Prevention of Chronic Renal Allograft Rejection by Soluble CD83
Bibliographic record
Abstract
BACKGROUND: Recombinant human soluble CD83 had previously exhibited significant immunosuppressive properties that involved interference with dendritic cell maturation in both mouse and humans, inhibition of autoimmunity in mice, and induction of antigen-specific mouse cardiac allograft tolerance when used in combination with other immunosuppressive drugs. Our current research focus turned to examining the effects of peritransplant soluble CD83 (sCD83) administration on prevention of chronic renal allograft rejection. METHODS: Fisher344-to-Lewis orthotopic rat renal transplants were performed with sequential recipient killing on postoperative days (PODs) 2, 14, and 140 to examine both the acute and chronic effects of peritransplant sCD83 treatment in rat recipients. RESULTS: Recipients treated with sCD83 exhibited a marked decrease in IgM and IgG deposition in the graft and antidonor antibody levels in the circulation, as early as POD14 and persisting until POD140. sCD83 treatment also reduced the infiltration of T cells and monocytes into the graft tissue and inhibited intragraft expression of MyD88 and inflammatory cytokine levels during the observation period. sCD83-treated grafts demonstrated normal histology beyond POD140, including dramatic reductions in tubular atrophy and interstitial fibrosis compared with untreated recipients. CONCLUSION: We have demonstrated that peritransplant treatment with recombinant sCD83 attenuates both innate and adaptive immune responses and leads to prevention of chronic rejection in a rat renal transplant model. Because sCD83 is of human origin, the therapeutic approach used in our rodent transplant model holds significant promise for clinical transplantation.
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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) | 0.000 | 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".