The secretory proprotein convertase neural apoptosis-regulated convertase 1 (NARC-1): Liver regeneration and neuronal differentiation
Bibliographic record
Abstract
Seven secretory mammalian kexin-like subtilases have been identified that cleave a variety of precursor proteins at monobasic and dibasic residues. The recently characterized pyrolysin-like subtilase SKI-1 cleaves proproteins at nonbasic residues. In this work we describe the properties of a proteinase K-like subtilase, neural apoptosis-regulated convertase 1 (NARC-1), representing the ninth member of the secretory subtilase family. Biosynthetic and microsequencing analyses of WT and mutant enzyme revealed that human and mouse pro-NARC-1 are autocatalytically and intramolecularly processed into NARC-1 at the (Y,I)VV(V,L)(L,M) downward arrow motif, a site that is representative of its enzymic specificity. In vitro peptide processing studies andor Ala substitutions of the P1-P5 sites suggested that hydrophobicaliphatic residues are more critical at P1, P3, and P5 than at P2 or P4. NARC-1 expression is highest in neuroepithelioma SK-N-MCIXC, hepatic BRL-3A, and in colon carcinoma LoVo-C5 cell lines. In situ hybridization and Northern blot analyses of NARC-1 expression during development in the adult and after partial hepatectomy revealed that it is expressed in cells that have the capacity to proliferate and differentiate. These include hepatocytes, kidney mesenchymal cells, intestinal ileum, and colon epithelia as well as embryonic brain telencephalon neurons. Accordingly, transfection of NARC-1 in primary cultures of embryonic day 13.5 telencephalon cells led to enhanced recruitment of undifferentiated neural progenitor cells into the neuronal lineage, suggesting that NARC-1 is implicated in the differentiation of cortical neurons.
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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) | 0.001 | 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".