Mechanical ventilation affects alveolar fibrinolysis in LPS-induced lung injury
Bibliographic record
Abstract
The aim of the present study was to determine the effects of mechanical ventilation on alveolar fibrin turnover in lipopolysaccharide (LPS)-induced lung injury. In a randomised controlled trial, Sprague-Dawley rats (n = 61) were allocated to three ventilation groups after intratracheal LPS (Salmonella enteritidis) instillations. Group I animals were subjected to 16 cmH(2)O positive inspiratory pressure (PIP) and 5 cmH(2)O positive end-expiratory pressure (PEEP); group II animals to 26 cmH(2)O PIP and 5 cmH(2)O PEEP; and group III animals to 35 cmH(2)O PIP and 5 cmH(2)O PEEP. Control rats (not mechanically ventilated) received LPS. Healthy rats served as a reference group. Levels of thrombin-antithrombin complex (TATc), D-dimer, plasminogen activator inhibitor (PAI) activity and PAI-1 antigen in bronchoalveolar lavage fluid were measured. LPS-induced lung injury increased TATc, D-dimer and PAI activity and PAI-1 antigen levels versus healthy animals. High pressure-amplitude ventilation increased TATc concentrations. D-dimer concentrations were not significantly raised. Instead, PAI activity increased with the amplitude of the pressure, from 0.7 U.mL(-1) in group I to 3.4 U.mL(-1) in group II and 5.0 U.mL(-1) in group III. There was no change in PAI-1 antigen levels. In conclusion, mechanical ventilation creates an alveolar/pulmonary anti-fibrinolytic milieu in endotoxin-induced lung injury which, at least in part, might be due to an increase in plasminogen activator inhibitor activity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".