Serine Protease Inhibitor-6 Inhibits Granzyme B–Mediated Injury of Renal Tubular Cells and Promotes Renal Allograft Survival
Bibliographic record
Abstract
BACKGROUND: Protease inhibitor 9 (PI-9) is an intracellular serpin that specifically inhibits granzyme B, a cytotoxic serine protease found in the cytosolic granules of cytotoxic T lymphocytes and natural killer cells. Enhanced cortical expression of PI-9 has been observed in kidney allografts with subclinical rejection, suggesting that the tubular epithelial cell (TEC) expression of this protein may have a protective role and attenuate overt allograft rejection. METHODS AND RESULTS: We demonstrate that TEC express SPI-6 protein, the murine homolog of PI-9, basally with a modest increase after cytokine exposure. Tubular epithelial cell expression of SPI-6 blocks granzyme B-mediated death because TEC from SPI-6 null kidneys have increased susceptibility to cytotoxic CD8+ cells in vitro. The role of SPI-6 was tested in a mouse kidney transplant model using SPI-6 null or wild type donor kidneys (H-2) into nephrectomized recipients (H-2). SPI-6 null kidney recipients demonstrated reduced renal function at day 8 after transplantation compared to controls (creatinine, 113±23 vs. 28±3 μmol/L; n=5; P<0.01), consistent with observed tubular injury and extensive mononuclear cell infiltration. Loss of donor kidney SPI-6 shortened graft survival time (20±19 vs. 66±33 days; n=8-10; P<0.001). CONCLUSION: Our data show for the first time that resistance of kidney TEC to cytotoxic T-cell granzyme B-induced death in vitro and in vivo is mediated by the expression of SPI-6. We suggest that SPI-6 is an important endogenous mechanism to prevent rejection injury from perforin or granzyme B effectors and enhanced PI-9 or SPI-6 expressions by TEC may provide protection from diverse forms of inflammatory kidney injury and promote long-term allograft survival.
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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 | 0.000 | 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) | 0.001 | 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".