Inflammation-Susceptible Lewis Rats Show Less Sensitivity Than Resistant Fischer Rats in the Formalin Inflammatory Pain Test and With Repeated Thermal Testing
Bibliographic record
Abstract
Comparisons between Lewis and Fischer inbred strains of rats are used frequently to study the effect of inherent differences in function of the hypothalamic-pituitary-adrenal axis on pain-relevant traits, including differential susceptibility to chronic inflammatory disease and differential responsiveness to analgesic drugs. Increasing use of genetic models including transgenic knockout mice and inbred strains of rodents has raised our awareness of, and the importance of, thorough characterization (or phenotyping) of the strains of rodents being compared. Furthermore, genetic variability in analgesic sensitivity is correlated with, and may be caused by, genetically determined baseline sensitivity. Thus in this study, baseline inflammatory and thermal nociceptive sensitivities were measured in awake male and female Lewis and Fischer rats to examine whether the results could explain relevant strain differences reported in the literature. The effect of maternal separation was also examined and no effect was found on nociceptive sensitivity, corticosterone responses, or the development of adjuvant-induced arthritis, a model of rheumatoid arthritis. Lewis rats and female rats were more sensitive to thermal nociception in the tail withdrawal test (mean of 3 trials) than Fischer rats and male rats, respectively. Unexpectedly, the more inflammation-susceptible Lewis rats were less sensitive in the formalin inflammatory nociception test, and showed a significant decrease in sensitivity with repeated thermal nociceptive testing, whereas Fischer rats did not. These results affect the interpretation of previously observed results. Further study of the underlying mechanisms and the relevance to differential susceptibility to chronic inflammation is warranted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".