Proteomic study of periovarian adipose tissue in 17β-estradiol-treated and untreated ovariectomized rats
Bibliographic record
Abstract
Taking into account the sexual dimorphism previously found in white adipose tissue (WAT) regarding mitochondrial function and biogenesis, as well as insulin sensitivity, the aim of this study was to go further into the role of sex hormones in this dimorphism. To achieve this objective, we used ovariectomized rats and performed a screening by means of proteomic analyses of the periovarian WAT, combined with a study of the protein levels of specific factors involved in mitochondrial function. Rats were ovariectomized at 5 weeks of age and subcutaneously injected every 48 h with corn-oil (OVX group) or with 17β-estradiol (E2, 10 μg/kg body mass; OVX + E2 group) for 4 weeks prior to sacrifice. Beside proteomic analysis, protein levels of Transcription Factor A, Mitochondrial (TFAM), cytochrome oxidase (COX)II, and COXIV were determined by Western blot, and mRNA levels of peroxisome proliferator-activated receptor-γ coactivator (PGC)-1α, ERα, ERβ, lipoprotein lipase (LPL), peroxisome proliferator-activated receptor-γ (PPARγ), and adiponectin were quantified by real-time PCR. Our results show that ovariectomy leads to an increase in anabolic processes and inflammatory protein levels as well as to a decrease in some of the markers of mitochondrial function, which are restored, at least in part, by E2 supplementation. Indeed, this E2 supplementation seems to be counteracted by a decline in ERα and in the ERα to ERβ ratio values that could be directed to avoid an over-stimulation of the E2 signaling pathway, given the possibility of an activation of extra-gonadal steroid biosynthetic pathways.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".