Revisiting Proinsulin Processing: Evidence That Human β-Cells Process Proinsulin With Prohormone Convertase (PC) 1/3 but Not PC2
Bibliographic record
Abstract
Insulin is first produced in pancreatic β-cells as the precursor prohormone proinsulin. Defective proinsulin processing has been implicated in the pathogenesis of both type 1 and type 2 diabetes. Though there is substantial evidence that mouse β-cells process proinsulin using prohormone convertase 1/3 (PC1/3) and then prohormone convertase 2 (PC2), this finding has not been verified in human β-cells. Immunofluorescence with validated antibodies revealed that there was no detectable PC2 immunoreactivity in human β-cells and little PCSK2 mRNA by in situ hybridization. Similarly, rat β-cells were not immunoreactive for PC2. In all histological experiments, PC2 immunoreactivity in neighboring α-cells acted as a positive control. In donors with type 2 diabetes, β-cells had elevated PC2 immunoreactivity, suggesting that aberrant PC2 expression may contribute to impaired proinsulin processing in β-cells of patients with diabetes. To support histological findings using a biochemical approach, human islets were used for pulse-chase experiments. Despite inhibition of PC2 function by temperature blockade, brefeldin A, chloroquine, and multiple inhibitors that blocked production of mature glucagon from proglucagon, β-cells retained the ability to produce mature insulin. Conversely, suppression of PC1/3 blocked processing of proinsulin but not proglucagon. By demonstrating that healthy human β-cells process proinsulin by PC1/3 but not PC2, we suggest that there is a need to revise the long-standing theory of proinsulin processing.
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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 | 0.001 | 0.001 |
| 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".