The Role of Anti-non-Gal Antibodies in the Development of Acute Humoral Xenograft Rejection of hDAF Transgenic Porcine Kidneys in Baboons Receiving Anti-Gal Antibody Neutralization Therapy
Bibliographic record
Abstract
BACKGROUND: The present study was undertaken to determine the role of preformed and induced anti-non-Gal antibodies in the rejection of hDAF pig-to-baboon kidney xenotransplants after anti-Gal antibody neutralization therapy. METHODS: Seven baboons received life-supporting kidney transplants from hDAF transgenic pigs. Anti-Gal antibodies were neutralized by GAS914 or TPC (a Gal PEG glycoconjugate polymer). Group 1 (n=5) underwent a conventional immunosuppressive therapy with FK506, rabbit anti-thymocyte serum/immunoglobulin, mycophenolate mofetil, and steroids. Group 2 (n=2) received an anti-humoral immunity regimen with LF15-0195, Rituxan and cobra venom factor in addition to ATG, FK506 and steroids. Levels of anti-non-Gal antibodies and their mediated complement-dependent cytotoxic activities (CDC) were detected by flow cytometry using Gal knockout (k/o) pig lymphocytes (LC) or endothelial cells (EC) as targets. RESULTS: Continuous infusion of GAS914/TPC significantly reduced anti-Gal antibodies. In Group 1, four of five baboons developed severe acute humoral xenograft rejection (AHXR) and the rejection was associated with either a high level of preformed anti-non-Gal IgG or a marked elevation in induced anti-non-Gal IgG and IgM. Sera collected at the time of AHXR had a high level of CDC to porcine LC/EC from Gal k/o animals. The intensive anti-humoral therapy in Group 2 completely inhibited both anti-Gal and non-Gal antibody production and prevented AHXR. However, this therapy was not well tolerated by the baboons. CONCLUSION: In a pig-to-baboon kidney transplant model, both preformed and induced anti-non-Gal antibodies are strongly associated with the pathogenesis of AHXR when anti-Gal antibodies are neutralized.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".