Inactivation of Human β-Defensins 2 and 3 by Elastolytic Cathepsins
Bibliographic record
Abstract
beta-Defensins are antimicrobial peptides that contribute to the innate immune responses of eukaryotes. At least three defensins, human beta-defensins 1, 2, and 3 (HBD-1, -2, and -3), are produced by epithelial cells lining the respiratory tract and are active toward Gram-positive (HBD-3) and Gram-negative (HBD-1, -2, and -3) bacteria. It has been postulated that the antimicrobial activity of defensins is compromised by changes in airway surface liquid composition in lungs of patients with cystic fibrosis (CF), therefore contributing to the bacterial colonization of the lung by Pseudomonas and other bacteria in CF. In this report we demonstrate that HBD-2 and HBD-3 are susceptible to degradation and inactivation by the cysteine proteases cathepsins B, L, and S. In addition, we show that all three cathepsins are present and active in CF bronchoalveolar lavage. Incubation of HBD-2 and -3 with CF bronchoalveolar lavage leads to their degradation, which can be completely (HBD-2) or partially (HBD-3) inhibited by a cathepsin inhibitor. These results suggest that beta-defensins are susceptible to degradation and inactivation by host proteases, which may be important in the regulation of beta-defensin activity. In chronic lung diseases associated with infection, overexpression of cathepsins may lead to increased degradation of HBD-2 and -3, thereby favoring bacterial infection and colonization.
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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".