Renal Tubular Epithelial Cell Self-Injury Through Fas/Fas Ligand Interaction Promotes Renal Allograft Injury
Bibliographic record
Abstract
Tubular epithelial cells (TECs) coexpress Fas and Fas ligand (FasL), which could influence renal allograft injury. While TECs can resist apoptosis by Fas antibody, TEC apoptosis by contact with adjacent TECs has not been studied. Fas expression increased in TECs with cytokine treatment (IFN-gamma, TNF-alpha) while abundant FasL levels were not altered. Apoptosis (Annexin-V, DNA fragmentation) occurred in cytokine-treated TECs monolayers from C3H-HeJ mice by 24 h, but was absent in similarly treated TECs from Fas-deficient (lpr) or FasL-mutant (gld) mice, suggesting that 'self injury' occurred through Fas/FasL. Membrane labeling of TECs in cocultures confirmed that FasL-bearing TECs induced apoptosis when in contact with Fas-bearing TECs. Culturing TECs with allogeneic C57BL/6 (H-2b) splenocytes resulted in apoptosis and elimination of C3H-HeJ TECs by 48 h, with enhanced survival and reduced apoptosis using lpr or gld TECs. In a renal allograft model, survival of C57BL/6 recipients was greater (p < 0.05) and renal function improved (p < 0.001) using C3H-lpr or C3H-gld (H-2 k) donor kidneys compared with C3H-HeJ kidneys. These data demonstrate for the first time that cytokine-activated TECs can injure TECs through expression of functional FasL and Fas. We suggest that inhibition of TEC-TEC 'self injury' may be a novel strategy to augment renal allograft survival.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".