Increases in glycogenin and glycogenin mRNA accompany glycogen resynthesis in human skeletal muscle
Bibliographic record
Abstract
Glycogenin is the self-glycosylating protein primer that initiates glycogen granule formation. To examine the role of this protein during glycogen resynthesis, eight male subjects exercised to exhaustion on a cycle ergometer at 75% Vo2 max followed by five 30-s sprints at maximal capacity to further deplete glycogen stores. During recovery, carbohydrate (75 g/h) was supplied to promote rapid glycogen repletion, and muscle biopsies were obtained from the vastus lateralis at 0, 30, 120, and 300 min postexercise. At time 0, no free (deglycosylated) glycogenin was detected in muscle, indicating that all glycogenin was complexed to carbohydrate. Glycogenin activity, a measure of the glycosylating ability of the protein, increased at 30 min and remained elevated for the remainder of the study. Quantitative RT-PCR showed elevated glycogenin mRNA at 120 min followed by increases in protein levels at 300 min. Glycogenin specific activity (glycogenin activity/relative protein content) was also elevated at 120 min. Proglycogen increased at all time points, with the highest rate of resynthesis occurring between 0 and 30 min. In comparison, macroglycogen levels did not significantly increase until 300 min postexercise. Together, these results show that, during recovery from prolonged exhaustive exercise, glycogenin mRNA and protein content and activity increase in muscle. This may facilitate rapid glycogen resynthesis by providing the glycogenin backbone of proglycogen, the major component of glycogen synthesized in early recovery.
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".