Colony-Specific Differences in Endocrine and Immune Responses to an Inflammatory Challenge in Female Sprague Dawley Rats
Bibliographic record
Abstract
Sprague Dawley rats from different vendor colonies display divergent responses in a variety of experimental paradigms. An adjuvant-induced arthritis (AA) model of human rheumatoid arthritis was used to examine immune and endocrine responses to inflammatory challenge in Sprague Dawley rats from Charles River and Harlan colonies. Rats were injected with either complete Freund's adjuvant or physiological saline (control), weights, and paw volumes measured over 15 days, and blood and tissue were collected 16 days post-injection. Overall, Harlan rats developed more severe AA than Charles River rats. In addition, despite comparable corticosterone levels, corticosteroid binding globulin levels were lower in Harlan compared with Charles River rats in the absence of inflammation, suggesting that a lower corticosterone reservoir in Harlan rats may underlie their greater susceptibility to inflammation. With increasing AA severity, there was an increase in plasma corticosterone (total and free) and a decrease in corticosteroid binding globulin in both Charles River and Harlan rats. However, contrasting patterns of cytokine activation were observed in the hind paw, suggesting a reliance on different cytokine networks at different stages of inflammation, with Charles River rats exhibiting increased TNF-α, monocyte chemotactic protein-1 (MCP-1), keratinocyte chemoattractant/growth-regulated oncogene (KC/GRO), and IL-1β in the absence of clinical signs of arthritis, whereas Harlan had increased TNF-α, monocyte chemotactic protein-1, and IL-6 with mild to moderate arthritis. These colony-specific differences in endocrine and immune responses to AA in Sprague Dawley rats must be considered when comparing data from different laboratories and could be exploited to provide insight into physiological changes and therapeutic outcomes in arthritis and other inflammatory disorders.
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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 | 0.001 |
| 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 | 0.001 |
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".