Activated CD8+ T Cells Induce Expansion of Vβ5+ Regulatory T Cells via TNFR2 Signaling
Bibliographic record
Abstract
Vβ5(+) regulatory T cells (Tregs), which are specific for a mouse endogenous retroviral superantigen, become activated and proliferate in response to Friend virus (FV) infection. We previously reported that FV-induced expansion of this Treg subset was dependent on CD8(+) T cells and TNF-α, but independent of IL-2. We now show that the inflammatory milieu associated with FV infection is not necessary for induction of Vβ5(+) Treg expansion. Rather, it is the presence of activated CD8(+) T cells that is critical for their expansion. The data indicate that the mechanism involves signaling between the membrane-bound form of TNF-α on activated CD8(+) T cells and TNFR2 on Tregs. CD8(+) T cells expressing membrane-bound TNF-α but no soluble TNF-α remained competent to induce strong Vβ5(+) Treg expansion in vivo. In addition, Vβ5(+) Tregs expressing only TNFR2 but no TNFR1 were still responsive to expansion. Finally, treatment of naive mice with soluble TNF-α did not induce Vβ5(+) Treg expansion, but treatment with a TNFR2-specific agonist did. These results reveal a new mechanism of intercellular communication between activated CD8(+) T cell effectors and Tregs that results in the activation and expansion of a Treg subset that subsequently suppresses CD8(+) T cell functions.
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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) | 0.001 | 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".