Ascorbic acid is associated with favourable hormonal profiles among infertile males
Bibliographic record
Abstract
Introduction Infertility affects about 16% of North American couples, with the male factor contributing to ∼30% of cases. Reproductive hormones play an integral role in regulating the reproductive system and consequently, fertility. Oxidative stress reduces testosterone synthesis, and reduction in oxidative stress can improve hormone profiles. Ascorbic acid is a potent antioxidant that accounts for up to 65% of seminal antioxidant activity; however, its effects on reproductive hormones in humans are unknown. Methods The objective was to determine the association between serum ascorbic acid concentrations and male reproductive hormones. We conducted a cross-sectional study involving infertile males ( n = 302) recruited from Mount Sinai Hospital, Toronto. Serum was analyzed for ascorbic acid, luteinizing hormone (LH), follicular stimulating hormone (FSH), total testosterone (TT), prolactin and estradiol. Statistical analyses included Spearman's rank correlations, linear regressions, logistic regressions, simple slope and Johnson-Neyman procedures. Results After adjusting for covariates, ascorbic acid was inversely associated with LH ( P = 0.01). Ascorbic acid was positively associated with TT only among males over the age of 41.6 years ( P = 0.01). Discussion Our findings show that ascorbic acid is associated with higher testosterone levels and improved androgenic status in infertile males, and some of the effects appear to be age dependent.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".