Leukocyte Elastase Induces Lung Epithelial Apoptosis via a PAR-1–, NF-κB–, and p53-Dependent Pathway
Bibliographic record
Abstract
Leukocyte elastase induces apoptosis of lung epithelial cells via alterations in mitochondrial permeability, but the signaling pathways regulating this response remain uncertain. Here we investigated the involvement of proteinase-activated receptor-1 (PAR-1), the transcription factor NF-kappaB, and the protooncogene p53 in this pathway. Elastase-induced apoptosis of lung epithelial cells correlated temporally with activation of NF-kappaB, phosphorylation, and nuclear translocation of p53, increased p53 up-regulated modulator of apoptosis (PUMA) expression, and mitochondrial translocation of Bax resulting in enhanced permeability. Elastase-induced apoptosis was also prevented by pharmacologic inhibitors of NF-kappaB and p53 and by short interfering RNA knockdown of PAR-1, p53, or PUMA. These inhibitors prevented elastase-induced PUMA expression, mitochondrial translocation of Bax, increased mitochondrial permeability, and attenuated apoptosis. NF-kappaB inhibitors also reduced p53 phosphorylation. We conclude that elastase-induced apoptosis of lung epithelial cells is mediated by a PAR-1-triggered pathway involving activation of NF-kappaB and p53, and a PUMA- and Bax-dependent increase in mitochondrial permeability leading to activation of distal caspases. Further, p53 contributes to elastase-induced apoptosis by both transcriptional and post-transcriptional mechanisms.
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.
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".