Imbalance between Cysteine Proteases and Inhibitors in a Baboon Model of Bronchopulmonary Dysplasia
Bibliographic record
Abstract
RATIONALE: Bronchopulmonary dysplasia (BPD) continues to be a major morbidity in preterm infants. The lung pathology in BPD is characterized by impaired alveolar and capillary development. An imbalance between proteases and protease inhibitors in association with changes in lung elastic fibers has been implicated in the pathogenesis of BPD. OBJECTIVE: To investigate the expression and activity levels of papain-like lysosomal cysteine proteases, cathepsins B, H, K, L, S, and their inhibitors, cystatins B and C, in a baboon model of BPD. METHODS: Real-time reverse transcriptase-polymerase chain reaction, immunohistochemistry, immunoblotting, active site labeling of cysteine proteases, and in situ hybridization were performed. MEASUREMENTS AND MAIN RESULTS: The steady-state mRNA and protein levels of all cathepsins were significantly increased in the lung tissue of baboons with BPD. In contrast, the steady-state mRNA and protein levels of two major cysteine protease inhibitors, cystatin B and C, were unchanged. Correlating with these alterations, the activity of cysteine proteases in lung tissue homogenates and bronchoalveolar lavage fluid was significantly higher in the BPD group. The levels of cathepsin B, H, and S increased and cathepsin K decreased with advancing gestation. All cathepsins, except for cat K, were immunolocalized to macrophages in BPD. In addition, cathepsin H and cystatin B were colocalized in type 2 alveolar epithelial cells. Cathepsin L was detected in some bronchial epithelial, endothelial, and interstitial cells. Cathepsin K was localized to some perivascular cells by in situ hybridization. CONCLUSIONS: Cumulatively, these findings demonstrate an imbalance between cysteine proteases and their inhibitors in BPD.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".