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Updated: Dec 30, 2025

Behavioral Phenotyping of Murine Disease Models with the Integrated Behavioral Station INBEST
Published on: April 23, 2015
Sickness Behavior Score Is Associated with Neuroinflammation and Late Behavioral Changes in Polymicrobial Sepsis
Mariana Pereira de Souza Goldim1, Amanda Della Giustina1, Khiany Mathias1
1Laboratory of Neurobiology of Inflammatory and Metabolic Processes (NEUROIMet), Graduate Program in Health Sciences, University of South Santa Catarina, Tubarão, SC, Brazil.
Abstract:
The use of reliable scores is a constant development in critical illness. According to Sepsis-3 consensus, the use of Sequential Organ Failure Assessment (SOFA) score of 2 or more is associated with a higher mortality of sepsis patients. In experimental research, due murine animal model limitations, the use of a score systems can be an alternative to assess sepsis severity. In this work, we suggest a sickness behavior score (SBS) that uses physiological variables to assess sepsis severity and mortality. Animals were evaluated daily by the presence of six indicators of sickness behavior: temperature alteration, preference of water/sucrose, liquid intake, food intake, body weight, and movimentation. Male adult Wistar rats were evaluated daily after sepsis induction by cecal ligation and puncture (CLP) or laparotomy only (sham) for determination of SBS. Oxidative stress, IL-6, and HPA axis markers (corticosterone and adrenal gland weight) were evaluated 24 h after CLP to determine the correlation with the acute SBS and neuroinflammation. Also, BDNF and four cognitive behavioral tests were correlated with the chronic SBS, i.e., sum of 8 days after surgery. In result, septic rats presented higher SBS than sham animals. Sepsis severity markers were associated with acute and chronic SBS. Also, SBS was negative correlated with the cognitive tests. In conclusion, SBS shows to be reliable score to predict sepsis severity and mortality. The use of score system provides the analysis of global sickness behavior, beyond evaluation of each parameter individually.

