Heterogeneity in the Evolution and Mechanisms of the Lesions of Kidney Allograft Rejection in Mice
Bibliographic record
Abstract
The natural history and pathogenesis of the pathologic lesions that define rejection of kidney transplants have not been well characterized. We studied the evolution of the pathology of rejection in mouse kidney allografts, using four strain combinations across full major histocompatibility complex (MHC) plus nonMHC disparities, to permit more general conclusions. Interstitial infiltrate, MHC induction, and venulitis appeared by day 5, peaked at day 7-10, then stabilized or regressed by day 21. In contrast, tubulitis, arteritis, and glomerulitis were absent or mild at days 5 and 7, but progressed through day 21, indicating separate regulation and homeostatic control of these lesions. Edema, hemorrhage, and necrosis also increased through day 21. All lesions were T-dependent, failing to develop in T-cell-deficient hosts. Allografts into immunoglobulin-deficient hosts manifested typical infiltration, MHC induction, and tubulitis at days 7 and 21, indicating that these lesions are alloantibody-independent. However at day 21 kidneys rejecting in immunoglobulin-deficient hosts showed decreased edema, arteritis, venulitis, and necrosis. Thus the three groups of lesions are: T-cell-mediated interstitial infiltration, MHC induction, and venulitis, which develops rapidly then stabilizes; slower but progressive T-cell-mediated tubulitis and arteritis; and late antibody-mediated endothelial injury, which contributes to late edema, arteritis, and venulitis.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".