Carbohydrate and Amino Acid Degradation Pathways in <scp>l</scp>-Methionine/<scp>d</scp>-[<sup>13</sup>C] Glucose Model Systems
Bibliographic record
Abstract
Maillard model systems consisting of labeled D-[(13)C]glucoses, L-[(15)N]methionine, and L-[methyl-(13)C]methionine, have been utilized to identify the amino acid and carbohydrate fragmentation pathways occurring in the model system through Py-GC/MS analysis. The label incorporation analyses have indicated that the carbohydrate moiety produces 1-deoxy- and 3-deoxyglucosones and undergoes C(2)/C(4) and C(3)/C(3) cleavages to produce glycolaldehyde, tetrose, and C(3)-reactive sugar derivatives such as acetol, glyceraldehyde, and pyruvaldehyde. Glycolaldehyde was found to incorporate C-1, C-2 (70%) and C-5, C-6 (30%) glucose carbon fragments, whereas the tetrose moiety incorporates only C-3, C-4, C-5, C-6 glucose carbon atoms. In addition, the major source of reactive C(3) fragments was found to contain C-4, C-5, C-6 sugar moiety. On the other hand, methionine alone also generated Strecker aldehyde as detected by its condensation product with 3-(methylthio)propylamine. Plausible mechanisms were proposed for the formation of the interaction products between sugar and amino acid degradation products on the basis of the label incorporation patterns.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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".