Bioavailability of soy isoflavones in rats Part I: Application of accurate methodology for studying the effects of gender and source of isoflavones
Bibliographic record
Abstract
There are limited and controversial reports about the effects of gender and source of isoflavones on their bioavailability. Moreover, several previous studies have not used appropriate methodology to determine the bioavailability of soy isoflavones, which requires comparing the area under the plasma concentration-time curve after both oral and intravenous injection (IV) administration. Therefore, the present study was conducted to determine the bioavailability of isoflavones from different sources following both oral and IV administration in male and female rats. Three sources of isoflavones; Novasoy (a commercial supplement), a mixture of synthetic aglycones (daidzein, genistein and glycitein) and a mixture of synthetic glucosides (daidzin, genistin and glycitin) were tested. Following administration, blood samples were collected at several time points (0, 10, 30 min and 1, 2, 8, 24, 48 h post oral gavage and 0, 10, 30, 45 min and 1, 2, 3, 4, 8 h post-IV dosing) and plasma isoflavones were measured by LC/MS. Bioavailability values for daidzein, genistein and glycitein were significantly (p <0.05) higher (up to sevenfold) in Novasoy and the glucoside forms of isoflavones compared with those of the aglycone forms. Moreover, significant (p <0.05) gender differences in the bioavailability of 7-hydroxyl-3-(4'-hydroxyphenyl)-chroman (a metabolite of daidzein), glycitein and daidzein were observed for Novasoy, with higher values in male rats. In summary, the source of isoflavones and the sex of rats had significant effects on isoflavone bioavailability.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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 | 0.001 |
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".