Deletion of carboxypeptidase E in beta cells disrupts proinsulin processing and alters beta cell identity in mice
Bibliographic record
Abstract
Abstract Carboxypeptidase E (CPE) facilitates the conversion of prohormones into mature hormones and is highly expressed in multiple neuroendocrine tissues. Carriers of CPE mutations have elevated plasma proinsulin and develop severe obesity and hyperglycemia. We aimed to determine whether loss of Cpe in pancreatic beta cells disrupts proinsulin processing and accelerates development of diabetes and obesity in mice. Pancreatic beta cell-specific Cpe knockout mice (β Cpe KO; Cpe fl/fl x Ins1 Cre/+ ) lack mature insulin granules and have elevated proinsulin in plasma; however, glucose-and KCl-stimulated insulin secretion in β Cpe KO islets remained intact. High fat diet-fed β Cpe KO mice showed comparable weight gain and glucose tolerance compared to Wt littermates. Notably, beta-cell area was increased in chow-fed β Cpe KO mice and beta-cell replication was elevated in β Cpe KO islets. Transcriptomic analysis of β Cpe KO beta cells revealed elevated glycolysis and Hif1α -target gene expression. Upon high glucose challenge, beta cells from β Cpe KO mice showed reduced mitochondrial membrane potential, increased reactive oxygen species, reduced MafA , and elevated Aldh1a3 transcript levels. Following multiple low-dose streptozotocin treatment, β Cpe KO mice had accelerated hyperglycemia with reduced beta-cell insulin and Glut2 expression. These findings suggest that Cpe and proper proinsulin processing are critical in maintaining beta cell function during the development of diabetes.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".