AI Article Synopsis
- The chronic unpredictable mild stress model is a common experimental method for studying depression in rats, helping researchers understand similar human conditions.
- The study analyzed various behavioral tests and measurements, revealing that chronic stress over six weeks leads to clear signs of depression and anxiety in rats.
- The researchers identified specific combinations of behaviors that can reliably differentiate between stressed and normal rats, highlighting important relationships among different behavioral indicators.
Article Abstract
The chronic unpredictable mild stress model of depression has been widely used as an experimental tool to investigate human psychopathology. Our objective was to provide an update on the validity and reliability of the chronic unpredictable mild stress model, by analyzing the interrelationships among the indexes using stepwise discriminant analysis and Pearson correlation coefficient to examine the possible combinations. We evaluated the depressive rats in both the presence and the absence of chronic unpredictable mild stress, using weight change, percentage of sucrose preference, coat state, splash test, open-field test, elevated plus-maze test, forced swimming test, and Morris water maze test. The results showed that 6-week-long chronic unpredictable mild stress produces significant depression and anxiety-like behavior. The combination of body weight change, percentage of sucrose preference, coat state score, open-field score, grooming latency of splash test, immobility time in force swimming test, and platform crossing in the Morris water maze test can effectively discriminate between normal and chronic unpredictable mild stress rats. Strong interrelationships were noted among these indexes in both open-field test and elevated plus-maze test. In conclusion, there might be certain criteria for the combination of behavioral endpoints, which is advantageous to more effectively and reliably assess the chronic unpredictable mild stress induced depression model.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5607203 | PMC |
| http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0185129 | PLOS |
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