Electrophysiological identification of mouse islet α-cells: From isolated single α-cells to in situ assessment within pancreas slices
Bibliographic record
Abstract
Investigation of α-cells has long been constrained by their scarce population and localization at the islet mantle which exposes α-cells to injury by conventional islet isolation and dispersion to single cells that employ damaging enzymatic and mechanical means. To surmount these limitations, we recently reported employing the pancreas slice preparation which enables highly efficient acute in situ electrophysiological (patch clamp) examination of α-cells within its unperturbed native social environment with preserved paracrine regulation. In this review, we compare the electrophysiological properties of α-cells in these three preparations, and discuss the current view of glucose regulation of α-cells. We discuss current genetic mouse models that flurophore-tagged α-cells (GYY) and β-cells (MIP-GFP) which can reliably identify islet cells to facilitate their study. Combining these strategies should enable future studies directed at the precise assessment of the perturbation in intrinsic and paracrine regulation of α-cells contributing to abnormal glucose homeostasis in 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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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".