FcRγ Controls the Fas-Dependent Regulatory Function of Lymphoproliferative Double Negative T Cells
Bibliographic record
Abstract
Patients with autoimmune lymphoproliferative syndrome (ALPS) and lymphoproliferation (LPR) mice are deficient in Fas, and accumulate large numbers of αβ-TCR(+), CD4(-), CD8(-) double negative (DN) T cells. The function of these DN T cells remains largely unknown. The common γ subunit of the activating Fc receptors, FcRγ, plays an important role in mediating innate immune responses. We have shown previously that a significant proportion of DN T cells express FcRγ, and that this molecule is required for TCR transgenic DN T cells to suppress allogeneic immune responses. Whether FcRγ plays a critical role in LPR DN T cell-mediated suppression of immune responses to auto and allo-antigens is not known. Here, we demonstrated that FcRγ(+), but not FcRγ(-) LPR DN T cells could suppress Fas(+) CD4(+) and CD8(+) T cell proliferation in vitro and attenuated CD4(+) T cell-mediated graft-versus host disease. Although FcRγ expression did not allow LPR DN T cells to inhibit the expansion of Fas-deficient cells within the LPR context, adoptive transfer of FcRγ(+), but not FcRγ(-), DN T cells inhibited lymphoproliferation in generalized lymphoproliferative disease (GLD) mice. Furthermore, FcRγ acted in a cell-intrinsic fashion to limit DN T cell accumulation by increasing the rate of apoptosis in proliferated cells. These results indicate that FcRγ can confer Fas-dependent regulatory properties on LPR DN T cells, and suggest that FcRγ may be a novel marker for functional DN Tregs.
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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 | 0.000 | 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".