Inflammatory Cytokines Determine the Susceptibility of Human CD8 T Cells to Fas-mediated Activation-induced Cell Death through Modulation of FasL and c-FLIPS Expression
Bibliographic record
Abstract
The nature of inflammatory signals determines the outcome of T cell responses. However, little is known about how inflammatory cytokines provided to human CD8 T cells during activation affects their susceptibility to post-activation cell death. We have examined and compared the effects of the inflammatory cytokine IL-12, as well as the combination of IL-1, IL-6, and IL-23 (IL-1/6/23) on the susceptibility of primary human CD8 T cells to post-activation cell death. Human CD8 T cells activated in the presence of IL-1/6/23 underwent significantly less cell death after activation as compared with those activated in IL-12. This was due to reduced susceptibility to Fas-mediated activation-induced cell death (AICD). Mechanistically, the reduced level of cell death in CD8 T cells activated in IL-1/6/23 was a result of a low level of FasL expression and high level of c-FLIP(S) expression. When the effect of IL-1, IL-6, and IL-23 individually was examined, IL-1 or IL-6 alone was sufficient to inhibit CD8 T cell death that occurs after activation in IL-12. IL-1, but not IL-6, inhibited expression of FasL, whereas IL-6, but not IL-1, increased c-FLIP(S) expression. Our findings show that the presence of IL-1 and/or IL-6 during activation of human CD8 T cells attenuates Fas-mediated AICD, whereas IL-12 increases the susceptibility of activated CD8 T cells to this form of cell death.
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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".