Inhibition of β-Cell Sodium-Calcium Exchange Enhances Glucose-Dependent Elevations in Cytoplasmic Calcium and Insulin Secretion
Bibliographic record
Abstract
OBJECTIVE: The sodium-calcium exchanger isoform 1 (NCX1) regulates cytoplasmic calcium (Ca(2+)(c)) required for insulin secretion in beta-cells. NCX1 is alternatively spliced, resulting in the expression of splice variants in different tissues such as NCX1.3 and -1.7 in beta-cells. As pharmacological inhibitors of NCX1 splice variants are in development, the pharmacological profile of beta-cell NCX1.3 and -1.7 and the cellular effects of NCX1 inhibition were investigated. RESEARCH DESIGN AND METHODS: The patch-clamp technique was used to examine the pharmacological profile of the NCX1 inhibitor KB-R7943 on recombinant NCX1.3 and -1.7 activity. Ca(2+) imaging and membrane capacitance were used to assess the effects of KB-R7943 on Ca(2+)(c) and insulin secretion in mouse and human beta-cells and islets. RESULTS: NCX1.3 and -1.7 calcium extrusion (forward-mode) activity was approximately 16-fold more sensitive to KB-R7943 inhibition compared with cardiac NCX1.1 (IC(50s) = 2.9 and 2.4 vs. 43.0 micromol/l, respectively). In single mouse/human beta-cells, 1 micromol/l KB-R7943 increased insulin granule exocytosis but was without effect on alpha-cell glucagon granule exocytosis. KB-R7943 also augmented sulfonylurea and glucose-stimulated Ca(2+)(c) levels and insulin secretion in mouse and human islets, although KB-R7943 was without effect under nonstimulated conditions. CONCLUSIONS: Islet NCX1 splice variants display a markedly greater sensitivity to pharmacological inhibition than the cardiac NCX1.1 splice variant. NCX1 inhibition resulted in glucose-dependent increases in Ca(2+)(c) and insulin secretion in mouse and human islets. Thus, we identify beta-cell NCX1 splice variants as targets for the development of novel glucose-sensitive insulinotropic drugs for type 2 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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".