Long-term Kinetics of Intragraft Gene Signatures in Renal Allograft Tolerance Induced by Transient Mixed Chimerism
Bibliographic record
Abstract
BACKGROUND: Renal allograft tolerance (TOL) has been successfully induced in nonhuman primates (NHPs) and humans through the induction of transient mixed chimerism. To elucidate the mechanisms of TOL, we compared local immunologic responses in renal allografts with those in T-cell-mediated rejection (TCMR) and chronic antibody-mediated rejection (CAMR) in NHPs. METHODS: Using the NanoString nCounter platform, we retrospectively studied 52 mRNAs in 256 kidney allograft samples taken from NHP kidney recipients of donor BMT. No immunosuppression was given after 1-month post-donor BMT. Recipients who achieved TOL (n = 13) survived for >1840 ± 1724 days with normal kidney function, while recipients with CAMR (n = 13) survived for 899 ± 550 days with compromised graft function, and recipients with TCMR (n = 15) achieved only short-term survival (132 ± 69 days). RESULTS: The most prominent difference between the groups was FOXP3, which was significantly higher in TOL than in CAMR and TCMR, both early (<1 y, P < 0.01) and late (≥1 y, P < 0.05) after transplant. Other mRNAs related to regulatory T cells (Treg), such as IL10, TGFB, and GATA3, were also high in TOL. In contrast, transcripts of inflammatory cytokines were higher in TCMR, while activated endothelium-associated transcripts were higher in CAMR than in TOL. The receiver operating characteristic analyses revealed that intragraft FOXP3 and CAV1 can reliably distinguish TOL from CAMR. CONCLUSIONS: High FOXP3 and other Treg-related mRNAs together with suppressed inflammatory responses and endothelial activation in renal allografts suggest that intragraft enrichment of Treg is a critical mechanism of renal allograft TOL induced by transient mixed chimerism.
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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 | 0.000 | 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) | 0.000 | 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".