Rapid, efficient, and accurate determination of aflatoxins and capsaicinoids in vegetable oils by immunomagnetic sorbents coupled with UHPLC–MS/MS
Bibliographic record
Abstract
Abstract A fast, simple, and sensitive analytic method was proposed for the simultaneous quantification of aflatoxins (AFTs) and capsaicinoids in vegetable oils by immunomagnetic sorbent coupled with ultra‐performance liquid chromatography coupled with tandem mass spectrometry. The immunomagnetic solid phase extraction (IMSPE) sorbents were synthesized with the monoclonal antibodies via cyanogen bromide magnetic sorbents, which could modify the surface magnetic sorbents under mild synthetic condition. The IMSPE procedure had the following aspects such as ease manipulation, easy disperse, quick isolation, eco‐friendly, and cost‐effective. The major conditions of IMSPE procedure were systemically studied, and the optimized pretreatment was accomplished in 15 min avoding complicated condition or sophisticated equipment. Excellent linearities were achieved by the correlation ( R 2 ) more than 0.9983. The limits of quantifications of all analytes ranged from 0.03 to 0.20 µg kg −1 , and the recoveries were satisfactory ranging from 75.7% to 124.0% with the intra‐day and inter‐day precisions less than 10.1%. Additionally, the proposed method was used to analyze AFTs and capsaicinoids in retail oil samples. Overall, 25% of soybean and peanut oils and 12.5% of corn and blended oil were detected with AFTs, and no capsaicinoid was found. The content of AFTs was under the MRLs set by EU and China regulation for food quality and safety. The validated results indicated that this method could be utilized for a rapid, efficient, and accurate quantification of AFTs and capsaicinoids in complex lipid‐based matrix.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".