Loss of ovarian function alters multiple aspects of lipid metabolism in adipose tissue and skeletal muscle from female mice.
Bibliographic record
Abstract
Post‐menopausal females are at risk for dyslipidemia, thus we sought to discover if surgical‐induced menopause (OVX) altered mechanisms that regulate lipid metabolism and to determine if voluntary wheel running (Ex) or 17β‐estradiol (E2) attenuated these changes. C57BL/6 mice were placed into the following groups for 8 wks: SHAM, OVX, OVX‐Ex, or OVX+E2. Visceral fat mass (VF) was significantly higher in OVX and OVX‐Ex compared to other groups, as were serum glycerol and free fatty acids indicating increased lipolytic action, which was a result of increased ATGL activation and reduced perilipin expression in VF. The increased lipolysis resulted in ectopic lipid deposition in skeletal muscle (SM), which was associated with increased FAT/CD36 expression in the OVX compared to the SHAM, but exercise or E2 attenuated the increase. Metabolic profiling of SM found OVX animals exhibit lower levels of short chain acyl‐cartinine species compared to SHAM, which was prevented by exercise or E2. Citrate levels were elevated in all OVX mice compared to SHAM animals, with minimal differences in other organic acids. Finally, decreased expression of critical proteins in the electron transport chain was detected in OVX compared to all other groups. Reductions in ovarian function resulted in significant alterations in regulatory mechanisms in multiple tissues that contribute to the metabolic syndrome in post‐menopausal females.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".