Excessive Autophagy Activation and Increased Apoptosis Are Associated with Palmitic Acid-Induced Cardiomyocyte Insulin Resistance
Bibliographic record
Abstract
Diabetic cardiomyopathy (DCM) remains the major cause of death associated with diabetes. Researchers have demonstrated the importance of impaired cardiac insulin signaling in this process. Insulin resistance (IR) is an important predictor of DCM. Previous studies examining the dynamic changes in autophagy during IR have yielded inconsistent results. This study aimed to investigate the dynamic changes in autophagy and apoptosis in the rat H9c2 cardiomyocyte IR model. H9c2 cells were treated with 500 μM palmitic acid (PA) for 24 hours, resulting in the induction of IR. To examine autophagy, monodansylcadaverine staining, GFP-LC3 puncta confocal observation, and Western blot analysis of LC3I-to-LC3II conversion were used. Results of these studies showed that autophagic acid vesicles increased in numbers during the first 24 hours and then decreased by 36 hours after PA treatment. Western blot analysis showed that treatment of H9c2 cells with 500 μM PA for 24 hours decreased the expression of Atg12-Atg5, Atg16L1, Atg3, and PI3Kp85. Annexin V/PI flow cytometry revealed that PA exposure for 24 hours increased the rate of apoptosis. Together, this study demonstrates that PA induces IR in H9c2 cells and that this process is accompanied by excessive activation of autophagy and increases in apoptosis.
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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 | 0.001 | 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".