Decreasing intramuscular phosphagen content simultaneously increases plasma membrane FAT/CD36 and GLUT4 transporter abundance
Bibliographic record
Abstract
Decreasing muscle phosphagen content through dietary administration of the creatine analog beta-guanidinopropionic acid (beta-GPA) improves skeletal muscle oxidative capacity and resistance to fatigue during aerobic exercise in rodents, similar to that observed with endurance training. Surprisingly, the effect of beta-GPA on muscle substrate metabolism has been relatively unexamined, with only a few reports of increased muscle GLUT4 content and insulin-stimulated glucose uptake/clearance in rodent muscle. The effect of chronically decreasing muscle phophagen content on muscle fatty acid (FA) metabolism (transport, oxidation, esterification) is virtually unknown. The purpose of the present study was to examine changes in muscle substrate metabolism in response to 8 wk feeding of beta-GPA. Consistent with other reports, beta-GPA feeding decreased muscle ATP and total creatine content by approximately 50 and 90%, respectively. This decline in energy charge was associated with simultaneous increases in both glucose (GLUT4; +33 to 45%, P < 0.01) and FA (FAT/CD36; +28 to 33%, P < 0.05) transporters in the sarcolemma of red and white muscle. Accordingly, we also observed significant increases in insulin-stimulated glucose transport (+47%, P < 0.05) and AICAR-stimulated palmitate oxidation (+77%, P < 0.01) in the soleus muscle of beta-GPA-fed animals. Phosphorylation of AMPK (+20%, P < 0.05), but not total protein, was significantly increased in both fiber types in response to muscle phosphagen reduction. Thus the content of sarcolemmal transporters for both of the major energy substrates for muscle increased in response to a reduced energy charge. Increased phosphorylation of AMPK may be one of the triggers for this response.
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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 | 0.001 |
| 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".