Paracrine Generation of NO by Bystander Human CD8 T Cells Augments Allogeneic Responses by Inhibiting Cytokine Deprivation-Induced Cell Death (141.3)
Bibliographic record
Abstract
Abstract We previously reported that NO, generated by iNOS expressed in bystander human CD8 T cells, augments the accumulation of allogeneically activated human CD8 T cells in vitro and in vivo. Here we report that iNOS-derived NO does not affect T cell proliferation but rather inhibits cell death of activated human CD8 T cells after activation by allogeneic endothelial cells in culture. Furthermore, exogenous NO does not affect activation-induced cell death of human CD8 T cells but specifically reduces death of activated T cells due to cytokine deprivation. This effect does not involve cGMP signaling, and NO does not affect the protein expression levels of Bcl-2, Bcl-xL, Mcl-1, Bim, or PUMA, which are Bcl-2-related proteins previously implicated as regulators of cytokine deprivation-induced cell death. However, NO inhibits the activity of caspases activated as a consequence of cytokine deprivation in activated T cells. This protective effect correlated with S-nitrosylation of caspases and was phenocopied by ZVAD-FMK and LEDH-FMK, pharmacological inhibitors of caspases. Our findings suggest that NO augments the accumulation of allo-activated human T cells principally by inhibiting cytokine deprivation-induced cell death through S-nitrosylation of caspases.
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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".