Canonical and non‐canonical functions of proteins regulating mitochondrial dynamics in mammalian physiology
Bibliographic record
Abstract
Mitochondria are dynamic and multifunctional organelles central to cellular bioenergetics and metabolism and acting as vital signalling hubs. Their morphology is finely regulated by the opposing processes of fusion and fission, predominantly controlled by four key GTPases: mitofusin 1 (MFN1), mitofusin 2 (MFN2), optic atrophy 1 (OPA1) and dynamin-related protein 1 (DRP1). In humans, mutations in their genes are linked to a broad range of pathological disorders. In animal models, both loss- and gain-of-function manipulations of these proteins lead to diverse physiological outcomes. Recent research has uncovered that, beyond their canonical roles in shaping mitochondrial morphology, these GTPases also participate in a variety of non-canonical cellular functions, impacting broader aspects of cell physiology. In this review, we examine the established functions of these GTPases in mitochondrial dynamics alongside their emerging roles beyond shaping mitochondrial morphology. We also provide an in-depth overview of how alterations in their expression or activity influence mammalian health and physiology. By highlighting the multifaceted roles and broad physiological impact of mitochondrial fusion and fission proteins, we aim to underscore their complex biology and promote further investigation into their broader physiological significance.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".