Misfolded Proinsulin Affects Bystander Proinsulin in Neonatal Diabetes
Bibliographic record
Abstract
It has previously been shown that misfolded mutant Akita proinsulin in the endoplasmic reticulum engages directly in protein complexes either with nonmutant proinsulin or with "hProCpepGFP" (human proinsulin bearing emerald-GFP within the C-peptide), impairing the trafficking of these "bystander" proinsulin molecules (Liu, M., Hodish, I., Rhodes, C. J., and Arvan, P. (2007) Proc. Natl. Acad. Sci. U.S.A. 104, 15841-15846). Herein, we generated transgenic mice, which, in addition to expressing endogenous proinsulin, exhibit beta-cell-specific expression of hProCpepGFP via the Ins1 promoter. In these mice, hProCpepGFP protein levels are physiologically regulated, and hProCpepGFP is packaged and processed to CpepGFP that is co-stored in beta-secretory granules. Visualization of CpepGFP fluorescence provides a quantifiable measure of pancreatic islet insulin content that can be followed in live animals in states of health and disease. We examined loss of pancreatic insulin in hProCpepGFP transgenic mice mated to Akita mice that develop neonatal diabetes because of the expression of misfolded proinsulin. Loss of bystander insulin in Akita animals is detected initially as a block in CpepGFP/insulin production with intracellular accumulation of the precursor, followed ultimately by loss of pancreatic beta-cells. The data support that misfolded proinsulin perturbs bystander proinsulin in the endoplasmic reticulum, leading to beta-cell failure.
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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 | 0.001 |
| 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".