Tracing the Biotransformation of Polycyclic Aromatic Hydrocarbons in Contaminated Soil Using Stable Isotope-Assisted Metabolomics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Biotransformation of organic pollutants may result in the formation of oxidation products that are more toxic than the parent contaminants. However, tracing and identifying those products, and the metabolic pathways involved in their formation, are still challenging within complex environmental samples. We applied stable isotope-assisted metabolomics (SIAM) to polycyclic aromatic hydrocarbon-contaminated soil collected from a wood treatment facility. Soil samples were separately spiked with uniformly 13 C-labeled fluoranthene, pyrene, or benzo[ a ]anthracene at a level below that of the native contaminant and incubated for 1 or 2 weeks under aerobic biostimulated conditions. Combining high-resolution mass spectrometry and automated SIAM workflows, we propose chemical structures of metabolites and metabolic pathways in the soil. Ring-cleavage products, including previously unreported intermediates such as C 11 H 10 O 6 and C 15 H 12 O 5, were detected originating from fluoranthene and benzo[ a ]anthracene, respectively. Sulfate conjugates of dihydroxy compounds were found as major metabolites of pyrene and benzo[ a ]anthracene, suggesting the potential role of fungi in their biotransformation in soils. A series of unknown N-containing metabolites were identified from pyrene, but their structural elucidation requires further investigation. Our results suggest that SIAM can be successfully applied to understand the fate of organic pollutants in environmental samples, opening lines of evidence for novel mechanisms of microbial transformation within such complex matrices.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.007 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it