Pulmonary Capillary Endothelium-Bound Angiotensin-Converting Enzyme Activity in Acute Lung Injury
Bibliographic record
Abstract
BACKGROUND: Pulmonary capillary endothelium-bound (PCEB) angiotensin-converting ectoenzyme (ACE) activity alteration is an early, sensitive, and quantifiable lung injury index in animal models. We hypothesized that (1) PCEB-ACE alterations can be found in patients with acute lung injury (ALI) and (2) PCEB-ACE activity correlates with the severity of lung injury and may be used as a quantifiable marker of the underlying pulmonary capillary endothelial dysfunction. METHODS AND RESULTS: Applying indicator-dilution techniques, we measured single-pass transpulmonary hydrolysis of the synthetic ACE substrate (3)H-benzoyl-Phe-Ala-Pro (BPAP) in 33 mechanically ventilated, critically ill patients with a lung injury score (LIS) ranging from 0 (no lung injury) to 3.7 (severe lung injury) and calculated the kinetic parameter A(max)/K(m). Both parameters decreased early during the ALI continuum and were inversely related to APACHE II score and LIS. Hydrolysis decreased with increasing cardiac output (CO), whereas 2 different patterns were observed between CO and A(max)/K(m). CONCLUSIONS: PCEB-ACE activity decreases early during ALI, correlates with the clinical severity of both the lung injury and the underlying disease, and may be used as a quantifiable marker of underlying pulmonary capillary endothelial dysfunction.
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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 | 0.001 |
| 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".