Yellow Mustard Protein a Immunoreactivity Reduction Through Seed Germination, Lactic Acid Fermentation, and Cooking
Bibliographic record
Abstract
Food allergens are becoming increasingly threatening and are disrupting the health and social structure of a significantly large population worldwide. Proteins from mustard are among the well-recognized food allergens which affect many sensitive individuals. Many processing methods are continually being explored to reduce allergen immunoreactivity and for developing hypoallergenic foods. Cooking, germination, and fermentation have been evaluated to attenuate the immunoreactivity of food allergens. The objective of this study is to evaluate the effect of seed germination, lactic acid fermentation, and/or cooking on yellow mustard seed protein immunoreactivity (IR) (protein A) using ELISA techniques. Samples from five-day germination at 35-40 °C and three-day fermentation between 25 °C and 35 °C were evaluated. The germination and fermentation processes yielded varying reductions in the IRs of mustard proteins, with a combined yield of about 90% reduction. When complemented with further stovetop cooking, protein IR reduction was extended up to 98%, while cooking alone resulted only in about a 70% reduction. FTIR results confirmed that changes in mustard protein conformation maybe due to the unfolding and/or denaturation of mustard proteins. These processing methods are beneficial as they not only help reduce the native mustard protein IR, but also increased inherent antioxidant activities in germinated and fermented mustard seeds.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".