Determination of Basic Antidepressants and Their <i>N</i>-Desmethyl Metabolites in Raw Sewage and Wastewater Using Solid-Phase Extraction and Liquid Chromatography−Tandem Mass Spectrometry
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
A novel analytical method has been developed for the determination of six basic antidepressants (venlafaxine, sertraline, paroxetine, citalopram, amitriptyline, and fluoxetine) and four of their metabolites (O-desmethylvenlafaxine, desmethylsertraline, nortriptyline, and norfluoxetine) in raw sewage and roughly primary-treated wastewater. For analytical development purposes, two ion exchange solid-phase extraction cartridges were compared. Extracts were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) with positive-mode electrospray (+ESI) and selected reaction monitoring transitions. The choice of a basic mobile phase significantly improved the instrumental sensitivity (by up to 14-fold for norfluoxetine) relative to common +ESI acidic mobile phases. In addition to the remarkable gain in sensitivity, negligible matrix effects were also observed in the raw sewage samples. Analyte recoveries ranged from 80 to 103% and effluent detection limits from 0.048 to 0.10 ng/L. Samples collected at the Montreal Wastewater Treatment Plant showed the unequivocal presence of all the target compounds at concentrations of 2-346 ng/L. The target antidepressants were also detected in samples taken from the effluent receiving waters (i.e., the St. Lawrence River) but at lower concentrations (0.41-69 ng/L). The highly sensitive proposed method constitutes one of the best means for monitoring the environmental occurrence of tricyclic antidepressants, selective serotonin reuptake inhibitors (SSRIs), and some of their metabolites.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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