The Human Cathelicidin LL-37 Preferentially Promotes Apoptosis of Infected Airway Epithelium
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Cationic host defense peptides are key, evolutionarily conserved components of the innate immune system. The human cathelicidin LL-37 is an important cationic host defense peptide up-regulated in infection and inflammation, specifically in the human lung, and was shown to enhance the pulmonary clearance of the opportunistic pathogen Pseudomonas aeruginosa in vivo by as yet undefined mechanisms. In addition to its direct microbicidal potential, LL-37 can modulate inflammation and immune mechanisms in host defense against infection, including the capacity to modulate cell death pathways. We demonstrate that at physiologically relevant concentrations of LL-37, this peptide preferentially promoted the apoptosis of infected airway epithelium, via enhanced LL-37-induced mitochondrial membrane depolarization and release of cytochrome c, with activation of caspase-9 and caspase-3 and induction of apoptosis, which only occurred in the presence of both peptide and bacteria, but not with either stimulus alone. This synergistic induction of apoptosis in infected cells was caspase-dependent, contrasting with the caspase-independent cell death induced by supraphysiologic levels of peptide alone. We demonstrate that the synergistic induction of apoptosis by LL-37 and Pseudomonas aeruginosa required specific bacteria-epithelial cell interactions with whole, live bacteria, and bacterial invasion of the epithelial cell. We propose that the LL-37-mediated apoptosis of infected, compromised airway epithelial cells may represent a novel inflammomodulatory role for this peptide in innate host defense, promoting the clearance of respiratory pathogens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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