Synergistic Inhibitory Effects of Selected Amino Acids on the Formation of 2-Amino-1-methyl-6-phenylimidazo[4,5-<i>b</i>]pyridine (PhIP) in both Benzaldehyde– and Phenylacetaldehyde–Creatinine Model Systems
Bibliographic record
Abstract
Although various inhibitors have been employed to react with phenylacetaldehyde to form adducts and thus interrupt the formation of 2-amino-1-methyl-6-phenylimidazo[4,5- b ]pyridine (PhIP), high concentrations of PhIP remain in the final system. It remains unknown whether other critical aldehyde or ketone intermediates are involved in the generation of PhIP, and scavenging these reactive carbonyls simultaneously may achieve higher inhibitory efficiency of PhIP. In this study, reactive carbonyls in a glucose/creatinine/phenylalanine model system were first identified by gas chromatography–mass spectrometry (GC–MS), and then the single and synergistic effects of nonprecursor amino acids (cysteine, methionine, proline, histidine, arginine, and leucine) on scavenging reactive carbonyls were investigated to find out promising combination partners. The obtained results showed that the concentrations of benzaldehyde and phenylacetaldehyde in the glucose/creatinine/phenylalanine model system reached 0.49 ± 0.01 and 6.22 ± 0.21 μg/mL, respectively. Heating these carbonyl compounds in the presence of creatinine resulted in the quantity of PhIP produced increasing linearly with the added quantity of benzaldehyde ( r = 0.9733, P = 0.0002) and phenylacetaldehyde ( r = 0.9746, P = 0.0002), indicating that both compounds are key intermediates for PhIP generation. Among the investigated amino acids, histidine produced the maximum inhibition of PhIP formation (78–99%) in the benzaldehyde/creatinine model system, and proline produced the maximum inhibition of PhIP formation (13–97%) in the phenylacetaldehyde/creatinine model system, where both compounds decreased PhIP formation in a dose-dependent manner. Histidine in combination with proline enhanced the inhibitory effect against PhIP formation at a low addition level, where the highest inhibitory efficiency was obtained using a 1:3 mass ratio of histidine to proline (2 mg/mL in total), reducing PhIP formation by 96%. These findings suggest that histidine–proline combinations can scavenge benzaldehyde and phenylacetaldehyde simultaneously, enhancing the suppression of PhIP formation.
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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) | 0.000 | 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".