Strain Differences and Effects of Environmental Manipulation on Astrocytes (Glial Fibrillary Acidic Protein), Glucocorticoid Receptor, and Microglia (Iba1) Immunoreactivity between Wistar-Kyoto and Wistar Females
Bibliographic record
Abstract
BACKGROUND: Depression is often associated with an increase in hypothalamic-pituitary-adrenal (HPA) axis reactivity and immune response. To investigate this relationship, we examined the consequences of environmental manipulation on the neural correlates of the HPA axis and immune response in an animal model of depression, the Wistar-Kyoto (WKY) rat. Additionally, female animals are often overlooked in preclinical research because of the hormone fluctuations inherent in the estrous cycle. METHODS: Female rats were randomly assigned to 1 of 3 environments for 30 days: (1) environmental enrichment (EE), (2) standard housing (SH), and (3) isolated housing (IH). Immunoreactivity of astrocytes (glial fibrillary acidic protein [GFAP]), glucocorticoid receptors (GRs), and microglia (Iba1) in the hippocampus and amygdala were measured using immunohistochemistry. RESULTS: WKY animals had significantly more GR staining area and Iba1 staining intensity and area in the CA1 of the hippocampus. In enriched Wistar rats, GFAP staining intensity and area were greater in the CA1. A trend towards a greater percent of area stained with GR was found in WKY animals as compared to that of the Wistar animals. This was due to WKY females in EE having significantly higher GR staining intensity and area in the amygdala as compared to that of animals in SH. DISCUSSION: These strain differences lend support to the use of WKY animals as an animal model of depression. Furthermore, due to the effects of EE on GFAP and GR staining in WKY females, we suggest that EE can be used as an intervention to potentially alleviate the negative effects of depression.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".