The transcription factor ROR alpha preserves group 3 innate lymphoid cell lineage identity and function
Bibliographic record
Abstract
Abstract Innate lymphoid cells (ILCs) are critical for host defense and tissue repair. The transcription factor RORα is essential for ILC2 development but it is also highly expressed by ILC3s where its function remains poorly defined. Previously, we found that Rorasg/sg bone marrow transplant (BMT) mice were protected from intestinal fibrosis in a Salmonella--induced model of Crohn’s disease and that this is due to defective cytokine production by ILC3s. In the current study, whole transcriptome sequencing analysis reveals a striking downregulation of ILC3 signature genes in RORα-deficient ILC3s isolated from Salmonella infected mice. In particular, the expression of genes involved in sensing an inflammatory milieu is attenuated. Moreover, we find that Rorasg/sg ILC3s fail to express IL-17A following ex vivo stimulation with IL-23 and IL-1β. Consistent with these observations, we also find that Rorasg/sg BMT mice are more susceptible to Citrobacter rodentium infection due to attenuated expression of IL-22 and impaired induction of antimicrobial peptides. Collectively, our data suggests that RORα plays a key role in preserving functional ILC3s by modulating their ability to sense environmental cues that stimulate the efficient production of cytokines. These observations also suggest that targeting ILC3 cells could be of therapeutic benefit in fibrosis associated with Crohn’s disease.
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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) | 0.002 | 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".