Reduced Fat Mass in Mice Lacking Orphan Nuclear Receptor Estrogen-Related Receptor α
Bibliographic record
Abstract
The estrogen-related receptor alpha (ERRalpha) is an orphan member of the superfamily of nuclear hormone receptors expressed in tissues that preferentially metabolize fatty acids. Despite the molecular characterization of ERRalpha and identification of target genes, determination of its physiological function has been hampered by the lack of a natural ligand. To further understand the in vivo function of ERRalpha, we generated and analyzed Estrra-null (ERRalpha-/-) mutant mice. Here we show that ERRalpha-/- mice are viable, fertile and display no gross anatomical alterations, with the exception of reduced body weight and peripheral fat deposits. No significant changes in food consumption and energy expenditure or serum biochemistry parameters were observed in the mutant animals. However, the mutant animals are resistant to a high-fat diet-induced obesity. Importantly, DNA microarray analysis of gene expression in adipose tissue demonstrates altered regulation of several enzymes involved in lipid, eicosanoid, and steroid synthesis, suggesting that the loss of ERRalpha might interfere with other nuclear receptor signaling pathways. In addition, the microarray study shows alteration in the expression of genes regulating adipogenesis as well as energy metabolism. In agreement with these findings, metabolic studies showed reduced lipogenesis in adipose tissues. This study suggests that ERRalpha functions as a metabolic regulator and that the ERRalpha-/- mice provide a novel model for the investigation of metabolic regulation by nuclear receptors.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".