Effects of the Steroidal Aromatase Inhibitor Exemestane and the Nonsteroidal Aromatase Inhibitor Letrozole on Bone and Lipid Metabolism in Ovariectomized Rats
Bibliographic record
Abstract
PURPOSE: Exemestane (EXE) and letrozole (LET) are third-generation aromatase inhibitors currently prescribed for postmenopausal hormone-dependent breast cancer. The impact on end organs of estrogen depletion in menopausal women is of significant clinical importance. We studied the effects of EXE, its principal metabolite, 17-hydroexemestane (17-H-EXE), and LET on bone and lipid metabolism in ovariectomized (OVX) rats. EXPERIMENTAL DESIGN: OVX rats were treated by weekly intramuscular injection for 16 weeks with 20, 50, and 100 mg/kg EXE, 20 mg/kg 17-H-EXE, and daily oral gavage of 1 mg/kg LET. At the end of the treatment period, bone mineral density (BMD), the bone resorption marker serum pyridinoline, the bone formation marker serum osteocalcin, bone mechanical properties, histomorphometry, and serum lipid concentrations were determined. RESULTS: Lumbar vertebral and femoral BMD, bending strength of the femur, compressive strength of the fifth lumbar vertebra, and trabecular bone volume were significantly higher in OVX animals given EXE and 17-H-EXE than in OVX controls. EXE and 17-H-EXE significantly reduced an ovariectomy-induced increase in serum pyridinoline and serum osteocalcin. EXE and 17-H-EXE given to OVX rats caused significant reductions of serum cholesterol and low-density lipoprotein cholesterol. In contrast, OVX rats treated with LET had BMD, bone biomarkers, mechanical failure properties, and lipid levels similar to those of OVX controls. CONCLUSIONS: EXE and 17-H-EXE significantly prevent bone loss, enhance bone mechanical strength, and lower serum cholesterol and low-density lipoprotein levels in OVX rats. These protective effects on end-organ function are not seen with the nonsteroidal inhibitor LET.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".