γ<sub>c</sub> cytokines provide multiple homeostatic signals to naive CD4<sup>+</sup> T cells
Bibliographic record
Abstract
Cytokines signaling through receptors sharing the common gamma chain (gamma(c)), including IL-2, IL-4, IL-7, IL-9, IL-15 and IL-21, are critical for the generation and peripheral homeostasis of B, T and NK cells. To identify unique or redundant roles for gamma(c) cytokines in naive CD4(+) T cells, we compared monoclonal populations of CD4(+) T cells from TCR-Tg mice that were gamma(c) (+), gamma(c) (-), CD127(-/-) or CD122(-/-). We found that gamma(c) (-) naive CD4(+) T cells failed to accumulate in the peripheral lymphoid organs and the few remaining cells were characterized by small size, decreased expression of MHC class I and enhanced apoptosis. By over-expressing human Bcl-2, peripheral naive CD4(+) T cells that lack gamma(c) could be rescued. Bcl-2(+) gamma(c) (-) CD4(+) T cells demonstrated enhanced survival characteristics in vivo and in vitro, and could proliferate normally in vitro in response to antigen. Nevertheless, Bcl-2(+) gamma(c) (-) CD4(+) T cells remained small in size, and this phenotype was not corrected by enforced expression of an activated protein kinase B. We conclude that gamma(c) cytokines (primarily but not exclusively IL-7) provide Bcl-2-dependent as well as Bcl-2-independent signals to maintain the phenotype and homeostasis of the peripheral naive CD4(+) T cell pool.
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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".