Mechanisms of exercise-induced mitochondrial biogenesis in skeletal muscleThis paper is one of a selection of papers published in this Special Issue, entitled 14th International Biochemistry of Exercise Conference – Muscles as Molecular and Metabolic Machines, and has undergone the Journal’s usual peer review process.
Bibliographic record
Abstract
Acute exercise initiates rapid cellular signals, leading to the subsequent activation of proteins that increase gene transcription. The result is a higher level of mRNA expression, often observed during the recovery period following exercise. These molecules are translated into precursor proteins for import into preexisting mitochondria. Once inside the organelle, the protein is processed to its mature form and either activates mitochondrial DNA gene expression, serves as a single subunit enzyme, or is incorporated into multi-subunit complexes of the respiratory chain devoted to electron transport and substrate oxidation. The result of this exercise-induced sequence of events is the expansion of the mitochondrial network within muscle cells and the capacity for aerobic ATP provision. An understanding of the molecular processes involved in this complex pathway of organelle synthesis is important for therapeutic purposes, and is a primary research undertaking in laboratories involved in the study of mitochondrial biogenesis. This pathway in muscle becomes impaired with chronic inactivity and aging, which leads to a reduced muscle aerobic capacity and an increased tendency for mitochondrially mediated apoptosis, a situation that can contribute to muscle atrophy. The resumption, or adoption, of an active lifestyle can ameliorate this metabolic dysfunction, improve endurance, and help maintain muscle mass.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".