Physiological effects of oxidized exogenous surfactant in vivo: effects of high tidal volume and surfactant protein A
Bibliographic record
Abstract
Oxidative damage to surfactant can decrease lung function in vivo. In the current study, our two objectives were: 1) to examine whether the adverse effects of oxidized surfactant would be accentuated in animals exposed to high tidal volume ventilation, and 2) to test whether supplementation with surfactant protein A (SP-A) could improve the function of oxidized surfactant in vivo. The first objective was addressed by evaluating the response of surfactant-deficient rats administered normal or oxidized surfactant and then subjected to low tidal volume (6 ml/kg) or high tidal volume (12 ml/kg) mechanical ventilation. Under low tidal volume conditions, rats administered oxidized surfactant had impaired lung function, as determined by lung compliance and arterial blood gas analysis, compared with nonoxidized controls. Animals subjected to high tidal volume ventilation had impaired lung function compared with low tidal volume groups, regardless of the oxidative status of the surfactant. The second experiment demonstrated a significantly superior physiological response in surfactant-deficient rats receiving SP-A containing oxidized surfactant compared with oxidized surfactant. Lavage analysis at the end of the in vivo experimentation showed no differences in the recovery of oxidized surfactant compared with nonoxidized surfactant. We conclude that minimizing excessive lung stretch during mechanical ventilation is important in the context of exogenous surfactant supplementation and that SP-A has an important biophysical role in surfactant function in conditions of oxidative stress. Furthermore, the oxidative status of the surfactant does not appear to affect the alveolar metabolism of this material.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".