Structural stability and Sin a 1 anti-epitope antibody binding ability of yellow mustard (<i>Sinapis alba</i> L.) napin during industrial-scale myrosinase inactivation process
Bibliographic record
Abstract
This study investigated the structural stability of yellow mustard (YM, Sinapis alba L.) napin and the changes of its Sin a 1 anti-epitope antibody-binding ability during myrosinase enzyme inactivation process. The food industry uses myrosinase-inactive non-pungent YM for uses beyond spice applications. Napin was isolated from seeds received from an industrial processor before (YM + M) and after (YM - M) myrosinase inactivation. Secondary and tertiary structural features and surface hydrophobicity parameters of napin were analyzed. The Sin a 1 content in YM seeds and the stability of Sin a 1-containing napin during simulated in vitro gastrointestinal (GI) digestion were determined by a non-competitive indirect enzyme-linked immunosorbent assay using the Sin a 1 anti-epitope antibody (AE-Ab) as the primary Ab. YM napin retained the dominant alpha-helical components of secondary and tertiary structure folds during this process. YM - M napin showed changes in hydrophobicity parameters of the molecules and binding ability of AE-Ab: 2.19 ± 0.48 g per 100 g of YM - M seeds vs. 1.49 ± 0.16 g per 100 g YM + M seeds. YM - M proteins were more susceptible for in vitro GI digestion and also showed a 30% reduction in AE-Ab binding ability upon digestion of napins. This suggests that the myrosinase inactivation process has induced the surface modification of napin, exposing Sin a 1 epitope, leading to an increase in AE-Ab binding. However, the epitope region of YM - M napin showed improved susceptibility for hydrolysis during GI digestion resulting in fewer available epitope regions, suggesting a possible reduction in napin immune reactivity.
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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) | 0.000 | 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 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".