Importance of Insoluble-Bound Phenolics to the Antioxidant Potential Is Dictated by Source Material
Bibliographic record
Abstract
Insoluble-bound phenolics (IBPs) are extensively found in the cell wall and distributed in various tissues/organs of plants, mainly cereals, legumes, and pulses. In particular, IBPs are mainly distributed in the protective tissues, such as seed coat, pericarp, and hull, and are also available in nutritional tissues, including germ, epicotyl, hypocotyl radicle, and endosperm, among others. IBPs account for 20-60% of the total phenolics in food matrices and can exceed 70% in leaves, flowers, peels, pulps, seeds, and other counterparts of fruits and vegetables, and up to 99% in cereal brans. These phenolics are mostly covalently bound to various macromolecules such as hemicellulose, cellulose, structural protein, arabinoxylan, and pectin, which can be extracted by acid, alkali, or enzymatic hydrolysis along with various thermal and non-thermal treatments. IBPs obtained from various sources exhibited a wide range of biological activities, including antioxidant, anti-inflammatory, antihypertensive, anticancer, anti-obesity, and anti-diabetic properties. In this contribution, the chemistry, distribution, biological activities, metabolism, and extraction methods of IBPs, and how they are affected by various treatments, are summarized. In particular, the effect of thermal and non-thermal processing on the release of IBPs and their antioxidant potential is discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".