The effects of isoflavone supplementation plus combined exercise on salivary markers of oxidative stress in postmenopausal women
Bibliographic record
Abstract
This study tested the effect of isoflavone supplementation in addition to combined exercise training in salivary oxidative stress markers in non-obese postmenopausal women. Thirty-two postmenopausal women without hormone therapy were randomly assigned to exercise + placebo (n = 15) or exercise + isoflavone supplementation (n = 17) groups. They performed 30 sessions of combined exercises (aerobic plus resistance) over ten weeks and consumed 100 mg of isoflavone supplementation or placebo. Saliva samples were collected after an overnight fast. Superoxide dismutase, total antioxidant capacity, thiobarbituric acid reactive substances, catalase, total protein and nitrite were determined before and after ten weeks of the intervention. The ANOVA two-way analysis of variance was applied with α of 5%. Both groups increase (p<0.05) superoxide dismutase activity and decrease catalase levels. There was interaction (time × group) in both nitrite and thiobarbituric acid reactive substances results, with increase (p<0.05) in placebo group and decrease (p<0.05) in isoflavone group. No difference was found for total antioxidant capacity or total protein. The combination of isoflavone supplementation and exercise training can promote an antioxidant effect through reduction of lipid peroxidation and concentrations of salivary nitrite.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".