A Synergistic Effect Between PG490-88 and Tacrolimus Prolongs Renal Allograft Survival in Monkeys
Bibliographic record
Abstract
This study was undertaken to determine if PG490-88 and tacrolimus (Tac) act synergistically to prevent renal allograft rejection in monkeys and to explore possible mechanisms of synergy between these agents. MHC-mismatched renal allografts were transplanted into cynomolgus monkeys after bilateral nephrectomy. Recipients were divided into the following groups: (i) no treatment; (ii) PG490-88 (0.03 mg/kg); (iii) Tac (1 mg/kg); (iv) PG490-88 (0.01 mg/kg) + Tac (1 mg/kg) and (v) PG490-88 (0.03 mg/kg) + Tac (1 mg/kg). Through synergy PG490-88 and Tac inhibited anti-CD3/PMA-induced T-cell proliferation and IFN-gamma expression in vitro. Tac monotherapy only marginally prolonged survival (27 +/- 3.2 days), while the combination of PG490-88 and Tac significantly prolonged graft survival to a median of 99 days (PG490-88 at 0.03 mg) and 38.5 days (PG490-88 at 0.01 mg/kg). Prolonged survival correlated with inhibited IgM production as well as reduced T-cell infiltration, IL-2 protein expression and NF-AT/NF-kappaB activity. We conclude that PG490-88 and a subtherapeutic dose of Tac significantly prolong renal allograft survival in monkeys through the synergistic inhibition of T-cell activation and a decrease in IFN-gamma production and NF-AT/NF-kappaB activity.
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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".