In vitro–expanded human CD4+CD25+ T-regulatory cells can markedly inhibit allogeneic dendritic cell–stimulated MLR cultures
Bibliographic record
Abstract
CD4(+)CD25(+) T-regulatory (Treg) cells have been shown to critically regulate self- and allograft tolerance in several model systems. Studies of human Treg cells have been restricted by the small number present in peripheral blood and their naturally hypoproliferative state. To better characterize Treg suppressor cell function, we determined methods for the isolation and expansion of these cells. Stringent magnetic microbead-based purification was required for potent suppressor cell line generation. Culture stimulation with cell-sized Dynabeads coated with anti-CD3 and anti-CD28 monoclonal antibodies, CD4(+) feeder cells, and interleukin 2, provided for marked expansion in cell number (100-fold), with retention and enhancement of suppressor function. The potent Treg cell lines suppressed proliferation in dendritic cell-driven allo-mixed lymphocyte reaction (MLR) cultures by more than 90%. The Treg-derived suppressor cells functioned early in allo-MLR because expression of activation antigens and accumulation of cytokines was nearly completely prevented. Importantly, cultured Treg cells also suppressed activated and matured dendritic cell-driven responses. These results demonstrate that short-term suppressor cell lines can be generated, and they can express a very potent suppressive activity. This approach will enable more detailed biologic studies of Treg cells and facilitate the evaluation of cultured Treg cells as a novel form of immunosuppressive therapy.
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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) | 0.002 | 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".