CD8+ T CELLS ARE CAPABLE OF REJECTING PANCREATIC ISLET XENOGRAFTS1, 2
Bibliographic record
Abstract
BACKGROUND: In this study, the capacity of CD8+ T cells to act as a potential effector mechanism in pancreatic xenograft rejection was examined. METHODS: The fate of pancreatic islet xenografts was studied in mice deficient in MHC class II molecules and CD4+ T cells. Fetal pig pancreas (FPP) or Wistar rat islets (RI) were transplanted into nondiabetic or streptozotocin-induced diabetic I-A knock-out (CII K/O) mice. RESULTS: CII K/O mice were capable of rejecting both RI and FPP grafts. RI graft survival was not prolonged compared with wild type C57BL/6 controls. However, FPP grafts did survive longer in CII K/O recipients than in C57BL/J6 mice. Both RI and FPP graft rejection were CD8+ T-cell phenomena in CII K/O mice, as anti-CD8 monoclonal antibody prolonged graft survival, there were increased CD8+ T cells in the grafts and spleens of CII K/O recipients, and cell-mediated cytotoxicity was a CD8+ T-cell phenomenon associated with activation of the perforin/granzyme B system. By contrast, RI and FPP graft rejection was a CD4+ T cell-dependent phenomenon in wild type C57BL/6 mice with graft survival prolonged by anti-CD4 monoclonal antibody. There were increased numbers of CD4+ T cells, and cell-mediated cytotoxicity was a CD4+ T-cell phenomenon associated with activation of the Fas/FasL lytic pathway. CONCLUSIONS: The results demonstrate that, in the absence of CD4+ T cells, CD8+ T cells were capable of rejecting both rat and pig pancreatic islet xenografts.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".