Heterocyclic amines detected in cooked meats and fishes from street markets and restaurants in the city of Hanoi, Vietnam: A Pilot local field investigation findings in 2020
Bibliographic record
Abstract
Background: Street food has been a typical culinary feature of many countries. These foods, mainly, meats and fish, were often fried, and grilled with varied marinade and preparation. However, foods that contain a lot of protein after processing at high temperatures always have many risks, including cancer risks of which heterocyclic aromatic amines (HAAs) have been one of the typical compounds. However, there is a lack of data on HAAs in low- and medium-income countries to date. Objective: ]indole (AαC) in cooked meat and fish samples. Methods: Three standards including PhIP, MeIQx, AαC, and three isotopically labeled internal standards PhIP-d3, MeIQx-d3, and AαC-15N3 were purchased from Toronto Research Chemicals, Inc. (Toronto, Canada). Formic acid, HPLC-grade methanol, acetonitrile, water, sodium chloride, and magnesium sulfate were supplied by Sigma-Aldrich (St. Louis, MO, USA). We collected cooked meat and fish samples from street markets and restaurants in the area of Cau Giay district, Hanoi, Vietnam in 2020. The collected samples were prepared for LC-MS/MS analysis. Results: Among 23 selected samples of cooked beef, fish, chicken, and pork, we have detected PhIP(ng/g) in 9 samples (the mean 2.68, standard deviation 2.41, median 2.40, minimum 0.33, and maximum 7.19); and AαC(ng/g) in 6 samples (the mean 0.74, standard deviation 0.75, median 0.45, minimum 0.12, and maximum 1.90); and MeIQx(ng/g) was not detected in all samples. Three grilled pork samples were positive with AαC at a concentration of 0.75-1.95 ng/g. Five fish samples have been detected to contain PhIP at the concentration of mean of 3.17; the standard deviation of 1.47, and the median of 3.90 ng/g. Two fried chickens have been detected to contain PhIP at the concentration of 0.41 and 7.19 ng/g. Conclusions: We detected a considerable amount of PhIP concentration in the collected fried fish and other fried meat samples and AαC in grilled and fried pork, beef, and chicken samples. The findings warrant further measuring more compounds of the HAA group and extending the number of real samples, as well as types of samples for example cooked meats, fish, fried eggs, tofu, and other cooked food receipts by regions in Vietnam.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".