Biophysical investigation of vape additives with complex lung surfactant model systems and physiological surfactant extracts
Bibliographic record
Abstract
Selected vape additives, vitamin E acetate and CBD, are suspected agents in pathology of vape related lung illnesses. The lipophilic nature of these molecules allow them to partition into lung surfactant and disrupt proper function. Such dysfunction can lead to respiratory distress and hypoxemia, two common symptoms of this new class of lung injury. Lung surfactant models were formed by depositing lipids at the air-water interface on a Langmuir-Blodgett trough. Surface pressure-area isotherms were conducted for lipid-additive systems to determine changes in lipid packing, film elasticity, and film stability, while Brewster angle microscopy was used to visualize lateral film organization. Vape additives were found to interfere with proper lipid packing, inducing fluidization throughout the lipid films. Additionally, this hindered the formation of lipid condensed domains. Such structures are necessary for surfactant protein anchoring in order to facilitate the formation of multilayers. In complex model systems, this vital processes was significantly impaired, namely by vitamin e acetate. These data suggest a vape additive induced dysfunction of lipid films which may be involved in the pathology of vape-related lung injury.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".