Faculty Opinions recommendation of A multiply redundant genetic switch 'locks in' the transcriptional signature of regulatory T cells.
Bibliographic record
Abstract
The transcription factor Foxp3 participates dominantly in the specification and function of Foxp3(+)CD4(+) regulatory T cells (T(reg) cells) but is neither strictly necessary nor sufficient to determine the characteristic T(reg) cell signature. Here we used computational network inference and experimental testing to assess the contribution of other transcription factors to this. Enforced expression of Helios or Xbp1 elicited distinct signatures, but Eos, IRF4, Satb1, Lef1 and GATA-1 elicited exactly the same outcome, acting in synergy with Foxp3 to activate expression of most of the T(reg) cell signature, including key transcription factors, and enhancing occupancy by Foxp3 at its genomic targets. Conversely, the T(reg) cell signature was robust after inactivation of any single cofactor. A redundant genetic switch thus 'locked in' the T(reg) cell phenotype, a model that would account for several aspects of T(reg) cell physiology, differentiation and stability. PMID: 22961053 Funding information This work was supported by: NIAID NIH HHS, United States Grant ID: R24 AI072073 NIAID NIH HHS, United States Grant ID: R01 AI051530 NIDDK NIH HHS, United States Grant ID: T32 DK7260 Canadian Institutes of Health Research, Canada NIAID NIH HHS, United States Grant ID: 3R24AI072073-03S1 NIGMS NIH HHS, United States Grant ID: T32 GM007753 NIAID NIH HHS, United States Grant ID: R37 AI051530 NIAID NIH HHS, United States Grant ID: AI072073 NIAID NIH HHS, United States Grant ID: AI051530 More Less keyboard_arrow_down
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.402 | 0.171 |
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".