Insulin Stimulates Mitochondrial Fusion and Function in Cardiomyocytes via the Akt-mTOR-NFκB-Opa-1 Signaling Pathway
Bibliographic record
Abstract
Insulin regulates heart metabolism through the regulation of insulin-stimulated glucose uptake. Studies have indicated that insulin can also regulate mitochondrial function. Relevant to this idea, mitochondrial function is impaired in diabetic individuals. Furthermore, the expression of Opa-1 and mitofusins, proteins of the mitochondrial fusion machinery, is dramatically altered in obese and insulin-resistant patients. Given the role of insulin in the control of cardiac energetics, the goal of this study was to investigate whether insulin affects mitochondrial dynamics in cardiomyocytes. Confocal microscopy and the mitochondrial dye MitoTracker Green were used to obtain three-dimensional images of the mitochondrial network in cardiomyocytes and L6 skeletal muscle cells in culture. Three hours of insulin treatment increased Opa-1 protein levels, promoted mitochondrial fusion, increased mitochondrial membrane potential, and elevated both intracellular ATP levels and oxygen consumption in cardiomyocytes in vitro and in vivo. Consequently, the silencing of Opa-1 or Mfn2 prevented all the metabolic effects triggered by insulin. We also provide evidence indicating that insulin increases mitochondrial function in cardiomyocytes through the Akt-mTOR-NFκB signaling pathway. These data demonstrate for the first time in our knowledge that insulin acutely regulates mitochondrial metabolism in cardiomyocytes through a mechanism that depends on increased mitochondrial fusion, Opa-1, and the Akt-mTOR-NFκB pathway.
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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) | 0.000 | 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) | 0.001 | 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".