Acute lung injury and lung transplantation influence in vitro subtype conversion of pulmonary surfactant
Bibliographic record
Abstract
The effects of surfactant treatment on surfactant subtype conversion after lung injury were examined. Dogs were subjected to hyperventilation for 8 h with or without surfactant treatment. Lungs were stored for 17 h, and the right lung was transplanted and reperfused for 6 h. Conversion of large aggregate (LA) surfactant to small aggregates was investigated using in vitro surface area cycling. LA from transplanted lungs (Transplant-LA) from the nontreated group converted more rapidly than Transplant-LA from the treated group. Transplant-LA from both groups converted more rapidly than LA from normal lungs. Calculations based on [(3)H]dipalmitoylphosphatidylcholine in the administered surfactant [bovine lipid extract surfactant (BLES)] showed that the endogenous component of Transplant-LA converted more rapidly than the exogenous component. This indicates exogenous BLES did not equilibrate completely with endogenous surfactant. LA from hyperventilated, stored donor right lungs and from the recipients' native lungs from the nontreated group converted more rapidly than corresponding LA in the BLES-treated group. Similar relative conversions were observed with exogenous components from all lungs. Relative conversion of endogenous component from Transplant-LA was more rapid than that from LA from donor's stored right lung or from the recipient's native right lung. Low levels of phenylmethylsulfonyl fluoride inhibited conversion of Transplant-LA to a greater extent than normal LA. LA from all experimental groups had similar protein levels. These studies show acute lung injury, transplant, ischemia-reperfusion, and surfactant treatment have major effects on surfactant subtype integrity.
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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 | 0.000 |
| 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".