Insight into the mechanism of ultrasound-assisted cold plasma alleviated the allergenicity of peanut protein with improved functional properties
Bibliographic record
Abstract
Peanuts are classified as the major allergens worldwide. This study aimed to investigate the effects of ultrasound-assisted cold plasma treatment (UC) on the structure, functionality, safety, and allergenicity of peanut protein (PP). The research findings revealed that compared with untreated PP, UC treatment for 25 min (UC25) could facilitate the transition of α-helix to β-sheet in the secondary structure. At the same time, there was a 77% decrease in the fluorescence intensity of aromatic amino acids and a 32.83-fold increase in hydrophobicity. These structural changes contributed to an increase in the emulsifying and foaming capabilities of PP by 102% and 63%, respectively. In vitro allergenicity results indicated that compared with ultrasound treatment (UL) group, the strong oxidizing property of UC25 could disrupt both native and exposed allergenic epitopes, resulting in a 74% reduction in IgG binding capacity. The results of mouse experiments revealed the ability of UC25 treatment to restore the Th1/Th2 balance by promoting IFN-γ secretion (increased by 2.11-fold) and inhibiting IL-13 secretion (decreased by 46%), further confirming the significant alleviation of allergic symptoms by UC25. This study aimed to provide new insights for the development of novel hypoallergenic peanut products. • Ultrasound and cold plasma were applied for modifications of peanut protein (PP). • Combined treatments induced hydrogen bond rearrangement and exposed hydrophobic groups of PP. • Combined treatments reduced allergenicity, while enhancing emulsifying and foaming capabilities of PP. • Combined treatments restored the Th1/Th2 cellular balance.
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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 | 0.001 |
| 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 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".