Abstract B146: The tumor necrosis factor superfamily member RANKL suppresses effector cytokine production in group 3 innate lymphoid cells
Bibliographic record
Abstract
Abstract While signals that activate group 3 innate lymphoid cells (ILC3s) have been described, the factors that negatively regulate these cells are less well understood. Here we found that the tumor necrosis factor (TNF) superfamily member receptor activator of nuclear factor κB ligand (RANKL) suppressed ILC3 activity in the intestine. Deletion of RANKL in ILC3s and T-cells increased C-C motif chemokine receptor 6 (CCR6)+ ILC3 abundance and enhanced production of interleukin-17A (IL-17A) and IL-22 in response to IL-23 and during infection with the enteric murine pathogen Citrobacter rodentium. Additionally, CCR6+ ILC3s produced higher amounts of the master transcriptional regulator RORγt at steady state in the absence of RANKL. RANKL-mediated suppression was independent of T-cells, and instead occurred via interactions between CCR6+ ILC3s that expressed both RANKL and its receptor, RANK. Thus, RANK-RANKL interactions between ILC3s regulate ILC3 abundance and activation, suggesting that cell clustering may control ILC3 activity. Citation Format: Jennifer Kaoru Bando, Susan Gilfillan, Christina Song, Keely McDonald, Stanley C-C. Huang, Rodney D. Newberry, Yasuhiro Kobayashi, David S.J. Allan, James R. Carlyle, Marina Cella, Marco Colonna. The tumor necrosis factor superfamily member RANKL suppresses effector cytokine production in group 3 innate lymphoid cells [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B146.
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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) | 0.006 | 0.002 |
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".