In Vitro and in Vivo Antioxidant Properties of the Plant-Based Supplement Greens+
Bibliographic record
Abstract
Dietary antioxidants play an important role against oxidation, an underlying mechanism in the incidence of chronic diseases. Greens+ is a commercially available preparation containing a variety of plant-derived ingredients. The aim of the current study was to evaluate the antioxidant potential of the methanolic extract of greens+ powder using in vitro and in vivo techniques. In vitro studies were conducted using a liposome model system to simulate biological cell membranes. Total antioxidant potential and polyphenol content of the herbal preparation was measured. For in vivo analysis, 10 healthy human subjects consumed either three or six teaspoons of greens+ per day for four weeks. Blood samples were analyzed at baseline and at the conclusion of the treatment period for total antioxidant capacity, polyphenol content, protein, lipid and LDL oxidation, and the level of glutathione peroxidase. Results showed that greens+ supplementation was well tolerated and increased serum antioxidant potential at higher levels of intake in a dose-dependent manner. HPLC analysis showed the presence of quercetin, apigenin, kaempferol and luteolin in the supplement. Plasma analysis indicated the presence of kaempferol only. A statistically significant (p < 0.05) reduction in protein and lipid oxidation was observed. Based on its antioxidant properties, the results suggest that greens+ might play a role in reducing the risk of chronic diseases involving a burden of oxidative damage.
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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 | 0.000 |
| 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) | 0.002 | 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".