Effect of sonication - cooking on the immunoreactivity of soy slurry from germinated soybeans
Bibliographic record
Abstract
Soy proteins are globular in nature and are resistant to denaturation with lower intensity thermal treatments like cooking. Likewise, germination can also alter the protein structure through the activity of various enzymes and sonication can disrupt the molecular structure through cavitation and other ultrasound effects, and contribute to some reduction in immunoreactivity (IR) of allergens. This study evaluated the effects of germination and sonication pretreatment in combination with common cooking on lowering the soy allergen IR. Germination was carried out for up to 120 h and ultrasound sonication treatments were given for 20, 40 and 60 min at room temperature. Cooking at 100 oC was carried out for 10 to 60 min. The soy allergen IR was evaluated using a commercial sandwich ELISA kit. The combined action of germination, sonication and cooking helped to reduce the soy allergen IR to single digit mg/L levels from the nearly 400 mg/L initial level in the 5% soy slurry (> 99% reduction). These levels are lower than the reported threshold values of soy allergens in foods. In addition, the germination and ultrasound process was shown to reduce the anti-nutritional properties and enhance the phenolic and radical scavenging activity by over 50%.
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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".