The circadian clock of CD8 T cells modulates their early response to vaccination and the rhythmicity of related signaling pathways
Bibliographic record
Abstract
Circadian variations of various aspects of the immune system have been described. However, the circadian control of T cells has been relatively unexplored. Here, we investigated the role of circadian clocks in regulating CD8 T cell response to antigen presentation by dendritic cells (DCs). The in vivo CD8 T cell response following vaccination with DCs loaded with the OVA 257–264 peptide antigen (DC-OVA) leads to a higher expansion of OVA-specific T cells in response to vaccination done in the middle of the day, compared to other time points. This rhythm was dampened when DCs deficient for the essential clock gene Bmal1 were used and abolished in mice with a CD8 T cell-specific Bmal1 deletion. Thus, we assessed the circadian transcriptome of CD8 T cells and found an enrichment in the daytime of genes and pathways involved in T cell activation. Based on this, we investigated early T cell activation events. Three days postvaccination, we found higher T cell activation markers and related signaling pathways (including IRF4, mTOR, and AKT) after a vaccination done during the middle of the day compared to the middle of the night. Finally, the functional impact of the stronger daytime response was shown by a more efficient response to a bacterial challenge at this time of day. Altogether, these results suggest that the clock of CD8 T cells modulates the response to vaccination by shaping the transcriptional program of these cells and making them more prone to strong and efficient activation and proliferation according to the time of day.
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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 | 0.000 |
| 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".