Carbohydrate restriction following strenuous glycogen-depleting exercise does not potentiate the acute molecular response associated with mitochondrial biogenesis in human skeletal muscle
Bibliographic record
Abstract
PURPOSE: Carbohydrate (CHO) restriction could be a potent metabolic regulator of endurance exercise-induced muscle adaptations. Here, we determined whether post-exercise CHO restriction following strenuous exercise combining continuous cycling exercise (CCE) and sprint interval exercise could affect the gene expression related to mitochondrial biogenesis and oxidative metabolism in human skeletal muscle. METHODS: In a randomized cross-over design, 8 recreationally active males performed two cycling exercise sessions separated by 4 weeks. Each session consisted of 60-min CCE and six 30-s all-out sprints, which was followed by ingestion of either a CHO or placebo beverage in the post-exercise recovery period. Muscle glycogen concentration and the mRNA levels of several genes related to mitochondrial biogenesis and oxidative metabolism were determined before, immediately after, and at 3 h after exercise. RESULTS: Compared to pre-exercise, strenuous cycling led to a severe muscle glycogen depletion (> 90%) and induced a large increase in PGC1A and PDK4 mRNA levels (~ 20-fold and ~ 10-fold, respectively) during the acute recovery period in both trials. The abundance of the other transcripts was not changed or was only moderately increased during this period. CHO restriction during the 3-h post-exercise period blunted muscle glycogen resynthesis but did not increase the mRNA levels of genes associated with muscle adaptation to endurance exercise, as compared with abundant post-exercise CHO consumption. CONCLUSION: CHO restriction after a glycogen-depleting and metabolically-demanding cycling session is not effective for increasing the acute mRNA levels of genes involved in mitochondrial biogenesis and oxidative metabolism in human skeletal muscle.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".