Bibliographic record
Abstract
Little is known about the molecules that control the development and function of CD4+ CD25+ Tregs. Recently, it was shown that the transcription factor FOXP3 is necessary and sufficient for the generation of CD4+ CD25+ Tregs in mice. We investigated the capacity of FOXP3 to drive the generation of suppressive CD4+ CD25+ Tregs in humans. Surprisingly, although ectopic expression of FOXP3 in human CD4+ T cells resulted in induction of hyporesponsiveness and suppression of IL-2 production, it did not lead to acquisition of significant suppressor activity in vitro. Similarly, ectopic expression of FOXP3delta2, an isoform found in human CD4+ CD25+ Tregs that lacks exon 2, also failed to induce the development of suppressor T cells. Moreover, when FOXP3 and FOXP3delta2 were simultaneously overexpressed, although the expression of several Treg-associated cell surface markers was significantly increased, only a modest suppressive activity was induced. These data indicate that in humans, overexpression of FOXP3 alone or together with FOXP3delta2 is not an effective method to generate potent suppressor T cells in vitro and suggest that factors in addition to FOXP3 are required during the process of activation and/or differentiation for the development of bona fide 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 | 0.001 | 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 | 0.000 |
| 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".