Effect of <i>Portulaca Oleracea</i> (purslane) extract on liver enzymes, lipid profile, and glycemic status in nonalcoholic fatty liver disease: A randomized, double‐blind clinical trial
Bibliographic record
Abstract
Purslane (Portulaca oleracea L.) is the richest green leafy vegetable source of omega-3, especially alpha linolenic acid (ALA). Experimental studies have shown beneficial effects of purslane extract on liver enzymes. The aim of the present study was to examine the effect of purslane hydroalcohoic extract in patients with non-alcoholic fatty liver disease (NAFLD). In a randomized double-blinded clinical trial, 74 patients were randomly assigned to receive either 300 mg purslane extract or placebo capsules for 12 weeks. Compared with baseline, alanine aminotransferase (ALT) (-9 [-17, 0.50] mg/dl; p = .007), aspartate aminotransferase (AST) (-4 [-10, -0.50] mg/dl; p = .001), gamma glutamyltransferase (GGT) (-6.21 ± 9.85 mg/dL; p < .001), fasting blood glucose (FBG) (-8 [-11, -1.50] mg/dl; p < .001) insulin resistance (-0.95 ± 2.23; p = .020), triglyceride (-20 [-67.50, 3.50] mg/dl; p = .010), and low-density lipoprotein cholesterol (LDL-C) (-5 [-12, -1] mg/dl; p < .001) decreased significantly in the purslane group. At the end of study, no significant changes were observed in liver steatosis grade, insulin, liver enzymes, total bilirubin, lipid profile, and blood pressure between the two groups. The findings of our study show that purslane extract at the dose of 300 mg/day for 12 weeks has no significant effects on liver enzymes, lipid profile, and glycemic indices in patients with NAFLD.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".