Ocular inflammation in HLA-B27 transgenic mice reveals a potential role for MHC class I in corneal immune privilege.
Bibliographic record
Abstract
PURPOSE: HLA-B27 is a major histocompatibility complex class I (MHCI) allele that has been closely associated with the development of ankylosing spondylitis and acute anterior uveitis (AAU), the most common form of uveitis worldwide. We have been characterizing the phenotypes of transgenic mice carrying a human HLA-B27 allele, but that are deficient in endogenous mouse MHCI genes (H-2K(-/-) and H-2D(-/-) double knockout, or DKO) to create the HLA-B27/DKO line. In maintaining and expanding this colony, we observed a rare sporadic severe central keratitis that developed in transgenic animals, but that was not present in wild-type (WT) animals. METHODS: The corneas of affected HLA-B27/DKO and DKO mice were compared to their WT counterparts by staining with standard histological methods for markers of inflammation and neovascularization. A model of experimental corneal inflammation was subsequently used to test the responses of each genotype to insult. RESULTS: We identified a previously unreported corneal pathology in naïve HLA-B27/DKO mice, and we describe significantly prolonged CD4(+)- and CD8(+)-associated inflammation in these animals following an experimentally induced corneal injury. CONCLUSIONS: These results demonstrate an increased T-cell response in B27/DKO corneas due to the expression of the HLA-B27 allele, suggesting that low MHCI expression in WT corneas is an important contributor to immune privilege.
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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) | 0.000 | 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) | 0.003 | 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".