Inhibitory Activities of Soluble and Bound Millet Seed Phenolics on Free Radicals and Reactive Oxygen Species
Bibliographic record
Abstract
Oxidative stress, caused by reactive oxygen species (ROS), is responsible for modulating several pathological conditions and aging. Soluble and bound phenolic extracts of commonly consumed millets, namely, kodo, finger (Ravi), finger (local), foxtail, proso, little, and pearl, were investigated for their phenolic content and inhibition of 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical and ROS, namely, hydroxyl radical, peroxyl radical, hydrogen peroxide (H(2)O(2)), hypochlorous acid (HOCl), and singlet oxygen ((1)O(2)). Inhibition of DPPH and hydroxyl radicals was detrmined using electron paramagnetic resonance (EPR) spectroscopy. The peroxyl radical inhibitory activity was measured using the oxygen radical absorbance capacity (ORAC) assay. The scavenging of H(2)O(2), HOCl, and (1)O(2) was evaluated using colorimetric methods. The results were expressed as micromoles of ferulic acid equivalents (FAE) per gram of grain on a dry weight basis. In addition, major hydroxycinnamic acids were identified and quantified using high-performance liquid chromatography (HPLC) and HPLC-mass spectrometry (MS). All millet varieties displayed effective radical and ROS inhibition activities, which generally positively correlated with phenolic contents, except for hydroxyl radical. HPLC analysis revealed the presence of ferulic and p-coumaric acids as major hydroxycinnamic acids in phenolic extract and responsible for the observed effects. Bound extracts of millet contributed 38-99% to ROS scavenging, depending on the variety and the test system employed. Hence, bound phenolics must be included in the evaluation of the antioxidant activity of millets and other cereals.
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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) | 0.001 | 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".