Depletion of Mitochondrial DNA Causes Impaired Glucose Utilization and Insulin Resistance in L6 GLUT4myc Myocytes
Bibliographic record
Abstract
Mitochondrial dysfunction contributes to a number of human diseases, such as hyperlipidemia, obesity, and diabetes. The mutation and reduction of mitochondrial DNA (mtDNA) have been suggested as factors in the pathogenesis of diabetes. To elucidate the association of cellular mtDNA content and insulin resistance, we produced L6 GLUT4myc myocytes depleted of mtDNA by long term treatment with ethidium bromide. L6 GLUT4myc cells cultured with 0.2 mug/ml ethidium bromide (termed depleted cells) revealed a marked decrease in cellular mtDNA and ATP content, concomitant with a lack of mRNAs encoded by mtDNA. Interestingly, the mtDNA-depleted cells showed a drastic decrease in basal and insulin-stimulated glucose uptake, indicating that L6 GLUT4myc cells develop impaired glucose utilization and insulin resistance. The repletion of mtDNA normalized basal and insulin-stimulated glucose uptake. The mRNA level and expression of insulin receptor substrate (IRS)-1 associated with insulin signaling were decreased by 76 and 90% in the depleted cells, respectively. The plasma membrane (PM) GLUT4 in the basal state was decreased, and the insulin-stimulated GLUT4 translocation to the PM was drastically reduced by mtDNA depletion. Moreover, insulin-stimulated phosphorylation of IRS-1 and Akt2/protein kinase B were drastically reduced in the depleted cells. Those changes returned to control levels after mtDNA repletion. Taken together, our data suggest that PM GLUT4 content and insulin signal pathway intermediates are modulated by the alteration of cellular mtDNA content, and the reductions in the expression of IRS-1 and insulin-stimulated phosphorylation of IRS-1 and Akt2/protein kinase B are associated with insulin resistance in the mtDNA-depleted L6 GLUT4myc myocytes.
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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 | 0.001 |
| 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".