Measurement of Protein Import Capacity of Skeletal Muscle Mitochondria
Bibliographic record
Abstract
Mitochondria are key metabolic and regulatory organelles that determine the energy supply as well as the overall health of the cell. In skeletal muscle, mitochondria exist in a series of complex morphologies, ranging from small oval organelles to a broad, reticulum-like network. Understanding how the mitochondrial reticulum expands and develops in response to diverse stimuli such as alterations in energy demand has long been a topic of research. A key aspect of this growth, or biogenesis, is the import of precursor proteins, originally encoded by the nuclear genome, synthesized in the cytosol, and translocated into various mitochondrial sub-compartments. Mitochondria have developed a sophisticated mechanism for this import process, involving many selective inner and outer membrane channels, known as the protein import machinery (PIM). Import into the mitochondrion is dependent on viable membrane potential and the availability of organelle-derived ATP through oxidative phosphorylation. Therefore its measurement can serve as a measure of organelle health. The PIM also exhibits a high level of adaptive plasticity in skeletal muscle that is tightly coupled to the energy status of the cell. For example, exercise training has been shown to increase import capacity, while muscle disuse reduces it, coincident with changes in markers of mitochondrial content. Although protein import is a critical step in the biogenesis and expansion of mitochondria, the process is not widely studied in skeletal muscle. Thus, this paper outlines how to use isolated and fully functional mitochondria from skeletal muscle to measure protein import capacity in order to promote a greater understanding of the methods involved and an appreciation of the importance of the pathway for organelle turnover in exercise, health, and disease.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".