Overexpression of ZAC impairs glucose‐stimulated insulin translation and secretion in clonal pancreatic beta‐cells
Bibliographic record
Abstract
BACKGROUND: ZAC (Zinc finger protein that regulates apoptosis and cell-cycle arrest) is a candidate gene for transient neonatal diabetes mellitus (TNDM). This condition involves severe insulin deficiency at birth that reverses over weeks or months but may relapse with diabetes recurring in later life. ZAC overexpression in transgenic mice has previously been shown to result in complex changes in both beta-cell mass and possibly function. The present study therefore aimed to examine the role of ZAC in beta-cell function in vitro, independent of the confounder of a reduced beta-cell mass at birth. METHODS: Overexpression of ZAC was achieved through the tetracycline-regulatable system in the beta-cell line, INS-1. RESULTS: We found that ZAC overexpression exerted no significant effect on proliferation in this transformed cell line at any of the glucose concentrations examined. By contrast, glucose-stimulated insulin secretion was impaired through a mechanism downstream of cytosolic Ca(2+) increases. Furthermore, glucose-stimulated proinsulin biosynthesis was inhibited despite an increase in insulin transcript level. Finally, we found that glucose downregulated ZAC expression in both INS-1 cells and primary mouse islets. CONCLUSIONS: These results indicate that ZAC is a negative regulator of the acute stimulatory effects of glucose on beta-cells, and provide a possible explanation for both insulin deficiency in the neonate and the later relapse of diabetes in patients with transient neonatal diabetes mellitus cases.
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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".