Kinetic modelling of <i>β</i> ‐cell metabolism reveals control points in the insulin‐regulating pyruvate cycling pathways
Bibliographic record
Abstract
Abstract Insulin, a key hormone in the regulation of glucose homoeostasis, is secreted by pancreatic β ‐cells in response to elevated glucose levels. Insulin is released in a biphasic manner in response to glucose metabolism in β ‐cells. The first phase of insulin secretion is triggered by an increase in the ATP:ADP ratio; the second phase occurs in response to both a rise in ATP:ADP and other key metabolic signals, including a rise in the NADPH:NADP + ratio. Experimental evidence indicates that pyruvate‐cycling pathways play an important role in the elevation of the NADPH:NADP + ratio in response to glucose. The authors developed a kinetic model for the tricarboxylic acid cycle and pyruvate cycling pathways. The authors successfully validated the model against experimental observations and performed a sensitivity analysis to identify key regulatory interactions in the system. The model predicts that the dicarboxylate carrier and the pyruvate transporter are the most important regulators of pyruvate cycling and NADPH production. In contrast, the analysis showed that variation in the pyruvate carboxylase flux was compensated by a response in the activity of mitochondrial isocitrate dehydrogenase (ICD m ) resulting in minimal effect on overall pyruvate cycling flux. The model predictions suggest starting points for further experimental investigation, as well as potential drug targets for the treatment of type 2 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".