In Situ Electrophysiological Examination of Pancreatic α Cells in the Streptozotocin-Induced Diabetes Model, Revealing the Cellular Basis of Glucagon Hypersecretion
Bibliographic record
Abstract
Early-stage type 1 diabetes (T1D) exhibits hyperglucagonemia by undefined cellular mechanisms. Here we characterized α-cell voltage-gated ion channels in a streptozotocin (STZ)-induced diabetes model that lead to increased glucagon secretion mimicking T1D. GYY mice expressing enhanced yellow fluorescence protein in α cells were used to identify α cells within pancreas slices. Mice treated with low-dose STZ exhibited hyperglucagonemia, hyperglycemia, and glucose intolerance, with 71% reduction of β-cell mass. Although α-cell mass of STZ-treated mice remained unchanged, total pancreatic glucagon content was elevated, coinciding with increase in size of glucagon granules. Pancreas tissue slices enabled in situ examination of α-cell electrophysiology. α cells of STZ-treated mice exhibited the following: 1) increased exocytosis (serial depolarization-induced capacitance), 2) enhanced voltage-gated Na(+) current density, 3) reduced voltage-gated K(+) current density, and 4) increased action potential (AP) amplitude and firing frequency. Hyperglucagonemia in STZ-induced diabetes is thus likely due to increased glucagon content arising from enlarged glucagon granules and increased AP firing frequency and amplitude coinciding with enhanced Na(+) and reduced K(+) currents. These alterations may prime α cells in STZ-treated mice for more glucagon release per cell in response to low glucose stimulation. Thus, our study provides the first insight that STZ treatment sensitizes release mechanisms of α cells.
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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".