Boos Gisele Silva, Failing Klaus, Colodel Edson Moleta, Driemeier David, de Castro Márcio Botelho, Bassuino Daniele Mariath, Diomedes Barbosa José, Herden Christiane
Department of Veterinary Medicine, Institute of Veterinary Pathology, Justus-Liebig-Universität, Gießen, Germany.
Unit of Biomathematics and Data Processing, Department of Veterinary Medicine, Justus-Liebig-Universität, Gießen, Germany.
Front Vet Sci. 2021 Jul 9;8:660022. doi: 10.3389/fvets.2021.660022. eCollection 2021.
Like humans, horses are susceptible to neurotropic and neuroinvasive pathogens that are not always readily identified in histological sections. Instead, alterations in astrocytes and microglia cells can be used as pathological hallmarks of injured nervous tissue in a variety of infectious and degenerative diseases. On the other hand, equine glial cell alterations are poorly characterized in diseases. Therefore, in this study, we provide a statistically proved score system to classify astrogliosis and microgliosis in the central nervous system (CNS) of horses, based on morphological and quantitative analyses of 35 equine cases of encephalitis and/or encephalopathies and four non-altered CNS as controls. For this system, we used glial fibrillary acidic protein (GFAP) and ionized calcium-binding adapter molecule 1 (Iba1) immunohistochemistry, allied to statistical analysis to confirm that the scores were correctly designated. The scores of alterations ranged from 0 (non-altered) to 3 (severely altered) and provided a helpful method for describing astrocytic and microglial alterations in horses suffering from inflammatory and degenerative lesions. This system could be a template for comparative studies in other animal species and could aid algorithms designed for artificial intelligence methods lacking a defined morphological pattern.
与人类一样,马易受嗜神经和神经侵袭性病原体感染,而这些病原体在组织切片中并不总是容易识别。相反,星形胶质细胞和小胶质细胞的变化可作为各种感染性和退行性疾病中神经组织损伤的病理标志。另一方面,马的胶质细胞变化在疾病中的特征尚不明确。因此,在本研究中,我们基于对35例马脑炎和/或脑病病例以及4例未改变的中枢神经系统作为对照的形态学和定量分析,提供了一个经统计学验证的评分系统,用于对马中枢神经系统(CNS)中的星形胶质细胞增生和小胶质细胞增生进行分类。对于该系统,我们使用胶质纤维酸性蛋白(GFAP)和离子钙结合衔接分子1(Iba1)免疫组织化学,并结合统计分析来确认评分的正确指定。变化评分范围从0(未改变)到3(严重改变),为描述患有炎症和退行性病变的马的星形胶质细胞和小胶质细胞变化提供了一种有用的方法。该系统可为其他动物物种的比较研究提供模板,并有助于为缺乏明确形态模式的人工智能方法设计算法。