The C3H/HeJ mouse and DEBR rat models for alopecia areata: review of preclinical drug screening approaches and results
Bibliographic record
Abstract
The C3H/HeJ inbred mouse strain and the Dundee Experimental Bald Rat (DEBR) strain spontaneously develop adult onset alopecia areata (AA), a cell-mediated disease directed against actively growing hair follicles. The low frequency of AA and the inability to predict the stage of AA as it evolves in the naturally occuring C3H/HeJ model of AA can be converted into a highly predictable system by grafting full thickness skin from AA-affected mice to normal haired mice of the same strain. The rat DEBR model develops spontaneous AA at a higher frequency than in the mouse model but they are more expensive to use in drug studies owing to their larger size. Regardless of the shortcomings of either model, these rodent models can be used succesfully to screen novel or approved drugs for efficacy to treat human AA. As the pathogenesis of AA follows the canonical lymphocytic co-stimulatory cascade in the mouse AA model, it can be used to screen compounds potentially useful to treat a variety of cell-mediated diseases. Efficacy of various agents can easily be screened by simply observing the presence, rate, and cosmetic acceptability of hair regrowth. More sophisticated assays can refine how the drugs induce hair regrowth and evaluate the underlying pathogenesis of AA. Some drugs commonly used to treat human AA patients work equally as well in both rodent models validating their usefulness as models for drug efficacy and safety for humanAA.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".