‘Bystander polarization’ of CD4<sup>+</sup> T cells: activation with high‐dose IL‐2 renders naive T cells responsive to IL‐12 and/or IL‐18 in the absence of TCR ligation
Bibliographic record
Abstract
Responsiveness of CD4+ T cells to the IFN-gamma-inducing cytokines IL-12 and IL-18 is generally thought to be acquired only after stimulation via the TCR. We report herein that stimulation of naive CD4+ T cells with high-dose IL-2 (1000 U/ml) renders these cells responsive to IL-12 and/or IL-18 without a requirement for TCR ligation. Naive CD4+CD62L+ Tcells from normal C57BL/6 mice or from DO11.10/Rag2(-/- )OVA-specific TCR-transgenic mice secreted substantial amounts of IFN-gamma when stimulated concurrently with high-dose IL-2 plus IL-12 or IL-18. mRNA encoding both chains of the IL-12 and the IL-18 receptors was expressed by CD4+ T cells after stimulation with high-dose IL-2. Furthermore, anti-CD3-induced IL-12/IL-18 responsiveness was fully abrogated in the presence of cyclosporin A whereas IL-2-induced IL-12/IL-18 responsiveness was not, reminiscent of the previously reported IL-12+IL-18 innate pathway of T cell activation. Lastly, after stimulation with IL-2+IL-12, naive CD4+ T cells from DO11.10/Rag2(-/- )mice exhibited polarization towards a Th1 phenotype (high IFN-gamma but no IL-4) during secondary stimulation with immobilized anti-CD3. We have coined the term "bystander polarization" to describe this phenomenon and we speculate that bystander polarization of naive CD4+ T cells may occur in vivo during strong antigen-specific immune responses.
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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) | 0.000 | 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 | 0.001 |
| 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".