The Surface-Associated Surfactant Reservoir in the Alveolar Lining
Bibliographic record
Abstract
A small atmospheric bubble was introduced into a surfactant suspension in a captive bubble surfactometer. After film formation to the equilibrium surface tension at the bubble air-liquid interface, the bulk phase surfactant was depleted by replacing the chamber contents several times with a saline-CaCl2 solution. The remaining film adsorbed at the bubble surface was then compressed stepwise in quasi-static fashion to near zero minimum surface tension. This was followed by a series of quasi-static expansion steps to surface tensions slightly above equilibrium. The surface tension of films from lipid extract surfactants and phospholipid mixtures did not increase in a manner consistent with the presence of a single surface monolayer. After the initial, rapid rise in surface tension at each expansion step, a decrease in surface tension to a new value was observed. This decrease in surface tension is likely due to the adsorption of 'surplus' material from a 'surface-associated reservoir' into the surface active film. The presence of surplus non-monolayer surfactant material in situ at the alveolar surface was also demonstrated by electron microscopy. SP-A acted as a potent promoter for the movement of excess material (equivalent to 2-3 monolayers) at the interface into the surface active film. In contrast, inhibitory serum proteins prevented the formation of a surface-associated reservoir or the adsorption of excess material into a surface active film.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".