Mitochondrial quality control in health and in Parkinson’s disease
Bibliographic record
Abstract
As a central hub for cellular metabolism and intracellular signaling, the mitochondrion is a pivotal organelle, dysfunction of which has been linked to several human diseases including neurodegenerative disorders and in particular Parkinson's disease. An inherent challenge that mitochondria face is the continuous exposure to diverse stresses that increase their likelihood of dysregulation. In response, eukaryotic cells have evolved sophisticated quality control mechanisms to monitor, identify, repair, and/or eliminate abnormal or misfolded proteins within the mitochondrion and/or the dysfunctional mitochondrion itself. Chaperones identify unstable or otherwise abnormal conformations in mitochondrial proteins and can promote their refolding to recover their correct conformation and stability. However, if repair is not possible, the abnormal protein is selectively degraded to prevent potentially damaging interactions with other proteins or its oligomerization into toxic multimeric complexes. The autophagic-lysosomal system and the ubiquitin-proteasome system mediate the selective and targeted degradation of such abnormal or misfolded protein species. Mitophagy (a specific kind of autophagy) mediates the selective elimination of dysfunctional mitochondria, to prevent the deleterious effects of the dysfunctional organelles within the cell. Despite our increasing understanding of the molecular responses toward dysfunctional mitochondria, many key aspects remain relatively poorly understood. Here, we review the emerging mechanisms of mitochondrial quality control including quality control strategies coupled to mitochondrial import mechanisms. In addition, we review the molecular mechanisms regulating mitophagy, with an emphasis on the regulation of PINK1/Parkin-mediated mitophagy in cellular physiology and in the context of Parkinson's disease cell biology.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".