Effects of green coffee supplementation on paraoxonase-1 activity and malondialdehyde levels in Iranian women with polycystic ovary syndrome: a randomized clinical trial
Bibliographic record
Abstract
BACKGROUND: Polycystic ovary syndrome (PCOS) is a common, heterogeneous clinical syndrome affecting women. Investigating oxidative stress in women is crucial, as it is linked to insulin resistance and endothelial dysfunction. Chlorogenic acid, a bioactive component found in green coffee, has numerous documented health benefits. This study aimed to assess the beneficial effects of green coffee consumption on paraoxonase-1 (PON-1) activity and malondialdehyde (MDA) levels in women with PCOS. METHODS: This study was a double-blind randomized clinical trial that included 44 patients with PCOS. Participants were randomly assigned to either the intervention or control group. For 6 weeks, the intervention group (n=22) received 400 mg of green coffee supplements, while the control group (n=22) received 400 mg of a starch-based placebo. Anthropometric indices, dietary assessments, and physical activity levels were evaluated before and after the 6-week intervention period. Additionally, blood samples were collected for laboratory analysis. RESULTS: Supplementation with green coffee increased PON-1 levels by 3.5 units, a significant finding (p=0.038). Additionally, the intake of green coffee supplements significantly reduced blood cholesterol levels by 18.8 units (p=0.013) and triglyceride levels by 6.1 units (p=0.053). However, no significant differences were observed in the levels of MDA, high-density lipoprotein, low-density lipoprotein, fasting blood sugar, insulin, or homeostatic model assessment of insulin resistance as a result of the intervention. CONCLUSION: Supplementation with green coffee alters PON-1 activity and cholesterol levels in women with PCOS. However, it has no significant impact on MDA levels or glycemic status.
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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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".