Relationship of C5L2 Receptor to Skeletal Muscle Substrate Utilization
Bibliographic record
Abstract
OBJECTIVE: To investigate the role of Acylation Stimulating Protein (ASP) receptor C5L2 in skeletal muscle fatty acid accumulation and metabolism as well as insulin sensitivity in both mice and human models of diet-induced insulin resistance. DESIGN AND METHODS: Male wildtype (WT) and C5L2 knockout (KO) mice were fed a low (LFD) or a high (HFD) fat diet for 10 weeks. Intramyocellular lipid (IMCL) accumulation (by oil red O staining) and beta-oxidation HADH enzyme activity were determined in skeletal muscle. Mitochondria were isolated from hindleg muscles for high-resolution respirometry. Muscle C5L2 protein content was also determined in obese type 2 diabetics and age- and BMI matched men. RESULTS: IMCL levels were increased by six-fold in C5L2KO-HFD compared to WT-HFD mice (p<0.05) and plasma insulin levels were markedly increased in C5L2KO-HFD mice (twofold, p<0.05). Muscle HADH activity was elevated in C5L2KO-LFD mice (+75%, p<0.001 vs. WT-LFD) and C5L2KO-HFD displayed increased mitochondrial fatty acid oxidative capacity compared to WT-HFD mice (+23%, p<0.05). In human subjects, C5L2 protein content was reduced (-48%, p<0.01) in type 2 diabetic patients when compared to obese controls. Further, exercise training increased C5L2 (+45%, p = 0.0019) and ASP (+80%, p<0.001) in obese insulin-resistant men. CONCLUSION: The results suggest that insulin sensitivity may be permissive for coupling of C5L2 levels to lipid storage and utilization.
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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) | 0.002 | 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".