Comparative Evaluation of the Antioxidant Potential of Infant Cereals Produced from Purple Wheat and Red Rice Grains and LC-MS Analysis of Their Anthocyanins
Bibliographic record
Abstract
Cellular oxidative damage by endogenous and exogenous sources of free radicals and reactive oxygen species is a particular threat in infants. Antioxidant protection is normally achieved through a balance between pro-oxidants and endogenous and/or dietary antioxidants. Comprehensive research is required on optimization to achieve good antioxidant protection through infant foods, in particular, the commercially available infant cereals. This study therefore investigated the properties of whole purple wheat, unpolished red rice, and partially polished red rice before and after processing to produce infant cereals. Total phenolic content (TPC), total anthocyanin content (TAC), oxygen radical absorbance capacity (ORAC), individual anthocyanin components, and cellular antioxidant activity were measured. Home-made and laboratory-made pigmented infant cereals differed in that the latter required longer exposure to higher temperature and enzymatic hydrolysis. Home-made and laboratory-made unpolished red rice infant cereals showed higher total phenolic contents and peroxyl radical scavenging activity than home-made and laboratory-made purple wheat infant cereals; however, the latter had higher TAC. Pigmented infant cereals generally had higher TPC, TAC, and ORAC than the commercial ones (p < 0.05). Anthocyanins were identified in whole purple wheat, but they were not detected in unpolished red rice. C-Glycosyl apigenin was found in both whole purple wheat and unpolished red rice. Processing significantly decreased anthocyanin and C-glycosyl apigenin contents (p < 0.05). Purple wheat infant cereals had higher cellular antioxidant activity than unpolished red rice ones (p < 0.05). Whole purple wheat infant cereals showed higher antioxidant activity than the commercial infant cereal, suggesting a possibility of improving infant antioxidant status by incorporating this grain in their diet.
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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".