Atomic Force Microscopy of Interfacial Monomolecular Films of Pulmonary Surfactant
Bibliographic record
Abstract
Pulmonary surfactant (PS) is a lipid protein complex secreted at the terminal airways of the lung. The material is secreted as lipid rich multilamellate bodies, which transforms into lipid—protein tubules, planar bilayers, and monomolecular films at the alveolar air—aqueous interface ( 1 , 2 ). The films reduce the surface tension of the interface and prevents lung collapse during end expiration ( 3 ). PS layers also act as a protective barrier against inhaled particles and bacteria and keeps the upper airways or bronchioles open during respiration ( 3 ). Dysfunction of PS has been implicated in various lung diseases, such as asthma, acute respiratory distress syndrome, cystic fibrosis, and pneumonia ( 4 ). The composition of PS is conserved in most air-breathing species; however, its high content of saturated phosphatidylcholine (PC) and phosphatidylglycerol (PG) is unique compared with other secretory materials and cell membranes, which lack these phospholipids ( 1 , 5 ). Specifically, PS contains significant amounts of dipalmitoylphosphatidylcholine (DPPC), palmitoyl-oleyl-PC (POPC) and PG (POPG), cholesterol, and small amounts (10%) of surfactant proteins SP-A, SP-B, SP-C, and SP-D ( 1 ). It is not clear to date how this lipid—protein complex functions by forming alveolar films or barrier in situ because such fragile and dynamic films are difficult to preserve for traditional electron microscopy ( 2 , 3 ). In vitro studies have focused on model lipid—protein films of PS and also by extracting the material out of lungs and studying interfacial properties of surface tension of such material using Langmuir and other surface balances ( 6 – 8 ). These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".