A Multi-Ingredient Supplement Improves Body Re-Composition, Ovarian Aging Markers, and Reproductive Success in Young and Middle-Aged Female Mice
Bibliographic record
Abstract
Ovarian aging is characterized by mitochondrial dysfunction, oxidative stress, and inflammation. The development of adjunctive treatments that mitigate age-related subfertility is warranted. We examined the benefits of nutraceutical supplementation (FE; Fertility Enhancer) with mitochondrial antioxidants, anti-inflammatory agents, metabolic activators, vitamins and minerals, and amino acids on ovarian aging, metabolic activity, and reproductive success in young (Y; 6-month-old) and middle-aged (O; 11-month-old) female C57BL/6J mice. The mice were fed calorie- and macronutrient-matched diets w/wo the FE supplement for three months and harem mated twice. Daily FE supplementation promoted significant body re-composition, including loss of white adipose tissue (gWAT: −36% vs. CON, p < 0.001), gain of skeletal muscle (SkM: +67% vs. CON, p < 0.001), and improved SkM/gWAT ratio (+185% vs. CON, p < 0.001). Metabolic testing showed enhanced fat oxidation (+38%, p < 0.01) and energy expenditure (+7%, p = 0.051) in FE mice. Breeding and immunoblotting data demonstrated improved reproductive success (Y-CON: 44%, Y-FE: 89%, O-CON: 0%, O-FE: 18%) and a modest attenuation of ovarian aging markers in both FE groups. We surmise that a multi-ingredient supplement, such as the Fertility Enhancer, may improve body re-composition, metabolic activity, and markers of ovarian aging, thus enhancing reproductive health and fertility in females.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 teacher head, 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".