Leukocyte Elastase Inhibition Therapy in Cystic Fibrosis: Role of Glycosylation on the Distribution of Alpha-1–Proteinase Inhibitor in Blood versus Lung
Bibliographic record
Abstract
Cystic fibrosis patients demonstrate an increased susceptibility to bacterial lung infections. Airway infiltration by neutrophils will then lead to an increase in human leukocyte elastase (HLE) within the extracellular compartment, thereby producing deleterious effects. Here, we investigated the properties and tissue distribution of an unglycosylated, recombinant form of the HLE inhibitor alpha-1-proteinase inhibitor (alpha(1)-antitrypsin rhalpha1PI) when it is administered to the airway surface. We produced rhalpha1PI using a bacterial expression system and found the purified protein to be indistinguishable from blood-purified, glycosylated alpha1PI at inhibiting elastase in vitro. In contrast to intravenous administration, direct delivery of either alpha1PI or rhalpha1PI to the airway surface of CD-1 mice by nasal instillation produced similar highly detectable levels of protein in bronchoalveolar lavage at all time points, suggesting that glycosylation of alpha1PI does not play the same critical role in determining protein stability at the respiratory surface as it does in the vascular compartment. Interestingly, this unglycosylated rhalpha1PI was also highly protective against elastase-mediated injury 24 h after rhalpha1PI instillation and was consistently found to be significantly more protective than glycosylated blood-derived alpha1PI. Thus, these results provide evidence that aerosol delivery of rhalpha1PI could be an effective strategy for controlling HLE-dependent pathophysiology associated with cystic fibrosis lung disease.
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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 | 0.001 |
| 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 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".