The Influence of Baseline Expression of Human Decay Accelerating Factor Transgene on Graft Survival and Acute Humoral Xenograft Rejection
Bibliographic record
Abstract
BACKGROUND: Transgenic pigs expressing human decay accelerating factor (hDAF) have been widely used as donors in various non-human primate transplant models. Despite the use of similar immunosuppressive protocols, there is marked variation in graft survival among centres. The present study was undertaken to determine whether the level of hDAF expression in the pig kidney correlates with the degree of rejection and duration of graft survival. METHODS: hDAF transgenic pigs were provided from two suppliers: Guelph Imutran Centre (G) and Harlan Sprague Dawley (H). Following a bilateral nephrectomy, a single hDAF pig kidney was implanted in the baboon, which was subsequently treated with conventional immunosuppressive protocols. The pig's contralateral kidney was collected to provide baseline data. The severity of acute humoral xenograft rejection (AHXR) was graded as stage I-III. hDAF expression was measured using morphologic analysis comparing the contralateral and grafted kidneys at the endpoint. RESULTS: Baseline hDAF expression in kidneys from pigs provided by supplier G was significantly higher than that from supplier H (P<0.01). Furthermore, the survival of baboons receiving grafts from G pigs was significantly longer than those receiving grafts from H pigs (P<0.05). In addition, reduction of hDAF expression at the endpoint was associated with a higher degree of AHXR. Severe apoptosis or necrosis was found in grafts with AHXR II-III. CONCLUSIONS: Pig kidneys from different suppliers have variable baseline hDAF expression, which may have an influence on graft survival. Reduced expression of hDAF in the terminal graft was associated with the severity of rejection.
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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 | 0.001 | 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 | 0.000 |
| 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".