Insulin increases FA uptake and esterification but reduces lipid utilization in isolated contracting muscle
Bibliographic record
Abstract
We examined the effect of insulin on the synthesis and degradation of muscle lipid pools [phospholipid (PL), diacylglycerol (DG), triacylglycerol (TG)] and palmitate oxidation in isolated resting and contracting (20 tetani/min) soleus muscles. Lipid metabolism was monitored using the previously defined pulse-chase procedure. At rest, insulin significantly increased total palmitate uptake into soleus muscle (+49%, P < 0.05), corresponding to enhanced DG (+60%, P < 0.05) and TG (+61%, P < 0.05) esterification, but blunted palmitate oxidation (-38%, P < 0.05) and TG hydrolysis (-34%, P < 0.05). During muscle contraction, when total palmitate uptake was increased, insulin further enhanced uptake (+21%, P < 0.05) and esterification of fatty acids (FA) to PL (+73%, P < 0.05), DG (+19%, P < 0.05), and TG (+161%, P < 0.01). Despite a profound shift in the relative partitioning of FA away from esterification and toward oxidation during contraction, the increase in palmitate oxidation and TG hydrolysis was significantly blunted by insulin [oxidation, -24% (P = 0.05); hydrolysis, -83% (P < 0.01)]. The effects of insulin on FA esterification (stimulation) and oxidation (inhibition) during contraction were reduced in the presence of the phosphatidylinositol 3-kinase inhibitor LY-294002. In summary, the effects of insulin and contraction on palmitate uptake and esterification are additive, while insulin opposes the stimulatory effect of contraction on FA oxidation and TG hydrolysis. Insulin's modulatory effects on muscle FA metabolism during contraction are mediated at least in part through phosphatidylinositol 3-kinase.
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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) | 0.001 | 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".