Tubulitis and Epithelial Cell Alterations in Mouse Kidney Transplant Rejection Are Independent of CD103, Perforin or Granzymes A/B
Bibliographic record
Abstract
One of the defining lesions of kidney allograft rejection is epithelial deterioration and invasion by inflammatory cells (tubulitis). We examined epithelial changes and their relationship to effector T cells and to CD103/E-cadherin interactions in mouse kidney allografts. Rejecting allografts showed interstitial mononuclear infiltration from day 5. Loss of epithelial mass, estimated by tubular surface area, and tubulitis were minimal through day 7 and severe by day 21. Tubules in day 21 allografts manifested severe reduction of E-cadherin and Ksp-cadherin by immunostaining with redistribution to the apical membrane, indicating loss of polarity. By flow cytometry T cells isolated from allografts were 25% CD103+. Laser capture microdissection and RT-PCR showed increased CD103 mRNA in the interstitium and tubules. However, allografts in hosts lacking CD103 developed tubulitis, cadherin loss, and epithelial deterioration similar to wild-type hosts. The loss of cadherins and epithelial mass was also independent of perforin and granzymes A and B. Thus rejection is characterized by severe tubular deterioration associated with CD103+ T cells but not mediated by CD103/cadherin interactions or granzyme-perforin cytotoxic mechanisms. We suggest that alloimmune effector T cells mediate epithelial injury by contact-independent mechanisms related to delayed type hypersensitivity, followed by invasion of the altered epithelium to produce tubulitis.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".