β-Carotene bioaccessibility from biofortified maize (<i>Zea mays</i>) is related to its density and is negatively influenced by lutein and zeaxanthin
Bibliographic record
Abstract
of biofortified Pusa-PV-16-3 (BC = 808.4 μg per 100 g; AC = 839.3 μg per 100 g; BCX = 59 μg per 100 g) and Pusa-APQH8 (BC = 345.9 μg per 100 g; AC = 1739 μg per 100 g; BCX = 644.2 μg per 100 g) maize would contribute to 52 and 64% of RDAs for adult Indian men, respectively, after adjusting for cooking losses and conversion factors. The mean efficiency of micellarization of LUT (62.2% ± 5.3), ZEA (65% ± 4.7), and BCX (54% ± 9.5) exceeded that of AC (43% ± 8.9) and BC (49.8% ± 7.8) from all the maize hybrids. Furthermore, the micellarization and uptake in Caco-2 cells during a 4 h incubation period showed high correlation (P < 0.05) with the concentration of carotenoids in the maize digesta and micellar fraction, respectively. However, the LUT + ZEA content in the maize digesta and micellar fraction was inversely (p < 0.05) related to the BC micellarization and intestinal cell uptake, respectively. These results together suggest that the enrichment of pro-VA carotenoids together with decreasing the oxygenated carotenoid metabolites such as LUT and ZEA will further improve the bioavailability of BC from maize hybrids.
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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".