Elf3 regulates dendritic cell driven T cell differentiation (99.1)
Bibliographic record
Abstract
Abstract Elf3 belongs to the family of epithelium specific Ets transcription factors and can be upregulated in non-epithelial cells upon cytokine stimulation. Elf3-/- mice have normal T cell development and T cell differentiation into different T helper lineages. Here we show that upon epicutaneous sensitization with ovalbumin(OVA) followed by OVA intranasal challenge, Elf3-/- mice display a defect in Th17 induction, though OVA specific IgE and IgG1 antibody titers are several folds higher and airway inflammation is more extensive compared to Elf3+/+ mice, indicating an exaggerated Th2 response. Furthermore, intraperitoneal sensitization of Elf3-/- mice with OVA followed by OVA intranasal challenge, confirmed that Elf3-/- mice mounted an exaggerated Th2 response. Since, dendritic cells (DCs) are key players in initiation of adaptive immune response, we analyzed DC migration upon OVA challenge and showed that pulmonary DCs underwent hyperactivation in Elf3-/- mice compared to Elf3+/+ mice and rates of DC migration to the airway draining lymph nodes were also significantly higher in Elf3-/- mice, indicating that DCs may mediate the exaggerated Th2 response observed in Elf3-/- mice. Further analysis revealed that Elf3-/- DCs are more prone to maturation than Elf3+/+ DCs and upon maturation, Elf3-/- DCs preferentially secrete chemokines/cytokines that are important in polarizing Th2 differentiation. Taken together, these findings reveal a role of Elf3 in DC driven T cell differentiation.
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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) | 0.003 | 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".