Mass spectrometry strategies applied to the characterization of proline‐rich peptides from secretory parotid granules of pig (<i>Sus scrofa</i>)
Bibliographic record
Abstract
Basic proline-rich proteins (bPRPs) are a class of proteins widely present in saliva of humans and other mammals. They are synthesized as preproproteins and enzymatically cleaved into small peptides before secretion from the salivary glands. Recently, we characterized two proline-rich peptides (SP-A and SP-B) in parotid secretory granules of pig (Sus Scrofa) that are derived from three isoforms of a PRP proprotein (Swiss-Prot data bank: Q95JC9-1, Q95JC9-2 and Q95JC9-3). Together the coding regions for SP-A and SP-B, which are repeated many times, account for 52-70% of the coding regions of the PRP proproteins. This study was undertaken to identify peptides encoded by unassigned regions of the PRP proproteins. RP-HPLC-ESI-IT-MS analysis of enriched granule preparations from pig parotid glands by two different analytical strategies identified ten new proline-rich peptides derived from the three proproteins. Together with the coding regions for SP-A and SP-B already identified it was possible to assign 68-75% of the proproteins coding regions. The peptide sequences indicated a number of unusual proteolytic cleavage sites suggesting the presence of unknown proprotein convertases.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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".