The Notch signaling pathway: a new mastor regulator of effector CD8 T cell differentiation
Bibliographic record
Abstract
Abstract Following an infection, naïve CD8 T cells expand and differentiate into effectors able to eliminate the pathogen. At the peak of the response, two major populations of effectors are distinguishable: short-lived effector cells (SLECs) meant to die by apoptosis and memory precursor effector cells (MPECs) destined to survive as memory cells that confer long-term protection. We postulated that the Notch signaling pathway, known for its role in cellular differentiation and binary cell fate choice, acts as a key player in the MPEC/SLEC differentiation choice. To elucidate the role of Notch signalling, we have analyzed CD8 T cell response in mice lacking or not the expression of Notch1 and Notch2 in mature CD8 T cells. Following infection with Listeria or vaccination with antigen-pulsed dendritic cells, Notch deficiency drastically diminished SLEC generation and affect cytokines production without impairing CD8 memory T cell generation. Interestingly, altered SLEC differentiation occurs despite normal expression of the transcription factors, T-bet and Blimp-1, known to be necessary for SLEC differentiation. Moreover, the reduced generation of SLECs in absence of Notch signaling correlated with defective expression of CD25 by effectors. However, restoration of CD25 expression along with daily IL-2 complementation in Notch1/2-deficient T cells did not correct SLEC differentiation. These results suggest either that Notch regulates the expression of new players involved in SLEC differentiation or Notch signaling collaborates with already known actors of SLEC differentiation such as T-bet or Blimp-1. The identification of the genes regulated by Notch should help to reveal its role in CD8 T cell response.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".