Determination of Pharmaceutical Residues in Fish Bile by Solid-Phase Microextraction Couple with Liquid Chromatography-Tandem Mass Spectrometry (LC/MS/MS)
Bibliographic record
Abstract
The present study investigates possible uptake and bioconcentration of different classes of pharmaceuticals residues (organic contaminants) in fish bile using a simplified analytical methodology based on solid phase microextration (SPME). The use of solid phase microextraction (SPME), as a simple analytical tool, to screen for target pharmaceuticals in fish bile samples was validated in rainbow trout (Oncorhynchus mykiss) following short-term laboratory exposures to carbamazepine and fluoxetine. While fish bioconcentrated both fluoxetine and carbamazepine from exposure water, fluoxetine accumulated to a greater degree in bile than carbamazepine. Good agreement was obtained for both analytes in bile samples between SPME and traditional liquid (solvent) extraction approaches (R(2) > 0.99). The field application of SPME sampling was further demonstrated in fathead minnow (Pimephales promelas), a small-bodied fish caged upstream and downstream of a local wastewater treatment plant where fluoxetine, atorvastatin, and sertraline were detected in fish bile at the downstream location. SPME is a promising analytical tool for investigating the bioconcentration of trace contaminants in fish bile, facilitating detection of trace environmental contaminants otherwise undetectable due to low concentrations in the environment and biological tissues as well as the complexity of the sample matrices.
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How this classification was reachedexpand
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 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".