NOS2 (iNOS) Deficiency in Kidney Donor Accelerates Allograft Loss in a Murine Model
Bibliographic record
Abstract
Renal NOS2 is expressed and produces abundant nitric oxide (NO) in various renal cells in response to proinflammatory cytokines. However, the role of this enzyme in renal allograft survival remains unknown. Kidney allotransplantation was performed in the murine model of C57BL/6J (H-2(d)) to nephrectomized Balb/c (H-2(b)) mice. Here we show that deficiency in NOS2 expression in kidney donors significantly advanced allograft failure, indicated by decreasing mean survival of recipients receiving NOS2 null grafts (15.4 +/- 6.4 days) as compared to those with wild type grafts (65.4 +/- 28.1 days) (p = 0.0005). Consistent with survival results, NOS2 null grafts had more severe renal tubule injury and decreased renal function compared to wild type grafts. In vitro NOS2 expressing TEC had greater resistance to allogeneic lymphocyte-mediated apoptosis. The addition of exogenous NO inhibited Fas-mediated TEC apoptosis and reduced proliferation of allogeneic lymphocytes. These data suggest that endogenous production of NO through renal NOS2 activity can play a protective role in kidney grafts through attenuating Fas-mediated donor cell apoptosis as well as by inhibiting proliferation of inflammatory infiltrating lymphocytes. Enhanced donor NOS2 expression may be a useful strategy to improve kidney transplant 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) | 0.001 | 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".