Interleukin (IL)-6 Inhibits IL-27- and IL-30-Mediated Inflammatory Responses in Human Monocytes
Bibliographic record
Abstract
Interleukin (IL)-30, the IL-27p28 subunit of the heterodimeric cytokine IL-27, acts as an antagonist of IL-27 and IL-6 signaling in murine cells via glycoprotein 130 (gp130) receptor and additional binding partners. Thus far, functions of IL-30 have not been fully elucidated in human cells. We demonstrate that like IL-27, IL-30 upregulated TLR4 expression to enhance lipopolysaccharide-induced TNF-α production in human monocytes; however, these IL-30-mediated activities did not reach the same levels of cytokine induction compared to IL-27. Interestingly, IL-30- and IL-27-mediated interferon-γ-induced protein 10 (IP-10) production required WSX-1 engagement and signal transducer and activator of transcription (STAT) 3 phosphorylation; furthermore, IL-30 induced STAT phosphorylation after 16 h, whereas IL-27 induced STAT phosphorylation within 30 min. This prompted us to examine if a secondary mediator was required for IL-30-induced pro-inflammatory functions, and hence we examined IL-6-related molecules. Combined with inhibition of soluble IL-6 receptor α (sIL-6Rα) and data showing that IL-6 inhibited IL-30/IL-27-induced IP-10 expression, we demonstrate a role for sIL-6Rα and gp130 in IL-30-mediated activity in human cells.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".