The application of loop-mediated isothermal amplification (LAMP) in the rapid detection of banana allergen
Bibliographic record
Abstract
Bananas (Musa acuminata) have been recognized as a common cause of food allergies worldwide. To avoid allergic reactions in patients with allergies, it is important to avoid eating bananas. Therefore, sensitive and specific banana detection methods are needed to verify bananas in food. Loop-mediated isothermal amplification (LAMP) is a fast and simple DNA-based detection method, which is mainly suitable for field application or on-site analysis and screening of allergens in food production. This work describes the systematic development and selection of LAMP primers based on multiple copy genes of banana. The chemical method used allows the detection of amplified DNA using either direct observation of precipitated products or gel electrophoresis. LAMP based on AJ277278 gene is highly specific for bananas, allowing detection sensitivity of approximately sensitivity of 3.9 × 10−3 ng/μL DNA extracting solution. Different banana products can be detected at the same sensitivity level. LAMP enables simple, highly specific and sensitive detection of bananas without the need for expensive analytical equipment.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".