ER calcium stores contribute to glucose-induced Ca2+ waves and intercellular connectivity in mouse pancreatic islets
Bibliographic record
Abstract
Defective insulin secretion is a hallmark of diabetes mellitus. Glucose-induced Ca 2+ oscillations are critical for the stimulation of insulin secretion, though the mechanisms through which these propagate across the islet are poorly understood. Here, we use beta cell-targeted GCaMP6f to explore the role of endoplasmic reticulum (ER) Ca 2+ mobilization in response to submaximal (11mM) or hyperglycemic (25mM) glucose, mimicking diabetes. Inhibition of inositol 1,4,5-trisphosphate (IP 3 ) receptors, and other ion channels, with 2-aminoethoxydiphenyl borate (2-APB), had minimal effects on the initial peak or intercellular connectivity provoked by 11mM glucose. However, 2-APB lowered subsequent glucose-induced cytosolic Ca 2+ increases and connectivity at both 11 and 25mM glucose. Unexpectedly, the activation of IP 3 receptors with the muscarinic acetylcholine receptor agonist carbachol had minimal impact on the initial peak elicited by 11 mM glucose, but Ca 2+ waves at 11 and 25 mM glucose were more poorly coordinated. To determine whether ER calcium mobilization was sufficient to initiate Ca 2+ waves we next blocked sarco(endo)plasmic Ca 2+ ATPase (SERCA) pumps with thapsigargin, whilst preventing plasma membrane depolarization with the K ATP -channel opener, diazoxide. Under these conditions, an initial cytosolic Ca 2+ increase was followed by secondary Ca 2+ waves that subsided slowly. The application of carbachol alongside diazoxide still enhanced Ca 2+ dynamics, though activity was uncoordinated. After genetic deletion of SERCA2 in beta cells, Ca 2+ wave frequency, but not connectivity, were lowered. Our results show that ER Ca 2+ mobilization plays a relatively minor role in the initiation and propagation of Ca 2+ waves in response to glucose but is needed for sustained Ca 2+ waves.
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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".