Modulation of the TLR-Mediated Inflammatory Response by the Endogenous Human Host Defense Peptide LL-37
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Bibliographic record
Abstract
The sole human cathelicidin peptide, LL-37, has been demonstrated to protect animals against endotoxemia/sepsis. Low, physiological concentrations of LL-37 (< or =1 microg/ml) were able to modulate inflammatory responses by inhibiting the release of the proinflammatory cytokine TNF-alpha in LPS-stimulated human monocytic cells. Microarray studies established a temporal transcriptional profile and identified differentially expressed genes in LPS-stimulated monocytes in the presence or absence of LL-37. LL-37 significantly inhibited the expression of specific proinflammatory genes up-regulated by NF-kappaB in the presence of LPS, including NFkappaB1 (p105/p50) and TNF-alpha-induced protein 2 (TNFAIP2). In contrast, LL-37 did not significantly inhibit LPS-induced genes that antagonize inflammation, such as TNF-alpha-induced protein 3 (TNFAIP3) and the NF-kappaB inhibitor, NFkappaBIA, or certain chemokine genes that are classically considered proinflammatory. Nuclear translocation, in LPS-treated cells, of the NF-kappaB subunits p50 and p65 was reduced > or =50% in the presence of LL-37, demonstrating that the peptide altered gene expression in part by acting directly on the TLR-to-NF-kappaB pathway. LL-37 almost completely prevented the release of TNF-alpha and other cytokines by human PBMC following stimulation with LPS and other TLR2/4 and TLR9 agonists, but not with cytokines TNF-alpha or IL-1beta. Biochemical and inhibitor studies were consistent with a model whereby LL-37 modulated the inflammatory response to LPS/endotoxin and other agonists of TLR by a complex mechanism involving multiple points of intervention. We propose that the natural human host defense peptide LL-37 plays roles in the delicate balancing of inflammatory responses in homeostasis as well as in combating sepsis induced by certain TLR agonists.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it