Curtailed T‐cell activation curbs effector differentiation and generates CD8<sup>+</sup> T cells with a naturally‐occurring memory stem cell phenotype
Bibliographic record
Abstract
Abstract Human T memory stem (TSCM) cells with superior persistence capacity and effector functions are emerging as important players in the maintenance of long‐lived T‐cell memory and are thus considered an attractive population to be used in adoptive transfer‐based immunotherapy of cancer. However, the molecular signals regulating their generation remain poorly defined. Here we show that curtailed T‐cell receptor stimulation curbs human effector CD8+ T‐cell differentiation and allows the generation of CD45RO–CD45RA+CCR7+CD27+CD95+ ‐phenotype cells from highly purified naïve T‐cell precursors, resembling naturally‐occurring human TSCM. These cells proliferate extensively in vitro and in vivo, express low amounts of effector‐associated genes and transcription factors and undergo considerable self‐renewal in response to IL‐15 while retaining effector differentiation potential. Such a phenotype is associated with a lower number of mitochondria compared to highly‐activated effector T cells committed to terminal differentiation. These results shed light on the molecular signals that are required to generate long‐lived memory T cells with potential application in adoptive cell transfer immunotherapy.
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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) | 0.002 | 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".