punch and scalpel blade induction. The systematic review found that there are various methods for inducing oral ulcers in rats, with acetic acid being the recommended method to produce a suitable mucosal ulcer model in rats.

Publisher

Innovare Academic Sciences Pvt Ltd

Subject

Pharmaceutical Science

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3