A Glycine-Insulin Autocrine Feedback Loop Enhances Insulin Secretion From Human β-Cells and Is Impaired in Type 2 Diabetes
Bibliographic record
Abstract
The secretion of insulin from pancreatic islet β-cells is critical for glucose homeostasis. Disrupted insulin secretion underlies almost all forms of diabetes, including the most common form, type 2 diabetes (T2D). The control of insulin secretion is complex and affected by circulating nutrients, neuronal inputs, and local signaling. In the current study, we examined the contribution of glycine, an amino acid and neurotransmitter that activates ligand-gated Cl(-) currents, to insulin secretion from islets of human donors with and without T2D. We find that human islet β-cells express glycine receptors (GlyR), notably the GlyRα1 subunit, and the glycine transporter (GlyT) isoforms GlyT1 and GlyT2. β-Cells exhibit significant glycine-induced Cl(-) currents that promote membrane depolarization, Ca(2+) entry, and insulin secretion from β-cells from donors without T2D. However, GlyRα1 expression and glycine-induced currents are reduced in β-cells from donors with T2D. Glycine is actively cleared by the GlyT expressed within β-cells, which store and release glycine that acts in an autocrine manner. Finally, a significant positive relationship exists between insulin and GlyR, because insulin enhances the glycine-activated current in a phosphoinositide 3-kinase-dependent manner, a positive feedback loop that we find is completely lost in β-cells from donors with T2D.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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 teacher head, 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".