Quantification of fluoroquinolones, triclosan and triclocarban in wastewater and biosolids by on-line solid-phase extraction LC-MS/MS
Bibliographic record
Abstract
The consequences of the spread of antimicrobial resistance (AMR) are alarming and require an urgent initiative of concerted global effort. The use of contaminated biosolids as fertilizer under the circular economy initiative is increasing the return of pharmaceuticals consumed by humans to agricultural soils, creating a contamination pathway known as "feces-to-farm". This article focuses on the quantification of pharmaceuticals in wastewater treatment plant (WWTP) by-products as a possible source of AMR dissemination. To this end, two analytical methods have been developed using on-line SPE coupled to UHPLC-MS/MS for the simultaneous analysis of 33 different targeted pharmaceuticals in wastewater, sludge and biosolids. Target compounds include 31 different fluoroquinolones antimicrobials and two different antimicrobials, triclosan (TCS) and triclocarban (TCC). The developed methods have been validated in the respective matrices, and their specific limits of detection (LOD) and quantification (LOQ) were lower than methods reported in the literature with similar equipment while targeting a small number of antibiotics. The method developed for wastewater samples enables direct analysis without any sample preparation step, unlike the methods available in the literature. Extraction of biosolids samples was complemented by ultrasonic-assisted extraction (UAE). Both methods feature high sensitivity, a wide linearity range (10–5000 ng/L and 0.6–1000 μg/kg), high precision and RSDs below 3 % for most of the targeted antibiotics. The methods were successfully applied for the quantification of targeted antimicrobials in biosolids samples as well as in influent and effluent wastewater samples from 12 different wastewater treatment plants covering 6 different Canadian provinces. Results indicate the presence of fluoroquinolone antibiotics, TCS and TCC antimicrobial agents in all samples analyzed. Concentrations detected in biosolids ranged from 962 to 4408 μg/kg for FQ, 1945 to 10 237 μg/kg for TCS and 338–1290 μg/kg, for TCC. Concentrations detected in wastewater samples were lower and ranged from 12 to 73 ng/L for fluoroquinolones, from 4 to 35 ng/L for TCS and from 24 to 44 ng/L for TCC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".