DEPTOR modulates activation responses in CD4+ T cells and enhances immunoregulation following transplantation
Bibliographic record
Abstract
DEPTOR is an evolutionarily conserved cell-intrinsic binding partner of mTOR that functions as a negative regulator of signaling responses. In this study, we show that DEPTOR is expressed within CD4 + T cells, and we observed that its relative level of expression modulates differentiation as well as glucose utilization within CD4 + T effectors in vitro. Using knock-in mice, we also find that induced expression of DEPTOR within CD4 + T regulatory cells stabilizes Foxp3 expression, shifts metabolism toward oxidative phosphorylation, and increases survival and suppressive function. In vivo, fully MHC mismatched cardiac allograft survival is significantly prolonged in knock-in recipients and sustained recipient expression of DEPTOR in combination with costimulatory blockade induces long-term graft survival. Furthermore, we show that the induced expression of DEPTOR in CD4 + T effectors fails to inhibit acute allograft rejection. Rather, prolonged survival is dominantly mediated via induced expression and function of DEPTOR within recipient CD4 + T regulatory cells. These collective findings identify DEPTOR as a novel protein that functions in CD4 + T cells to augment immunoregulation in vitro and in vivo.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".