Stressful situations: Molecular insights on mitochondrial quality control pathways
Bibliographic record
Abstract
Mitochondrial quality control has emerged as an important area of research over the past decade, with more than 2000 publications exploring the molecular pathways that regulate it. Mitochondria are essential for energy production and various cellular functions but are highly susceptible to damage from stressors such as protein misfolding, reactive oxygen species, and chemicals that disrupt the electron transport chain. If left unresolved, mitochondrial dysfunction can lead to health complications, including neurodegenerative disorders, cardiovascular diseases, and cancer. To maintain cellular health, cells evolved quality control pathways to remove damaged mitochondrial components. This review focuses on three key quality control responses: the PTEN-induced kinase 1-Parkin pathway, the DELE1-HRI pathway, and the mitochondrial unfolded protein response. While these pathways have distinct functions, there is ongoing debate about how they overlap and which responds first in different contexts. In this review, we discuss the physiological and structural mechanisms behind each pathway, explore how they interconnect, and highlight their differences and relevance to disease. By summarizing this information in a single review, we aim to enhance the molecular understanding of mitochondrial quality control, which can help highlight avenues for novel therapeutics for diseases associated to dysfunctional mitochondria.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".