Dendritic cells partially abrogate the regulatory activity of CD4+CD25+ T cells present in the human peripheral blood
Bibliographic record
Abstract
The factors that influence the functionality of human CD4(+)CD25(+) regulatory T cells are not well understood. We sought to characterize the effects of dendritic cells (DCs) on the in vitro regulatory activity of CD4(+)CD25(+) T cells obtained from peripheral blood of healthy human donors. Flow cytometry showed that a higher proportion of CD4(+)CD25(+(High)) T cells expressed surface glucocorticoid-induced tumor necrosis factor receptor family-related protein (GITR) and CTL-associated antigen 4 than CD4(+)CD25(-) or CD4(+)CD25(+(Med-low)) T cells. Intracellular Foxp3 was equivalently expressed on CD4(+)CD25(+(All)), CD4(+)CD25(+(High)), CD4(+)CD25(+(Med-low)) and CD4(+)CD25(-) T cell populations, irrespective of GITR and CTL-associated antigen 4 expression. CD4(+)CD25(+) T cells were isolated and then cultured in vitro with CD4(+)CD25(-) responder T cells and stimulated with anti-CD3 antibodies, and immature dendritic cells (iDCs), mature dendritic cells (mDCs), PBMCs or PBMCs plus anti-CD28 antibodies to provide co-stimulation. In addition, secretion of the T(h)1 cytokine IFN-gamma, IL-2 and the immunoregulatory cytokines, IL-10 and transforming growth factor (TGF)-beta, were also assessed in these cultures. We found that iDCs and mDCs were capable of reversing the suppression of proliferation mediated by CD4(+)CD25(+) regulatory T cells. However, the reversal of suppression by DCs was not dependent upon the increase of IFN-gamma and IL-2 production or inhibition of IL-10 and/or TGF-beta production. Therefore, DCs are able to reverse the suppressive effect of regulatory T cells independent of cytokine production. These results suggest for the first time that human DCs possess unique abilities which allow them to influence the functions of regulatory T cells in order to provide fine-tuning in the regulation of T cell responses.
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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 | 0.001 |
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".