MEDICA 16 Inhibits Hepatic Acetyl-CoA Carboxylase and Reduces Plasma Triacylglycerol Levels in Insulin-Resistant JCR
Bibliographic record
Abstract
Intracellular triacylglycerol (TG) content of liver and skeletal muscle contributes to insulin resistance, and a significant correlation exists between TG content and the development of insulin resistance. Because acetyl-CoA carboxylase (ACC) is the rate-limiting enzyme for liver fatty acid biosynthesis and a key regulator of muscle fatty acid oxidation, we examined whether ACC plays a role in the accumulation of intracellular TG. We also determined the potential role of 5'-AMP-activated protein kinase (AMPK) in this process, since it can phosphorylate and inhibit ACC activity in both liver and muscle. TG content, ACC, and AMPK were examined in the liver and skeletal muscle of insulin-resistant JCR:LA-cp rats during the time frame when insulin resistance develops. At 12 weeks of age, there was a threefold elevation in liver TG content and a sevenfold elevation in skeletal muscle TG content. Hepatic ACC activity was significantly elevated in 12-week-old JCR:LA-cp rats compared with lean age-matched controls (8.75 +/- 0.53 vs. 3.30 +/- 0.18 nmol. min(-1). mg(-1), respectively), even though AMPK activity was also increased. The observed increase in hepatic ACC activity was accompanied by a 300% increase in ACC protein expression. There were no significant differences in ACC activity, ACC protein expression, or AMPK activity in the skeletal muscle of the 12-week JCR:LA-cp rats. Treatment of 12-week JCR:LA-cp rats with MEDICA 16 (an ATP-citrate lyase inhibitor) resulted in a decrease in hepatic ACC and AMPK activities, but had no effect on skeletal muscle ACC and AMPK. Our data suggest that alterations in ACC or AMPK activity in muscle do not contribute to the development of insulin resistance. However, increased liver ACC activity in the JCR:LA-cp rat appears to contribute to the development of lipid abnormalities, although this increase does not appear to occur secondary to a decrease in AMPK activity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".