Diagnostic Ions for the Analysis of Phenylalanine Adducts of Acrylamide and Styrene by ESI-QTOF Mass Spectrometry
Bibliographic record
Abstract
To facilitate the detection of acrylamide or styrene adduct of amino acids by mass spectrometry based techniques, phenylalanine was used as a representative amino acid and pyrolysis was employed in conjunction with isotope labeling technique as a microscale sample preparation tool to generate the reaction products. The residues remaining after the pyrolysis of phenylalanine/styrene, phenylalanine/acrylamide, and phenylalanine/glucose mixtures at 250 °C were analyzed by electrospray quadrupole time-of-flight (ESI-QqTOF) mass spectrometry to identify the adducts. The phenylalanine/acrylamide adduct was independently synthesized for confirmation. Characteristic product ions in the tandem mass spectra were found at m/z 191 for the acrylamide adduct and at m/z 262 and 190 for its double-addition product. On the other hand, an ion at m/z 224 was shown to be diagnostic of the styrene adduct. The ability of the m/z 224 ion to predict the presence of styrene adduct in a heated phenylalanine/glucose model system was tested and verified. Detailed isotope labeling analysis of the phenylalanine/glucose model further indicated the formation of a novel adduct that was consistent with the reaction of the Amadori product with styrene. Such diagnostic ions that are needed to develop MS/MS-based screening methodologies may accelerate in the future the detection of Michael-type adducts in food.
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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".