Characterization of bovine surfactant proteins B and C by electrospray ionization mass spectrometry
Bibliographic record
Abstract
Bovine surfactant proteins B (SP-B) and C (SP-C) were analyzed by nano-electrospray ionization mass spectrometry (nano-ESI-MS). The observed molecular masses showed discrepancies compared to the calculated molecular masses using the published amino acid sequences. The number of cysteine residues in the published bovine SP-B amino acid sequences also failed to match the observed mass shift upon reduction of the SP-B dimer. To determine the amino acid sequences of two proteins, SP-B was first digested with trypsin and analyzed by liquid chromatography/tandem mass spectrometry (LC/MS/MS), while SP-C was analyzed by MS/MS in its intact form. The amino acid sequence of bovine SP-B determined here matches the observed molecular mass. The sequence is almost identical to the sheep SP-B except for two amino acid residues, consistent with the proximity of the two species. The correct sequence contains seven cysteine residues. Bovine SP-B exists as dimers and all cysteines are oxidized to form disulfide bonds in physiological conditions, which is in agreement with the observed mass shift upon reduction of the SP-B dimer. These cysteine residues are completely conserved across all species indicating their importance for the biological functions of this surfactant protein. The sequence of SP-C determined here also reveals an L to V substitution at its position 22 compared with the published bovine SP-B sequence.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".