Fatty Acid Signaling in the β-Cell and Insulin Secretion
Bibliographic record
Abstract
Fatty acids (FAs) and other lipid molecules are important for many cellular functions, including vesicle exocytosis. For the pancreatic beta-cell, while the presence of some FAs is essential for glucose-stimulated insulin secretion, FAs have enormous capacity to amplify glucose-stimulated insulin secretion, which is particularly operative in situations of beta-cell compensation for insulin resistance. In this review, we propose that FAs do this via three interdependent processes, which we have assigned to a "trident model" of beta-cell lipid signaling. The first two arms of the model implicate intracellular metabolism of FAs, whereas the third is related to membrane free fatty acid receptor (FFAR) activation. The first arm involves the AMP-activated protein kinase/malonyl-CoA/long-chain acyl-CoA (LC-CoA) signaling network in which glucose, together with other anaplerotic fuels, increases cytosolic malonyl-CoA, which inhibits FA partitioning into oxidation, thus increasing the availability of LC-CoA for signaling purposes. The second involves glucose-responsive triglyceride (TG)/free fatty acid (FFA) cycling. In this pathway, glucose promotes LC-CoA esterification to complex lipids such as TG and diacylglycerol, concomitant with glucose stimulation of lipolysis of the esterification products, with renewal of the intracellular FFA pool for reactivation to LC-CoA. The third arm involves FFA stimulation of the G-protein-coupled receptor GPR40/FFAR1, which results in enhancement of glucose-stimulated accumulation of cytosolic Ca2+ and consequently insulin secretion. It is possible that FFA released by the lipolysis arm of TG/FFA cycling is partly "secreted" and, via an autocrine/paracrine mechanism, is additive to exogenous FFAs in activating the FFAR1 pathway. Glucose-stimulated release of arachidonic acid from phospholipids by calcium-independent phospholipase A2 and/or from TG/FFA cycling may also be involved. Improved knowledge of lipid signaling in the beta-cell will allow a better understanding of the mechanisms of beta-cell compensation and failure 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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".