Glial fibrillary acidic protein and ionized calcium-binding adapter molecule 1 immunostaining score for the central nervous system of horses with non-suppurative encephalitis and encephalopathies

• Autor(a) principal: Boos, Gisele Silva
• Data de Publicação: 2021
• Outros Autores: Failing, Klaus 1954-, Colodel, Edson Moleta, Driemeier, David, Castro, Márcio Botelho de, Bassuino, Daniele Mariath, Barbosa Neto, Jose Diomedes, Herden, Christiane
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFRGS
• Texto Completo: http://hdl.handle.net/10183/225543
• topic: Microglia; Astrócitos; Biomarcadores; Imunohistoquímica; Doencas do sistema nervoso central; Equinos; Microglia; Astrocytes; Score system; Etiology; Infectious; Degenerative

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.