Lung Surfactant Protein A (SP-A) Interactions with Model Lung Surfactant Lipids and an SP-B Fragment
Bibliographic record
Abstract
Surfactant protein A (SP-A) is the most abundant protein component of lung surfactant, a complex mixture of proteins and lipids. SP-A performs host defense activities and modulates the biophysical properties of surfactant in concerted action with surfactant protein B (SP-B). Current models of lung surfactant mechanism generally assume SP-A functions in its octadecameric form. However, one of the findings of this study is that when SP-A is bound to detergent and lipid micelles that mimic lung surfactant phospholipids, it exists predominantly as smaller oligomers, in sharp contrast to the much larger forms observed when alone in water. These investigations were carried out in sodium dodecyl sulfate (SDS), dodecylphosphocholine (DPC), lysomyristoylphosphatidylcholine (LMPC), lysomyristoylphosphatidylglycerol (LMPG), and mixed LMPC + LMPG micelles, using solution and diffusion nuclear magnetic resonance (NMR) spectroscopy. We have also probed SP-A's interaction with Mini-B, a biologically active synthetic fragment of SP-B, in the presence of micelles. Despite variations in Mini-B's own interactions with micelles of different compositions, SP-A is found to interact with Mini-B in all micelle systems and perhaps to undergo a further structural rearrangement upon interacting with Mini-B. The degree of SP-A-Mini-B interaction appears to be dependent on the type of lipid headgroup and is likely mediated through the micelles, rather than direct binding.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".