β-cell deletion of the PKm1 and PKm2 isoforms of pyruvate kinase in mice reveals their essential role as nutrient sensors for the KATP channel
Bibliographic record
Abstract
Pyruvate kinase (PK) and the phosphoenolpyruvate (PEP) cycle play key roles in nutrient-stimulated K ATP channel closure and insulin secretion. To identify the PK isoforms involved, we generated mice lacking β-cell PKm1, PKm2, and mitochondrial PEP carboxykinase (PCK2) that generates mitochondrial PEP. Glucose metabolism was found to generate both glycolytic and mitochondrially derived PEP, which triggers K ATP closure through local PKm1 and PKm2 signaling at the plasma membrane. Amino acids, which generate mitochondrial PEP without producing glycolytic fructose 1,6-bisphosphate to allosterically activate PKm2, signal through PKm1 to raise ATP/ADP, close K ATP channels, and stimulate insulin secretion. Raising cytosolic ATP/ADP with amino acids is insufficient to close K ATP channels in the absence of PK activity or PCK2, indicating that K ATP channels are primarily regulated by PEP that provides ATP via plasma membrane-associated PK, rather than mitochondrially derived ATP. Following membrane depolarization, the PEP cycle is involved in an ‘off-switch’ that facilitates K ATP channel reopening and Ca 2+ extrusion, as shown by PK activation experiments and β-cell PCK2 deletion, which prolongs Ca 2+ oscillations and increases insulin secretion. In conclusion, the differential response of PKm1 and PKm2 to the glycolytic and mitochondrial sources of PEP influences the β-cell nutrient response, and controls the oscillatory cycle regulating insulin secretion.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".