Bibliographic record
Abstract
The protein import process of mitochondria is vital for the assembly of the hundreds of nuclear-derived proteins into an expanding organelle reticulum. Most of our knowledge of this complex multisubunit network comes from studies of yeast and fungal systems, with little information known about the protein import process in mammalian cells, particularly skeletal muscle. However, growing evidence indicates that the protein import machinery can respond to changes in the energy status of the cell. In particular, contractile activity, a powerful inducer of mitochondrial biogenesis, has been shown to alter the stoichiometry of the protein import apparatus via changes in several protein import machinery components. These adaptations include the induction of cytosolic molecular chaperones that transport precursors to the matrix, the up-regulation of outer membrane import receptors, and the increase in matrix chaperonins that facilitate the import and proper folding of the protein for subsequent compartmentation in the matrix or inner membrane. The physiological importance of these changes is an increased capacity for import into the organelle at any given precursor concentration. Defects in the protein import machinery components have been associated with mitochondrial disorders. Thus, contractile activity may serve as a possible mechanism for up-regulation of mitochondrial protein import and compensation for mitochondrial phenotype alterations observed in diseased muscle.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.012 |
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".