Exposure of Human CD4 T Cells to IL-12 Results in Enhanced TCR-Induced Cytokine Production, Altered TCR Signaling, and Increased Oxidative Metabolism
Bibliographic record
Abstract
Human CD4 T cells are constantly exposed to IL-12 during infections and certain autoimmune disorders. The current paradigm is that IL-12 promotes the differentiation of naïve CD4 T cells into Th1 cells, but recent studies suggest IL-12 may play a more complex role in T cell biology. We examined if exposure to IL-12 alters human CD4 T cell responses to subsequent TCR stimulation. We found that IL-12 pretreatment increased TCR-induced IFN-γ, TNF-α, IL-13, IL-4 and IL-10 production. This suggests that prior exposure to IL-12 potentiates the TCR-induced release of a range of cytokines. We observed that IL-12 mediated its effects through both transcriptional and post-transcriptional mechanisms. IL-12 pretreatment increased the phosphorylation of AKT, p38 and LCK following TCR stimulation without altering other TCR signaling molecules, potentially mediating the increase in transcription of cytokines. In addition, the IL-12-mediated enhancement of cytokines that are not transcriptionally regulated was partially driven by increased oxidative metabolism. Our data uncover a novel function of IL-12 in human CD4 T cells; specifically, it enhances the release of a range of cytokines potentially by altering TCR signaling pathways and by enhancing oxidative metabolism.
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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".