Glucose and Endoplasmic Reticulum Calcium Channels Regulate HIF-1β via Presenilin in Pancreatic β-Cells
Bibliographic record
Abstract
Pancreatic beta-cell death is a critical event in type 1 diabetes, type 2 diabetes, and clinical islet transplantation. We have previously shown that prolonged block of ryanodine receptor (RyR)-gated release from intracellular Ca(2+) stores activates calpain-10-dependent apoptosis in beta-cells. In the present study, we further characterized intracellular Ca(2+) channel expression and function in human islets and the MIN6 beta-cell line. All three RyR isoforms were identified in human islets and MIN6 cells, and these endoplasmic reticulum channels were observed in close proximity to mitochondria. Blocking RyR channels, but not sarco/endoplasmic reticulum ATPase (SERCA) pumps, reduced the ATP/ADP ratio. Blocking Ca(2+) flux through RyR or inositol trisphosphate receptor channels, but not SERCA pumps, increased the expression of hypoxia-inducible factor (HIF-1beta). Moreover, inhibition of RyR or inositol trisphosphate receptor channels, but not SERCA pumps, increased the expression of presenilin-1. Both HIF-1beta and presenilin-1 expression were also induced by low glucose. Overexpression of presenilin-1 increased HIF-1beta, suggesting that HIF is downstream of presenilin. Our results provide the first evidence of a presenilin-HIF signaling network in beta-cells. We demonstrate that this pathway is controlled by Ca(2+) flux through intracellular channels, likely via changes in mitochondrial metabolism and ATP. These findings provide a mechanistic understanding of the signaling pathways activated when intracellular Ca(2+) homeostasis and metabolic activity are suppressed in diabetes and islet transplantation.
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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) | 0.000 | 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".