PGC1α and mitochondrial metabolism – emerging concepts and relevance in ageing and neurodegenerative disorders
Bibliographic record
Abstract
PGC1α is a transcriptional coactivator that is a central inducer of mitochondrial biogenesis in cells. Recent work highlighted that PGC1α can also modulate the composition and functions of individual mitochondria. Therefore, it is emerging that PGC1α is controlling global oxidative metabolism by performing two types of remodelling: (1) cellular remodelling through mitochondrial biogenesis, and (2) organelle remodelling through alteration in the intrinsic properties of mitochondria. The elevated oxidative metabolism associated with increased PGC1α activity could be accompanied by an increase in reactive oxygen species (ROS) that are primarily generated by mitochondria. However, increasing evidence suggests that this is not the case, as PGC1α is also a powerful regulator of ROS removal by increasing the expression of numerous ROS-detoxifying enzymes. Therefore, PGC1α, by controlling both the induction of mitochondrial metabolism and the removal of its ROS by-products, would elevate oxidative metabolism and minimize the impact of ROS on cell physiology. In this Commentary, we discuss how the biogenesis and remodelling of mitochondria that are elicited by PGC1α contribute to an increase in oxidative metabolism and the preservation of ROS homeostasis. Finally, we examine the importance of these findings in ageing and neurodegenerative disorders, conditions that are associated with impaired mitochondrial functions and ROS balance.
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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) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".