Identification of the IL-17 Receptor Related Molecule IL-17RC as the Receptor for IL-17F
Bibliographic record
Abstract
The proinflammatory cytokines IL-17A and IL-17F have a high degree of sequence similarity and share many biological properties. Both have been implicated as factors contributing to the progression of inflammatory and autoimmune diseases. Moreover, reagents that neutralize IL-17A significantly ameliorate disease severity in several mouse models of human disease. IL-17A mediates its effects through interaction with its cognate receptor, the IL-17 receptor (IL-17RA). We report here that the IL-17RA-related molecule, IL-17RC is the receptor for IL-17F. Notably, both IL-17A and IL-17F bind to IL-17RC with high affinity, leading us to suggest that a soluble form of this molecule may serve as an effective therapeutic antagonist of IL-17A and IL-17F. We generated a soluble form of IL-17RC and demonstrate that it effectively blocks binding of both IL-17A and IL-17F, and that it inhibits signaling in response to these cytokines. Collectively, our work indicates that IL-17RC functions as a receptor for both IL-17A and IL-17F and that a soluble version of this protein should be an effective antagonist of IL-17A and IL-17F mediated inflammatory diseases.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".