Coexpression of Proprotein Convertase SPC3 and the Neuroendocrine Precursor ProSAAS<sup>1</sup>
Bibliographic record
Abstract
The subtilisin-like proprotein convertases are a family of serine proteinases involved in the processing of secreted proteins via cleavage at paired basic residues. Until recently, only one natural inhibitor had been demonstrated, the neuropeptide 7B2, which contains a C-terminal domain with inhibitory activity against SPC2. A novel granin-like peptide precursor, named proSAAS, has recently been identified that contains potent and specific inhibitory activity on SPC3 in vitro. To exert such an inhibitory action of SPC3 activity, it would be important to demonstrate that proSAAS and SPC3 are colocalized. We have studied the expression of proSAAS and SPC3 mRNAs in the rat central nervous system and various peripheral tissues by in situ hybridization histochemistry. Our results show that, like 7B2, proSAAS is expressed with a panneuronal distribution. In the periphery, proSAAS is an excellent marker of endocrine cells. Double labeling studies show that SPC3 expression is nearly always accompanied by proSAAS expression. However, proSAAS was also found to be expressed in endocrine cells and neurons that did not express SPC3, suggesting that proSAAS could have additional functions other than the modulation of SPC3 activity. These data support the hypothesis that one of the roles of proSAAS may be to modulate the activity of SPC3.
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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) | 0.001 | 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".