Targeting the mTOR pathway uncouples the efficacy and toxicity of PD-1 blockade in renal transplantation
Bibliographic record
Abstract
Abstract Immune checkpoint inhibitor (ICI) use remains a challenge in patients with solid organ allografts as most would undergo rejection. In a melanoma patient in whom programmed-death 1 (PD-1) blockade resulted in organ rejection and colitis, the addition of the mTOR inhibitor sirolimus resulted in ongoing anti-tumor efficacy while promoting allograft tolerance. Strong granzyme B+, interferon (IFN)-γ+ CD8+ cytotoxic T cell and circulating regulatory T (Treg) cell responses were noted during allograft rejection, along with significant eosinophilia and elevated serum IL-5 and eotaxin levels. Co-treatment with sirolimus abated cytotoxic T cell numbers and eosinophilia, while elevated Treg cell numbers in the peripheral blood were maintained. Interestingly, numbers of IFN-γ+ CD4+ T cells and serum IFN-γ levels increased with the addition of sirolimus treatment likely promoting ongoing anti-PD-1 efficacy. Thus, our results indicate that sirolimus has the potential to uncouple anti-PD-1 therapy toxicity and efficacy.
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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 | 0.001 |
| 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".