Molecular Organization Revealed by Time-of-Flight Secondary Ion Mass Spectrometry of a Clinically Used Extracted Pulmonary Surfactant
Bibliographic record
Abstract
Pulmonary surfactant lowers the surface tension of the lung air−liquid interface to prevent alveolar collapse. It is composed mainly of saturated and unsaturated phosphatidylcholines and phosphatidylglycerols. Solvent-spread films of a pulmonary surfactant, bovine lipid extract surfactant (BLES), form liquid condensed and liquid expanded phases with changing surface pressures, as seen by fluorescence and atomic force microscopy. Time-of-flight secondary ion mass spectrometry conducted in an imaging mode below the static limit provides a novel means of mapping the identities of the molecular species present in each phase. Images can be obtained for cations, like calcium and sodium, as well as for phospholipid parent and fragment ions. The phospholipids identified include dipalmitoyl- and palmitoyloleoylphosphatidylcholine as positive ions and dipalmitoyl- and palmitoyloleoylphosphatidylglycerol as negative ions. We observe good miscibility of phospholipids with similar chain lengths but different headgroups. At higher surface pressures, dipalmitoylphosphatidylcholine and dipalmitoylphosphatidylglycerol cocrystallize in the liquid condensed (LC) phase. As well, there is evidence of an intermediate phase, within the LC region. The results indicate that the details of phospholipid mixing and reorganization in surfactant films can be determined by static secondary ion mass spectrometry imaging at high resolution, thus providing insight into the relationship between composition and structure in surfactant films at the air−aqueous interface.
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 | 0.000 |
| 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 | 0.000 |
| 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".