Signaling Pathways Mediating Chemokine Induction in Keratinocytes by Cathelicidin LL-37 and Flagellin
Bibliographic record
Abstract
Cathelicidin LL-37 is a multifunctional immunomodulatory and antimicrobial host defense peptide that has an important role in the immune defenses of the skin and other epithelial barriers. We have previously demonstrated that at physiological concentrations LL-37 synergistically augments the production of immune mediators in response to microbial compounds in human primary keratinocytes. Here we define the signaling mechanisms responsible for this activity. We demonstrate that inhibition of Src family kinases (SFKs) strongly inhibited the synergistic chemokine production in response to LL-37 and flagellin in keratinocytes. SFK activation was induced by LL-37 stimulation and was required for the downstream activation of Akt (protein kinase B) and the transcription factors CREB and ATF1. In cells stimulated with LL-37 and flagellin together, Akt activation was primarily induced by LL-37, while both flagellin and LL-37 contributed to the activation of CREB and ATF1 and consequently chemokine induction. The purinergic receptor P2X₇ was identified as the receptor upstream of SFK activation in LL-37-stimulated keratinocytes. Overall, these findings established the P2X₇-SFK-Akt-CREB/ATF1 signaling pathway activated by LL-37 in primary keratinocytes. These signaling mechanisms mediated the synergistic effects of LL-37 on chemokine production in flagellin-stimulated keratinocytes, and thus might have a role in the immune defenses of the skin and possibly other epithelial barriers.
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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".