Two mouse mutations mapped to chromosome 11 with differing morphologies but similar progressive inflammatory alopecia
Bibliographic record
Abstract
Abstract: Alopecia is a common dermatological condition in humans and other mammals. Here, we present two similar but histologically distinct mouse models of scarring alopecia. Both mutant lines were generated using random genome-wide N-ethyl-N-nitrosourea mutagenesis, and both harbor dominant mutations on chromosome 11. In both mutants, there is an early onset of alopecia that progresses to nearly complete pelage hair loss in both males and females by 20 weeks of age. Histologically, there is an increased dermal cellularity due to inflammatory cell infiltration at 7–10 days of age. By 3 weeks of age, the epidermis is acanthotic and the dermis is approximately twice as thick as in control mice due to a substantial, mostly mononuclear, inflammatory cell infiltrate. This infiltrate becomes more perifollicular by 4–5 weeks of age but is localized differently in the two mutants. In alopecia 1 (Alo-1), the perifollicular infiltrate is confined to the portion of the follicle within the dermis, whereas in Alo-2, the infiltrate extends the full length of the follicle. Expression of major histocompatibility complex (MHC) class I on the follicular epithelium in the two mutants is much greater than that in non-mutants. Furthermore, MHC class I expression is localized differently in the two mutant lines and mirrors the pattern of the inflammatory infiltrate. Despite these differences, the clinical progression of alopecia is identical in both mutants. The early onset of the disease, predictable progression, and differences in inflammatory cell localization between the two mutants make these mice particularly useful models for inflammatory hair loss and autoimmune diseases in general.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".