Inhibition of neutrophil elastase by the bacterial serine protease inhibitor ecotin in cystic fibrosis airway samples
Bibliographic record
Abstract
Abstract Cystic fibrosis (CF), a prevalent fatal genetic condition in North America, disrupts respiratory function by impeding chloride ion transport across mucosal surfaces. This leads to the thickening of mucus, resulting in constant lung inflammation and elevated levels of neutrophils. Neutrophil elastase (NE), a potent serine protease crucial for host defense, is released by these neutrophils. However, in excess, NE can cause detrimental host tissue damage. Abundant in CF airways, NE is a key predictor of lung disease progression. While past studies have explored targeting NE in CF, no optimal inhibitors have reached clinics. Our study tested ecotin, a bacterial periplasmic serine protease inhibitor, for its potential to impede NE activity in CF airway samples and curb NE release from human neutrophils. Results show that ecotin significantly reduces NE activity in sputum samples obtained from several CF patients. Additionally, we found that ecotin inhibits NE release from neutrophils exposed to CF lung stimuli like Staphylococcus aureus bacteria. These results establish ecotin as a promising NE inhibitor in CF with clinical potential.
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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".