Effective in vivo treatment of acute lung injury with helical, amphipathic peptoid mimics of pulmonary surfactant proteins
Bibliographic record
Abstract
Acute lung injury (ALI) leads to progressive loss of breathing capacity and hypoxemia, as well as pulmonary surfactant dysfunction. ALI's pathogenesis and management are complex, and it is a significant cause of morbidity and mortality worldwide. Exogenous surfactant therapy, even for research purposes, is impractical for adults because of the high cost of current surfactant preparations. Prior in vitro work has shown that poly-N-substituted glycines (peptoids), in a biomimetic lipid mixture, emulate key biophysical activities of lung surfactant proteins B and C at the air-water interface. Here we report good in vivo efficacy of a peptoid-based surfactant, compared with extracted animal surfactant and a synthetic lipid formulation, in a rat model of lavage-induced ALI. Adult rats were subjected to whole-lung lavage followed by administration of surfactant formulations and monitoring of outcomes. Treatment with a surfactant protein C mimic formulation improved blood oxygenation, blood pH, shunt fraction, and peak inspiratory pressure to a greater degree than surfactant protein B mimic or combined formulations. All peptoid-enhanced treatment groups showed improved outcomes compared to synthetic lipids alone, and some formulations improved outcomes to a similar extent as animal-derived surfactant. Robust biophysical mimics of natural surfactant proteins may enable new medical research in ALI treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".