Role of the N-Terminal Seven Residues of Surfactant Protein B (SP-B)
Bibliographic record
Abstract
Breathing is enabled by lung surfactant, a mixture of proteins and lipids that forms a surface-active layer and reduces surface tension at the air-water interface in lungs. Surfactant protein B (SP-B) is an essential component of lung surfactant. In this study we probe the mechanism underlying the important functional contributions made by the N-terminal 7 residues of SP-B, a region sometimes called the "insertion sequence". These studies employed a construct of SP-B, SP-B (1-25,63-78), also called Super Mini-B, which is a 41-residue peptide with internal disulfide bonds comprising the N-terminal 7-residue insertion sequence and the N- and C-terminal helices of SP-B. Circular dichroism, solution NMR, and solid state (2)H NMR were used to study the structure of SP-B (1-25,63-78) and its interactions with phospholipid bilayers. Comparison of results for SP-B (8-25,63-78) and SP-B (1-25,63-78) demonstrates that the presence of the 7-residue insertion sequence induces substantial disorder near the centre of the lipid bilayer, but without a major disruption of the overall mechanical orientation of the bilayers. This observation suggests the insertion sequence is unlikely to penetrate deeply into the bilayer. The 7-residue insertion sequence substantially increases the solution NMR linewidths, most likely due to an increase in global dynamics.
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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 | 0.000 |
| 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".