Soluble TIR-8 neutralizes anti-inflammatory effects of IL-37 in Crohn disease patients
Bibliographic record
Abstract
Abstract Toll-IL-1Receptor (TIR)-8 is an atypical member of the IL-1 receptor family (IL-1RF). Recently, it was shown to act as the second sub-unit of the receptor for IL-37, the first being IL-18Rα chain. IL-37 is a potent anti-inflammatory cytokine belonging to the IL-1 family that exerts anti-inflammatory, immune deviating and metabolic effects. We found that the cytokine concentrations are increased in the circulation of Crohn disease (CD) patients compared with healthy controls. However, the expression of TIR-8 was decreased on the surface of different peripheral blood mononuclear cells in the patients. Furthermore, the concentrations of soluble TIR-8 were also increased in the circulation of the patients. Our results show that metalloproteinase inhibitors prevent shedding of TIR-8 from the cell surface. Soluble TIR-8 inhibits anti-inflammatory effects of IL-37 in human cells. When soluble TIR-8 was added in different concentrations, in the presence and absence of IL-37, to LPS-stimulated THP-1 cells, it inhibited the anti-inflammatory effects of the cytokine on the secretion of TNF-α from these cells. The inhibition was exerted in a dose-dependent manner. Taken together, these results suggest that IL-37 is neutralized in CD patients by TIR-8 shedding, which makes immune cells less responsive to the cytokine. Furthermore, soluble TIR-8 also neutralizes anti-inflammatory effects of the cytokine and contributes towards a pro-inflammatory state in these patients. Measures aimed at restoring anti-inflammatory effects of IL-37 by inhibiting shedding of TIR-8 and/or neutralizing its soluble form may be helpful in attenuating inflammation in CD patients.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".