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Record W2970406808

Quantification and distribution of pharmaceuticals and their human metabolite conjugates in a municipal wastewater treatment plant

2019· dissertation· en· W2970406808 on OpenAlexaboutno aff
Alistair K. Brown

Bibliographic record

VenueMspace (University of Manitoba) · 2019
Typedissertation
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsMetaboliteWastewaterConjugateDistribution (mathematics)Sewage treatmentEnvironmental scienceChemistryEnvironmental chemistryChromatographyEnvironmental engineeringMathematicsBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

Pharmaceuticals have the potential to persist environmentally through constant anthropogenic input via wastewaters. Toxic effects, both acute and chronic, can be elicited on non-target organisms within the aquatic environment depending on both species sensitivity and chemical class. Overall toxicity can be due to not only parent compounds but transformation products (TPs) as well. It was hypothesised that levels of pharmaceutical TP conjugates would rival those of the parent compounds within a major point source of pharmaceuticals (i.e. wastewater). This thesis successfully developed quantitative methods, for the first time, for four different classes of pharmaceuticals and three different types of conjugate TPs using weak anion exchange solid phase extraction in conjunction with liquid chromatography-tandem mass spectrometry for wastewaters and associated solids; and was validated using the North End Waste Pollution Control Centre located in Winnipeg, Canada. A three-month pilot experiment was conducted using these methods and highlighted the levels of acetaminophen, propranolol, sulfamethoxazole, and thyroxine, in addition to associated conjugate TPs: acetaminophen sulfate, propranolol sulfate, N-acetyl sulfamethoxazole, sulfamethoxazole glucuronide, thyroxine glucuronide. Four different stages of wastewater processing were analysed (primary effluent, secondary effluent, mixed liquor, and final effluent), and levels in aqueous and solid phases assessed. Overall, acetaminophen was rapidly attenuated from primary to secondary effluent (>99%), propranolol and thyroxine persisted without any notable attenuation, and sulfamethoxazole were attenuated by approximately 67-78% from primary to secondary effluent; however the ratio of the three compounds remained consistent across treatments. Several batch bioreactor experiments using primary and secondary effluent, were conducted to backstop what was seen environmentally. In addition, plausible mechanisms for temporospatial variation (i.e. removal/ attenuation) were inferred. For the first time, bioreactor results showed concomitant effects on TP levels in the laboratory that were seen environmentally. In conclusion, levels of conjugates across all four classes of compounds, whether an acid, base, or zwitterion, did indeed rival those of the parent compounds within wastewaters. Sorption of ionisable pharmaceutical conjugates seems to be driven by hydrophobicity in the presence of substantial organic matter. Thus, dependent on pedoclimatic conditions, exposure levels and ostensibly the fate of these pharmaceutical TPs can vary.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.033
GPT teacher head0.263
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

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