Proteinase-activated receptors (PARs): activation of PAR<sub>1</sub> and PAR<sub>2</sub> by a proteolytic fragment of the neuronal growth associated protein B-50/GAP-43
Bibliographic record
Abstract
The neuronal growth associated protein B-50/GAP-43 has been localized in synaptosomes both as an intact protein and as a partial proteolysis product (termed B-60) that has an N-terminal sequence SFRGHITR.... Because of the relationship of this amino acid sequence to those of the tethered ligand for the human proteinase activated receptors PAR1 (SFLLRN...) and PAR2 (SLIGKV...), we wished to determine whether the B-50/GAP-43-derived proteolytic fragment SFRGHITR (SFR(B60)) might function as a PAR-activating peptide (PAR-AP) to stimulate either PAR1 or PAR2. With the use of a newly developed PAR1/PAR2 receptor activation-desensitization assay, employing PAR1/PAR2-bearing cultured human embryonic kidney (HEK293) cells, we found that SFR(B60) could activate both PAR1 and PAR2 so as to elevate intracellular calcium with EC50 values of approximately 200 and 50 microM, respectively. We also showed that trypsin can rapidly degrade B-50 to smaller fragments that would include the sequence SFR(B60). Because PAR1 and PAR2 are present on neurones, our data raise the possibility that in certain circumstances in vivo, B-50/GAP-43 may play a signalling role by serving as a precursor for proteolytically generated PAR-activating peptides.
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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) | 0.002 | 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".