Gamma-Ray Resistance of Regulatory CD4<sup>+</sup>CD25<sup>+</sup>Foxp3<sup>+</sup>T Cells in Mice
Bibliographic record
Abstract
Abstract CD4(+)CD25(+) regulatory T cells (Treg cells) are an important subset of T cells for keeping proper immune responses and tolerance. However, the effects of gamma radiation on CD4(+)CD25(high) Foxp3(+) Treg cells have not been examined previously. In the present study, we compared the sensitivity of mouse CD4(+)CD25(high) Foxp3(+) Treg cells and CD4(+)CD25(-) T cells to gamma radiation in vitro and in vivo. After C57BL/6 mice received a whole-body dose of 5 Gy gamma rays, the numbers of lymphocyte subsets in blood, lymph nodes, spleens and thymuses clearly decreased. However, gamma radiation significantly enhanced the ratios of CD4(+)CD25(high) Treg cells and CD4(+)CD25(high) Foxp3(+) Treg cells to CD4(+) T cells in the blood, lymph nodes, spleens and thymuses of mice. More dead cells were observed in CD4(+)CD25(-) T cells than in CD4(+)CD25(high) Treg cells or CD4(+)CD25(high) Foxp3(+) Treg cells when the cells were irradiated in vitro, indicating that CD4(+)CD25(high) Foxp3(+) Treg cells are more resistant to gamma radiation than other T cells. Moreover, a higher expression of Bcl-2 in CD4(+)CD25(high) Treg cells was detected compared with that in CD4(+)CD25(-) T cells. CD4(+)CD25(+) Treg cells from irradiated mice were functional, though their immunosuppressive ability was somewhat impaired compared to those from nonirradiated mice as determined by an in vitro assay. These results indicate that mouse CD4(+)CD25(+) Treg cells and CD4(+)CD25(-) T effector cells have different sensitivities to gamma radiation in mice.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".