Detection of Isoflavones in Mouse Tibia After Feeding Daidzein
Bibliographic record
Abstract
Many studies suggest that diets rich in isoflavones protect against bone loss or slow the loss of bone mass that occurs because of estrogen withdrawal. Although in vitro studies have reported effects of isoflavones on bone cells, the presence of daidzein and/or equol in bone tissue in vivo has not been reported. The objective of this study was to determine if daidzein and equol were present in bone tissue (tibias) after feeding mice a diet containing purified daidzein. Sham mice (n = 9) received control diet, and ovariectomized mice were randomized to control diet (Ovx) (n = 9) or control diet containing 200 mg of daidzein/kg of diet (n = 8) for 12 weeks. At necropsy, tibias and serum were collected. Mice in the Daidzein group had significantly higher (P < .05) levels of both daidzein and equol in tibias than Sham and Ovx mice. Tibia levels of daidzein and equol were approximately five and four times higher, respectively, than the Sham and Ovx groups. Similarly, mice fed daidzein also had significantly higher (P < .05) serum daidzein and equol than the Sham and Ovx mice. In conclusion, feeding a level of daidzein that is attainable by dietary intervention alone results in a high level of both daidzein and equol in tibias. These findings suggest that daidzein and its metabolite, equol, have the potential to act directly on bone cells in vivo.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".