Optimization of Aflatoxin B1-Lysine Analysis for Public Health Exposure Studies
Bibliographic record
Abstract
Aflatoxin B1 is a potent human carcinogen produced by several species of Aspergillus mainly found on nuts and maize. Exposures in parts of Africa, Latin America and Asia can be at multiples, sometimes orders of magnitude above tolerable daily levels. Although human exposure to aflatoxin can be estimated by analysis of the diet, only determination of the serum albumin aflatoxin adduct provides a health-relevant exposure measure. The lack of a reference serum limits interlaboratory method validation and data comparisons. In this study, we synthetically produced AFB1-dialdehyde and covalently coupled it to serum albumin in human serum. This synthetic produced aflatoxin-serum reference material was used in conjunction with isotopically labelled internal standards to evaluate sample digestion methods. This showed using sufficient Pronase in the digestion step was critical to ensure complete proteolytic digestion, which occurs within 4 h. Increasing the digestion temperature from 37 °C to 50 °C also provided a benefit to the overall analysis. In addition, the use of dried blood spots and Volumetric Absorptive Microsampling (VAMS) were investigated showing samples stored with VAMS produced equivalent results to serum samples.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".