Human cathelicidin <scp>LL</scp>‐37 and its derivative <scp>IG</scp>‐19 regulate interleukin‐32‐induced inflammation
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Bibliographic record
Abstract
Human cathelicidin LL-37 protects against infections and endotoxin-induced inflammation. In a recent study we have shown that IG-19, an LL-37-derived peptide, protects in a murine model of arthritis. Cytokine interleukin-32 (IL-32) is elevated and directly associated with the disease severity of inflammatory arthritis. Therefore, in this study we examined the effects of LL-37 and IG-19 on IL-32-induced responses in human peripheral blood-derived mononuclear cells (PBMC) and macrophages. We showed that CD14(+) monocytes are the primary cells that produce pro-inflammatory tumour necrosis factor-α (TNF-α) following stimulation of PBMC with IL-32. We demonstrated that LL-37 and IG-19 significantly suppress IL-32-induced production of pro-inflammatory cytokines, e.g. TNF-α and IL-1β, without altering chemokine production. In contrast, LL-37 and IG-19 enhance the production of the anti-inflammatory cytokine IL-1RA. Further mechanistic studies revealed that LL-37 and IG-19 suppress IL-32-mediated phosphorylation of Fyn (Y420) Src kinase. In contrast, IL-32-mediated phosphorylation of AKT-1 (T308) and MKP-1 (S359) is not suppressed by the peptides. LL-37 and IG-19 alone induce the phosphorylation of MKP-1 (S359), which is a known negative regulator of inflammation. Furthermore, the peptides induce the activity of p44/42 mitogen-activated protein kinase, which is known to phosphorylate MKP-1 (S359). This is the first study to demonstrate the regulation of IL-32-induced inflammation by LL-37 and its derivative peptide IG-19. The mechanistic results from this study suggest that regulation of immune-mediated inflammation by these peptides may be controlled by the dual phosphatase MKP-1. We speculate that LL-37 and its derivatives may contribute to the control of immune-mediated inflammatory diseases.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it