Regulation of pancreatic PC1 and PC2 associated with increased glucagon-like peptide 1 in diabetic rats
Bibliographic record
Abstract
The pancreatic processing enzymes, PC1 and PC2, convert proinsulin to insulin and convert proglucagon to glucagon and glucagon-like peptide 1 (GLP-1). We examined the effect of streptozotocin (STZ) treatment on the regulation of these enzymes and the production of insulin, glucagon, and GLP-1 in the rat. Pancreatic PC1 and PC2 mRNA increased >2-fold and >4-fold, respectively, in rats receiving intraperitoneal STZ (50 mg/kg) daily for 5 days. Immunocytochemistry revealed that, although pancreatic islet cells in the STZ-treated rats were sparse and atrophic PC1, PC2, glucagon, and GLP-1 immunoreactivity increased dramatically in the remaining islet cells. Heightened PC1 and PC2 expression was seen in cells expressing glucagon but not in insulin-expressing cells. Furthermore, in STZ-treated rats, bioactive GLP-1(7-36 amide) accumulated in pancreatic extracts and serum 3- and 2.5-fold, respectively, over control animals. This treatment also caused a 2-fold increase in the ratio of amidated forms of GLP-1 immunoreactivity to total glucagon immunoreactivity in the pancreas but did not affect the ratio of proinsulin to insulin. We conclude that hyperglycemic rats have an increased expression of prohormone converting enzymes in islet alpha cells, leading to an increase in amidated GLP-1, which can then exert an insulinotropic effect on the remaining beta 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
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".