IL-2 Induction of Blimp-1 Is a Key In Vivo Signal for CD8+ Short-Lived Effector T Cell Differentiation
Bibliographic record
Abstract
During infection or vaccination, only a small proportion of CD8(+) T cells differentiate into memory cells. The mechanisms underlying the differentiation of CD8(+) T cells into short-lived effector cells (SLECs) or memory precursor effector cells are poorly defined. It was recently shown in infectious models that the transcriptional repressor B lymphocyte-induced maturation protein 1 (Blimp-1) enhances the formation of SLECs. The factors controlling Blimp-1 expression leading to the in vivo formation of SLECs are still not known. However, it has been shown that cytokines such as IL-2 induce Blimp-1 expression in vitro. In this study, we took advantage of the low-inflammation model of dendritic cell immunization to study the role of the IL-2/Blimp-1 axis in SLEC differentiation as well as the importance of Blimp-1 expression in memory precursor effector cells for proper CD8(+) memory generation. Our results show that Blimp-1 deficiency affects effector differentiation and function in the absence of inflammation. Unexpectedly, memory generation was not affected in Blimp-1-deficient OT-I cells responding to vaccination. In addition, modulation of the bioavailability of IL-2 by injection either of a blocking Ab or of the cytokine, demonstrates a link between IL-2, Blimp-1 induction, and SLEC formation in wild-type cells. Conversely, injection of IL-2 had less effect on Blimp-1-deficient CD8(+) T cells, indicating that the effect of IL-2 on in vivo SLEC differentiation is mediated by Blimp-1. In conclusion, IL-2 induction of Blimp-1 expression is a key regulator of SLEC differentiation in vivo.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".