Furin may contribute to proglucagon processing and glucagon-like Peptide-1 production in human alpha cells
Bibliographic record
Abstract
OBJECTIVES: While glucagon-like peptide-1 (GLP-1) production has been previously documented in human alpha cells, the steps regulating its production and secretion are poorly characterized. We investigated the enzymes implicated in proglucagon processing, characterizing their expression and localization in primary human alpha cells and αTC1/9 cells. METHODS: Human alpha cells and αTC1/9 cells were maintained in control conditions or exposed to proinflammatory and Akt-activating stimuli to enhance GLP-1 levels. Proglucagon and convertase enzyme gene expression, protein content, and subcellular localization were evaluated by qPCR, Western Blot, and immunofluorescent microscopy, respectively. RESULTS: Our data suggests that the canonical GLP-1-producing enzyme, Prohormone Convertase 1/3 (PC1/3), is poorly expressed and localized in alpha cells, while its homologue furin is optimally positioned for GLP-1 production. We also note that GLP-1 and glucagon processing occur in different subcellular compartments, creating two distinct pools of secretory granules which respond to similar secretory stimuli. CONCLUSION: Our study suggests that furin, rather than PC1/3, is positioned to process proglucagon into GLP-1, and despite coming from the same precursor molecule, GLP-1 and glucagon are separately packaged in primary human alpha cells.
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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 | 0.000 |
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".