Persistence of the tricyclic antidepressant drugs amitriptyline and nortriptyline in agriculture soils
Bibliographic record
Abstract
Amitriptyline and nortriptyline are widely used tricyclic antidepressant drugs. They have been detected in wastewater, surface runoff, and effluents from sewage treatment plants. As such, they could potentially reach agriculture land through the application of municipal biosolids or reclaimed water. In the absence of data on their fate in the environment, the persistence and dissipation pathways of radiolabeled amitriptyline were determined in three agriculture soils varying widely in texture and chemical properties (loam soil, clay loam soil, and sandy loam soil). Tritiated amitriptyline was added to laboratory microcosms containing soils, and the metabolism of the extractable (3) H was monitored during incubation at 30°C. The total solvent extractable radioactivity decreased in all three soils with times to dissipate 50% of material (DT50) ranging from 34.1 ± 3.2 (loam soil) to 85.3 ± 3.2 d (sandy soil). Nortriptyline (N-desmethyl amitriptyline) and amitriptyline-N-oxide were identified as major transformation products in all three soils by high performance liquid chromatography with photodiode array detector and time-of-flight mass spectrometry (HPLC-TOF-MS/UV). The addition of liquid municipal biosolids to the loam soil had no effect on the dissipation of amitriptyline. The persistence of nortriptyline was evaluated in the loam soil. The DT50 of nortriptyline was 40.5 ± 3.2 d estimated with HPLC-TOF-MS/UV. Approximately 10% of added nortriptyline was converted to hydroxylated products after 50 d of incubation. In summary, amitriptyline persisted in agricultural soils with major dissipation mechanisms, including forming nonextractable residues and producing various transformation products including the psychoactive drug nortriptyline.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".