The human cationic host defense peptide LL-37 mediates contrasting effects on apoptotic pathways in different primary cells of the innate immune system
Bibliographic record
Abstract
The human cathelicidin LL-37 is a cationic host defense peptide (antimicrobial peptide) expressed primarily by neutrophils and epithelial cells. This peptide, up-regulated under conditions of inflammation, has immunomodulatory and antimicrobial functions. We demonstrate that LL-37 is a potent inhibitor of human neutrophil apoptosis, signaling through P2X(7) receptors and G-protein-coupled receptors other than the formyl peptide receptor-like-1 molecule. This process involved modulation of Mcl-1 expression, inhibition of BID and procaspase-3 cleavage, and the activation of phosphatidylinositol-3 kinase but not the extracellular signal-regulated kinase 1/2 mitogen-activated protein kinase pathway. In contrast to the inhibition of neutrophil apoptosis, LL-37 induced apoptosis in primary airway epithelial cells, demonstrating alternate consequences of LL-37-mediated modulation of apoptotic pathways in different human primary cells. We propose that these novel immunomodulatory properties of LL-37 contribute to peptide-mediated enhancement of innate host defenses against acute infection and are of considerable significance in the development of such peptides and their synthetic analogs as potential therapeutics for use against multiple antibiotic-resistant infectious diseases.
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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".