Succinate Is a Preferential Metabolic Stimulus-Coupling Signal for Glucose-Induced Proinsulin Biosynthesis Translation
Bibliographic record
Abstract
The secondary signals emanating from increased glucose metabolism, which lead to specific increases in proinsulin biosynthesis translation, remain elusive. It is known that signals for glucose-stimulated insulin secretion and proinsulin biosynthesis diverge downstream of glycolysis. Consequently, the mitochondrial products ATP, Krebs cycle intermediates, glutamate, and acetoacetate were investigated as candidate stimulus-coupling signals specific for glucose-induced proinsulin biosynthesis in rat islets. Decreasing ATP levels by oxidative phosphorylation inhibitors showed comparable effects on proinsulin biosynthesis and total protein synthesis. Although it is a cofactor, ATP is unlikely to be a metabolic stimulus-coupling signal specific for glucose-induced proinsulin biosynthesis. Neither glutamic acid methyl ester nor acetoacetic acid methyl ester showed a specific effect on glucose-stimulated proinsulin biosynthesis. Interestingly, among Krebs cycle intermediates, only succinic acid monomethyl ester specifically stimulated proinsulin biosynthesis. Malonic acid methyl ester, an inhibitor of succinate dehydrogenase, also specifically increased glucose-induced proinsulin biosynthesis without affecting islet ATP levels or insulin secretion. Glucose caused a 40% increase in islet intracellular succinate levels, but malonic acid methyl ester showed no further effect, probably due to efficient conversion of succinate to succinyl-CoA. In this regard, a GTP-dependent succinyl-CoA synthetase activity was found in cytosolic fractions of pancreatic islets. Thus, succinate and/or succinyl-CoA appear to be preferential metabolic stimulus-coupling factors for glucose-induced proinsulin biosynthesis translation.
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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) | 0.000 | 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) | 0.002 | 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".