Elf3 Regulates Allergic Airway Inflammation by Controlling Dendritic Cell-Driven T Cell Differentiation
Bibliographic record
Abstract
Elf3 belongs to the Ets family of transcription factors and has been implicated in inflammation. Elf3 is highly expressed in the lungs, and Elf3(-/-) mice are impaired in IL-6 production after intranasal LPS exposure. To identify the role of Elf3 in Th17-driven pulmonary inflammation, we have performed epicutaneous sensitization of Elf3(-/-) mice with OVA followed by airway OVA challenge and have identified Elf3(-/-) mice to be impaired in induction of Th17 response, attributable to impairment of IL-6 production by dendritic cells (DCs). However, increased serum levels of OVA-specific IgG1 and IgE were observed, pointing toward an exaggerated Th2 response. To study Th2 response, we performed i.p. sensitization of Elf3(-/-) mice with OVA and confirmed loss of Elf3 to result in an aggravated Th2 response, characterized by increased generation of IL-4-producing T cells, increased levels of OVA-specific IgE and IgG1 Ab titers, and increased serum levels of Th2 cytokines, together with extensive inflammation and mucus production in airways. Elf3(-/-) DCs were impaired in priming Th1 differentiation, which, in turn, promoted Th2 differentiation. This was mediated by the ability of Elf3(-/-) DCs to undergo hypermaturation but secrete significantly lower levels of IL-12 in response to inflammatory stimuli. The impairment of IL-12 production was due to impairment of IL-12p40 gene induction in Elf3(-/-) DCs in response to inflammatory stimuli. Taken together, our study identifies a novel function of Elf3 in regulating allergic airway inflammation by regulating DC-driven Th1, Th2, and Th17 differentiation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".