Development and validation of a method for the determination of aminoglycosides in foods using LC‐MS/MS with a zwitterionic HILIC stationary phase
Bibliographic record
Abstract
Aminoglycosides (AMGs) are broad-spectrum antibiotics that have bactericidal activity against aerobic bacterial infection and are commonly used as veterinary drugs on food-producing animals and in human medicine.Thus, it is important to monitor residues in food to control AMG use.Many countries have established maximum residue limits (MRL) for aminoglycosides approved for use on animals.AMGs are often analyzed in honey, eggs, milk, tissues, and biofluids of foodproducing animals for control and monitoring purposes.AMGs are highly polar compounds and show little to no retention in reversed phase columns.Although ionpairing reagents have been utilized successfully to chromatograph AMGs on C18 columns, when used with liquid chromatography tandem mass spectrometry (LC-MS/MS) this approach suffers from ion suppression and contamination of the LC and MS/MS systems.The introduction of hydrophilic interaction chromatography (HILIC) provided a more MS-compatible option for the analysis of polar compounds.Here we show the results from the successful evaluation of the Atlantis Premier BEH Z-HILIC column, which has a sulfobetaine zwitterionic chemistry, for the determination of AMGs.Samples of milk, eggs, and honey were extracted using a solution that contained 10 mM ammonium acetate, 0.4mM ethylenediamine tetraacetic acid (EDTA), 0.5% NaCl, and 2% trichloroacetic acid (TCA) and subjected to clean-up by Solid-Phase Extraction (SPE) on Oasis HLB cartridges prior to LC-MS/MS.The method was successfully validated according to Commission Implementing Regulation (EU) 2021/808 and is suitable for reliable determination of residues to check compliance with MRLs and in cases where use of the substances is not allowed.
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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 | 0.000 |
| 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) | 0.000 | 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".