Effect of Compressed Bovine Lipid Extract Surfactant Films on Oxygen Transfer
Bibliographic record
Abstract
In the lungs, oxygen transfer from the inspired air to the capillary blood needs to cross the surfactant lining layer of the alveoli. Therefore, the gas transfer characteristics of lung surfactant film are of fundamental physiological interest. However, previous in vitro studies-most relied on the Langmuir-type balance-fail to cover the low surface tension range (i.e., less than the equilibrium surface tension of approximately 25 mJ/m2) due to film leakage. We have recently developed a novel in vitro experimental strategy, the combination of axisymmetric drop shape analysis and captive bubble technique (ADSA-CB), in studying the effect of surfactant films on interfacial gas transfer (Langmuir 2005, 21, 5446). In the present work, ADSA-CB is used as a micro-film-balance to study the effect of compressed bovine lipid extract surfactant (BLES) films on oxygen transfer. A low surface tension ranging from approximately 25 mJ/m2 to 2 mJ/m2 is studied. The experimental results suggest that lung surfactant films at a low surface tension near 2 mJ/m2 provide resistance to oxygen transfer, as indicated by a decrease of 30-50% in the mass transfer coefficient (kL) of oxygen in BLES suspensions with respect to water. At higher surface tension (i.e., >6 mJ/m2), the resistance to oxygen transfer is only modest, i.e., the decrease in kL is less than 20% compared to water. The experimental results suggest that lung surfactant plays a role in oxygen transfer in the pulmonary system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 |
| 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".