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A proposal of standardization for histopathological lesions to characterize fish diseases
Reviews in Aquaculture ( IF 8.8 ) Pub Date : 2020-05-07 , DOI: 10.1111/raq.12435
Alba Lucía Rey 1, 2 , Javier Asín 2, 3 , Imanol Ruiz Zarzuela 2 , Lluís Luján 2 , Carlos A. Iregui 4 , Ignacio de Blas 2
Affiliation  

The use of histopathology in fish sciences is broadly extended, although it is currently devoid of standardization across the literature. There have been initiatives to standardize every step of the histological evaluation, including description, diagnosis, interpretation, data recording and reporting, and statistical analysis, but, in general, the histopathological systems applied to date present a series of limitations that hamper the reproducibility of the derived data. On top of these limitations, an agreed, organ‐by‐organ list of lesions to be recorded is currently lacking. Therefore, this communication proposes a validated and comprehensive list of features to record in skin, head, eye, nervous system, gastrointestinal tract, gonads, kidney, and other organs of farmed red and Nile tilapias (Oreochromis sp. and Oreochromis niloticus L., respectively), white cachama (Piaractus brachypomus), rainbow trout (Oncorhynchus mykiss) and other species. Once this list is agreed and accepted by fish pathologists and other fish scientists, it could be the cornerstone for the development of well‐established and reproducible histopathological scoring systems. This communication highlights the importance of standardization initiatives in fish histology to produce reliable and high‐quality data.

中文翻译:

关于组织病理学病变以表征鱼类疾病的标准化建议

尽管目前尚无有关文献的标准化方法,但在鱼类科学中组织病理学的使用已广泛扩展。已经采取措施来标准化组织学评估的每个步骤,包括描述,诊断,解释,数据记录和报告以及统计分析,但是,总的来说,迄今为止应用的组织病理学系统存在一系列限制其可重复性的限制。派生数据。除了这些限制之外,当前还缺少一个要记录的,经过认可的器官器官清单。因此,本通讯提出了经过验证的综合功能列表,以记录在养殖的红色和尼罗罗非鱼(Oreochromis)的皮肤,头部,眼睛,神经系统,胃肠道,性腺,肾脏和其他器官中sp。和尼奥罗非鱼(Oreochromis niloticus L.),白c(Piaractus brachypomus),虹鳟(Oncorhynchus mykiss)等物种。一旦该清单被鱼类病理学家和其他鱼类科学家同意并接受,它就可能成为发展完善且可复制的组织病理学评分系统的基石。本交流强调了鱼类组织学中标准化计划对于产生可靠和高质量数据的重要性。
更新日期:2020-05-07
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