Bioactive Compounds of Acai (Euterpe oleracea) and the Effect of their Consumption on Oxidative Stress Markers
Bibliographic record
Abstract
Açaí fruit (Euterpe oleracea Martius) is highly perishable, so it sought to apply conservation techniques that make its commercialization more bearable such as dehydration by the tray. This thermal technique that significantly inactivates harmful enzymes and microorganisms prolongs their shelf life but has the disadvantage that it decreases the proportion of bioactive components and its antioxidant power. The present work aims to estimate the content and antioxidant activity of the bioactive compounds of açaí powder supplied in hydroxypropyl methylcellulose (HPMC) vegetable capsules. For this purpose, total polyphenols were determined by the Folin-Ciocalteau test, total anthocyanin’s by the differential pH test, and the antioxidant capacity in vitro DPPH method (using Trolox and Vitamin C equivalent). Also, the effect of consumption of four daily capsules on a healthy population (10 people) between the ages of 33-65 years old evaluated through a 10-day intervention study in which the following biomarkers in blood assessed: glycemia, triglycerides, total cholesterol, HDL, LDL, and 8-isoprostane. The açaí powder showed a total polyphenol content of 962.7±22.2 mg EAG/100g, total anthocyanin’s up to 938.5±19.1 mg C3GE/100g, the antioxidant capacity of 643±24.32 µmol TE/100g and 14.07±0.45 g VCE/100g. In the intervention study, no significant differences were observed between before and after the different biochemical markers except for 8-isoprostane, suggesting that the consumption of dehydrated açaí caused effects benefices in the population tested.
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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 | 0.001 | 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) | 0.001 | 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".