Hypercholesterolemia does not affect pulmonary surfactant or the development of acute lung injury in rats
Bibliographic record
Abstract
Pulmonary surfactant is a lipoprotein complex necessary for lung function. The importance of surfactant is evident in Acute lung injury (ALI) in which the dysfunction of surfactant is thought to contribute to the hypoxemia characterizing the disease. Recent studies have specifically implicated elevated levels of cholesterol within surfactant as a mechanism for its dysfunction. It is not known if this effect is dependent on serum cholesterol. It was hypothesized that diet‐induced serum hypercholesterolemia affects surfactant composition and will cause development of more severe ALI. Wistar rats were fed a standard laboratory diet or high cholesterol diet prior to enrollment into one of three models of ALI: a ventilator induced lung injury model, a surfactant depleted lung injury model and an acid aspiration lung injury model. For each model measurements of lung injury, such as arterial oxygenation, as well as surfactant composition were measured. Results of this study indicated there were no significant differences in arterial oxygenation or surfactant composition between rats fed the standard diet versus the high cholesterol diet in any of the models of lung injury. In conclusion , these three complementary models of ALI suggest that diet‐induced serum hypercholesterolemia does not affect surfactant composition or the development of ALI. Funding was provided by the Canadian Institutes for Health Research.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".