Determination of a broad spectrum of pharmaceuticals and endocrine disruptors in biofilm from a waste water treatment plant-impacted river
Bibliographic record
Abstract
Wastewater treatment plants (WWTPs) are one of the main sources of pharmaceuticals and endocrine disrupting compounds in freshwater ecosystems, and several studies have reported bioaccumulation of these compounds in different organisms in those ecosystems. River biofilms are exceptional indicators of pollution, but very few studies have focused on the accumulation of these emerging contaminants. The objectives of this study were first to develop an efficient analytical methodology for the simultaneous analysis of 44 pharmaceuticals and 13 endocrine disrupting compounds in biofilm, and second, to assess persistence, distribution, and bioaccumulation of these contaminants in natural biofilms inhabiting a WWTP-impacted river. The method is based on pressurized liquid extraction, purification by solid-phase extraction, and analysis by ultra performance liquid chromatography coupled to a mass spectrometer (UPLC-MS/MS) in tandem. Recoveries for pharmaceuticals were 31-137%, and for endocrine disruptors 32-93%. Method detection limits for endocrine disruptors were in the range of 0.2-2.4 ng g(-1), and for pharmaceuticals, 0.07-6.7 ng g(-1). A total of five endocrine disruptors and seven pharmaceuticals were detected in field samples at concentrations up to 100 ng g(-1).
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.
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 | 0.000 | 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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".