Transcriptional Regulation of ROS Homeostasis by the ERR Subfamily of Nuclear Receptors
Bibliographic record
Abstract
) are generated endogenously by processes such as mitochondrial oxidative phosphorylation, or they may arise from exogenous sources like bacterial invasion. ROS can be beneficial (oxidative eustress) as signaling molecules but also harmful (oxidative distress) to cells when ROS levels become unregulated in response to physiological, pathological or pharmacological insults. Indeed, abnormal ROS levels have been shown to contribute to the etiology of a wide variety of diseases. Transcriptional control of metabolic genes is a crucial mechanism to coordinate ROS homeostasis. Therefore, a better understanding of how ROS metabolism is regulated by specific transcription factors can contribute to uncovering new therapeutic strategies. A large body of work has positioned the estrogen-related receptors (ERRs), transcription factors belonging to the nuclear receptor superfamily, as not only master regulators of cellular energy metabolism but, most recently, of ROS metabolism. Herein, we will review the role played by the ERRs as transcriptional regulators of ROS generation and antioxidant mechanisms and also as ROS sensors. We will assess how the control of ROS homeostasis by the ERRs can be linked to physiology and disease and the possible contribution of manipulating ERR activity in redox medicine.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".