The effect of <i>Dioscorea esculenta</i> powder on prostaglandin E <sub>2</sub> and cytochrome c oxidase subunit 2 levels, menstrual pain, and premenstrual syndrome in young women: A randomized double-blind controlled trial
Bibliographic record
Abstract
Background Diosgenin, extracted from Dioscorea esculenta, has been reported to decrease prostaglandin E 2 (PGE 2 ) levels and any other inflammatory cytokine in rodents. However, it is still unclear whether D. esculenta intake suppressed PGE 2 production and menstrual pain and premenstrual syndrome (PMS) in younger female. Aim This study aims to investigate the effect of D. esculenta intake on PGE 2 and cytochrome c oxidase subunit 2 (COX-2) levels and on menstrual pain and PMS in young women. This is a randomized, double-blind, placebo-controlled, crossover study. Methods Ten healthy young females were administered either a placebo or D. esculenta (300 mg/day) for 4 weeks, followed by a 4-week washout period. Fasting blood sample was taken from the fingertips on the second day of menstrual cycle began and obtained 24h before the last D. esculenta to avoid acute effects. Participants then switched treatments for 4 weeks as a second trial. Plasma PGE 2 and COX-2 levels were measured before and after each trial. The visual analogue scale (VAS), McGill pain questionnaire (MPQ), and Daily Record of Severity of Problems (DRSP) were also evaluated. The study was set and conducted from 2019 to 2020. Results PGE 2 and COX-2 levels significantly decreased after D. esculenta intake compared to placebo ( p = 0.038, p = 0.042 each). The VAS and DRSP scores were also significantly lower after D. esculenta intake ( p = 0.046, p = 0.035 each). Conclusion Four-week D. esculenta intake suppressed PGE 2 and COX-2 levels resulting in an improvement in PMS symptoms and menstrual pain in young women.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".