Characterization and functional role of voltage gated cation conductances in the glucagon‐like peptide‐1 secreting GLUTag cell line
Bibliographic record
Abstract
Glucagon-like peptide-1 (GLP-1) is released from intestinal L-cells in response to nutrient ingestion. It is currently under therapeutic evaluation because it enhances insulin secretion in type 2 diabetes. Previous studies using the GLP-1 secreting cell line GLUTag have shown that the cells are electrically active, and that the action potential frequency is regulated by nutrients. In this study we characterize voltage gated currents underlying this electrical activity and correlate the electrophysiological findings with gene expression determined by microarrays. Whole cell voltage clamp experiments designed to separate different ionic components revealed rapidly inactivating sodium currents sensitive to tetrodotoxin, calcium currents sensitive to nifedipine and omega-conotoxin GVIA, and sustained as well as rapidly inactivating potassium currents, which were sensitive to TEA and 4-AP, respectively. In perforated patch experiments we also observed hyperpolarization-activated currents which were inhibited by ZD7288. The amplitude of the sodium current was approximately 10 times that of the other depolarizing currents and tetrodotoxin abolished action potential firing. In secretion experiments, however, nifedipine, but not tetrodotoxin, omega-conotoxin GVIA or ZD7288, inhibited glucose-induced GLP-1 release. Consistent with this finding, the intracellular Ca2+ response to glucose was impaired by nifedipine but not by tetrodotoxin. Thus, in GLUTag cells, GLP-1 release is not dependent on the firing of Na+-carrying action potentials but requires membrane depolarization and Ca2+ entry through L-type Ca2+ channels. Understanding the characteristics of the currents and the molecular identification of the underlying channels in GLP-1 secreting cells might facilitate the development of agents to enhance GLP-1 secretion in vivo.
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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) | 0.001 | 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".