The Ikaros zinc finger transcription factor Eos as a candidate regulator of TH2 differentiation and function.
Bibliographic record
Abstract
Abstract Although CD4+ T helper 2 (TH2) cells normally defend against parasitic infection, they play a central role in the pathogenesis of allergic asthma. Therefore, understanding the molecular mechanisms governing TH2 differentiation and function is a top priority for improving asthma outcomes. One pathway of interest for controlling TH2-mediated disease is IL-2/STAT5 signaling, which is essential for TH2 polarization yet boasts a complex regulatory network that is incompletely understood. Here, we identify the Ikaros zinc finger (IkZF) transcription factor Eos as a candidate regulator of IL-2/STAT5 signaling underlying TH2 differentiation and function. To start, we show that Eos gene and protein expression is increased in TH2 cells relative to CD4+ T cell subsets that are negatively regulated by IL-2/STAT5 signaling, such as TH17 and TFH cells. Given these findings, we sought to define the functional effects of Eos in TH2 cells using in vitro and in vivo murine house dust mite asthma models. Intriguingly, Eos deficiency in vitro and in vivo results in reduced expression of key TH2 transcription factors (Gata3, Blimp-1), effector cytokines (IL-4, IL-13), and differentiation receptors (IL-2Rα, IL-2Rβ, IL-4Rα). Mechanistically, our data reveal that Eos interacts with and increases the activity of STAT5, suggesting that Eos enhances TH2 differentiation and effector function through direct STAT5 regulation. These findings in proinflammatory TH2 cells are of high significance, as Eos, to date, has largely been associated with the immunosuppressive functions of TREG cells. Taken together, our data reveal a novel mechanism by which Eos positively regulates IL-2/STAT5 signaling to promote TH2 differentiation and function. Work supported by grants from the NIH (R01AI134972) and The Ohio State University (Susan Huntington Dean’s Distinguished University Fellowship).
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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 | 0.000 |
| 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".