Cytokine regulation of skeletal muscle fatty acid metabolism: effect of interleukin-6 and tumor necrosis factor-α
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Bibliographic record
Abstract
IL-6 and TNF-alpha have been associated with insulin resistance and type 2 diabetes. Furthermore, abnormalities in muscle fatty acid (FA) metabolism are strongly associated with the development of insulin resistance. However, few studies have directly examined the effects of either IL-6 or TNF-alpha on skeletal muscle FA metabolism. Here, we used a pulse-chase technique to determine the effect of IL-6 (50-5,000 pg/ml) and TNF-alpha (50-5,000 pg/ml) on FA metabolism in isolated rat soleus muscle. IL-6 (5,000 pg/ml) increased exogenous and endogenous FA oxidation by approximately 50% (P < 0.05) but had no effect on FA uptake or incorporation of FA into endogenous lipid pools. In contrast, TNF-alpha had no effect on FA oxidation but increased FA incorporation into diacylglycerol (DAG) by 45% (P < 0.05). When both IL-6 (5,000 pg/ml) and insulin (10 mU/ml) were present, IL-6 attenuated insulin's suppressive effect on FA oxidation, increasing exogenous FA oxidation (+37%, P < 0.05). Furthermore, in the presence of insulin, IL-6 reduced the esterification of FA to triacylglycerol by 22% (P < 0.05). When added in combination with IL-6 or leptin (10 microg/ml), the TNF-alpha-induced increase in DAG synthesis was inhibited. In conclusion, the results demonstrate that IL-6 plays an important role in regulating fat metabolism in muscle, increasing rates of FA oxidation, and attenuating insulin's lipogenic effects. In contrast, TNF-alpha had no effect on FA oxidation but increased FA incorporation into DAG, which may be involved in the development of TNF-alpha-induced insulin resistance in skeletal muscle.
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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) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it