Enzyme- and nanozyme-based food allergen detections: from natural biocatalysts to rational engineering approaches
Bibliographic record
Abstract
The global prevalence of food allergies has experienced a substantial surge, significantly impacting populations worldwide. Consequently, the development of precise and sensitive detection techniques targeting these major allergens become increasingly ED 01 (eliciting dose of 1 %) to ensure accurate identification. Compared to conventional allergen analysis techniques, enzyme-based biosensors have shown high sensitivity, simplicity, and cost-effectiveness in detecting trace food allergens. However, the inherent instability of natural enzymes underscores its applications. More advanced catalysts to enhance sensing performance are necessary. In this review, we systematically summarize biosensors that integrate the historical development of enzyme-based biosensing devices, traditional enzyme-based biosensors, and advancements in enzyme-mimetic nanomaterials for food allergen detection, categorizing them by signal transduction methods, including colorimetric, electrochemical, fluorescence, chemiluminescent, electrochemiluminescence, and photoelectrochemical techniques. Moreover, sensor construction approaches and signaling mechanisms have been elaborated, highlighting how these methodologies contribute to the overall effectiveness and specificity of food allergen detection. Nanozymes have huge potential as potential alternatives to traditional biocatalysts in food allergen detection due to their exceptional storage stability, facile engineering, and reusability. With the increasing need of highly sensitive devices, novel signaling transduction methods have been designed with novel nanozymes that provide the required performances. Future research on biosensors using engineered nanozymes is anticipated to advance accurate allergen identification and improving food safety and consumer protection. • Reviewed enzyme-based biosensing methods for food allergen monitoring. • Major enzyme-mediated signal methodologies (electrochemical and optical) are introduced. • Advantages and limitations of nanozyme-enabled food allergen biosensors presented. • Future directions to optimize the performance of nanozymatic biosensors are discussed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".