Targeting Calcium Release–activated Calcium Channel Is Not Sufficient to Prevent Rejection in Nonhuman Primate Kidney Transplantation
Bibliographic record
Abstract
BACKGROUND: Calcineurin inhibitors successfully control rejection of transplanted organs but also cause nephrotoxicity. This study, using a rhesus monkey renal transplantation model, sought to determine the applicability of a new immunomodulatory drug inhibiting the store-operated calcium release-activated calcium channel of lymphocytes to control transplant rejection without nephrotoxicity. METHODS: Animals underwent kidney transplantation and were treated with tacrolimus alone (n = 3), a CRACM1 inhibitor (PRCL-02) (n = 6) alone, or with initial tacrolimus monotherapy followed by gradual conversion at 3 weeks to PRCL-02 alone (n = 3). PRCL-02 was administered via a surgically inserted gastrostomy tube BID. RESULTS: Dose-related drug exposure in monkeys was established and renal transplants were then performed using PRCL-02 monotherapy. Oral dosing of PRCL-02 was well tolerated and resulted in suppressed T-cell proliferation in in vitro MLR comparable to animals in the tacrolimus control arm. Animals receiving tacrolimus monotherapy were e on day 100 without rejection. PRCL-02 monotherapy only marginally prolonged graft survival (MST = 13.16 d; group 2) compared with untreated controls. Animals treated initially with tacrolimus and converted to PRCL-02 monotherapy had a mean graft survival of 35.3 days which was prolonged compared with PRCL-02 monotherapy but not compared with the tacrolimus-treated group. Pharmacokinetic studies showed inconsistent drug exposures despite attempts to adjust dose and exposure which may have contributed to the rejections. CONCLUSIONS: We conclude that, in this nonhuman primate model of kidney transplantation, PRCL-02 demonstrated evidence of in vivo immunosuppressive activity but was inferior to tacrolimus treatment with respect to suppressing immune transplant 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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".