Skeletal Muscle Lipogenic Protein Expression Is Not Different Between Lean And Obese Humans; A Potential Factor In Ceramide Accumulation.
Bibliographic record
Abstract
It is well known that intramuscular triacylglycerol (TAG) content is increased in obesity and is associated with the development of insulin resistance. However, this relationship is not likely causal in nature. Recent evidence has suggested that fatty acid storage as TAG represents a metabolically safe storage form of lipids. Fatty acid (FA) transport is increased in skeletal muscle of obese humans but little is known about the role of lipogenic proteins in lipid accumulation in skeletal muscle. PURPOSE: The purpose of this study was to compare the expression of lipid synthesis proteins and ceramide and diacylglycerol (DAG) content in skeletal muscle of lean and obese humans. We hypothesized that the expression of lipid synthesis proteins and ceramide and DAG content would be higher in skeletal muscle from obese humans. METHODS: The expression of proteins involved in lipid synthesis (steroyl coA desaturase-1 (SCD-1), steroyl retinol binding protein-1c (SREBP-1c), mitochondrial glycerol-3-phosphate acyltransferase (mtGPAT), diacylglycerol acyltransferase-1 (DGAT-1), lipin-1, and serine palmitoyltransferase (SPT) and linking ceramide (Protein phosphotase 2A (PP2A)) and DAG (DAG responsive isoforms of protein kinase C (PKC)) to insulin resistance was measured in rectus abdominus muscle samples obtained from lean and obese humans (BMI lean vs. obese: 24.0 ± 0.4 vs. 37.0 ± 1.6 kg/m2). Skeletal muscle ceramide and DAG content was also assessed in these populations. RESULTS: There was no difference in the expression of any lipogenic proteins measured between lean and obese humans. Total ceramide content was significantly higher in skeletal muscle from obese (lean vs. obese, 529.4 ± 54.8 vs. 672.4 ± 57.4 nmol/g*, p<0.05) humans, but there was no difference in total DAG content (lean vs. obese, 2244.1 ± 278.2 vs. 1941.4 ± 165.0 nmol/g). PP2A expression was significantly increased in skeletal muscle from obese (p<0.05), but there was no difference in the expression of any isoforms of PKC. CONCLUSION: We suggest that in skeletal muscle of obese humans, there is a mismatch between FA influx and utilization, and the lack of a metabolic response to upregulate lipogenic protein expression leads to the accumulation of FA in more reactive lipid pools such as ceramide.
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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 | 0.000 |
| 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".