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Record W4379598110 · doi:10.1002/etc.5684

Environmental Concentrations of the Type 2 Diabetes Medication Metformin and Its Transformation Product Guanylurea in Surface Water and Sediment in Ontario and Quebec, Canada

2023· article· en· W4379598110 on OpenAlexafffundabout
Cameron Littlejohn, Justin B. Renaud, Lyne Sabourin, David R. Lapen, Jane J. Pappas, Bindu Tuteja, Dianne Hughes, Erin Ussery, Ken K.‐C. Yeung, Mark W. Sumarah

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsEnvironment and Climate Change CanadaHealth CanadaAgriculture and Agri-Food CanadaWestern University
FundersHealth Canada
KeywordsMetforminEnvironmental scienceSurface waterSedimentEnvironmental chemistryMedicineEnvironmental engineeringDiabetes mellitusChemistryBiology

Abstract

fetched live from OpenAlex

Metformin, used to treat Type 2 diabetes, is the active ingredient of one of the most prescribed drugs in the world, with over 120 million yearly prescriptions globally. In wastewater-treatment plants (WWTPs), metformin can undergo microbial transformation to form the product guanylurea, which could have toxicological relevance in the environment. Surface water samples from 2018 to 2020 and sediment samples from 2020 were collected from six mixed-use watersheds in Quebec and Ontario, Canada, and analyzed to determine the metformin and guanylurea concentrations at each site. Metformin and guanylurea were present above their limits of quantification in 51.0% and 50.7% of all water samples and in 64% and 21% of all sediment samples, respectively. In surface water, guanylurea was often present at higher concentrations than metformin, while the inverse was true in sediment, with metformin frequently detected at higher concentrations than guanylurea. In addition, at all sites influenced solely by agriculture, concentrations of metformin and guanylurea were <1 µg/L in surface water, suggesting that agriculture is not a significant source of these compounds in the investigated watersheds. These data suggest that WWTPs and potentially septic system leaks are the most likely sources of the compounds in the environment. Guanylurea was detected at many of these sites above environmental concentrations of concern, where critical processes in fish may be affected. Due to the scarcity of available ecotoxicological data and the prominence of guanylurea across all sample sites, there is a need to perform more toxicological investigations of this transformation product and revisit regulations. The present study will help provide toxicologists with environmentally relevant concentration ranges in Canada. Environ Toxicol Chem 2023;42:1709-1720. © 2023 His Majesty the King in Right of Canada and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. Reproduced with the permission of the Minister of Agriculture and Agri-Food Canada.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.185

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.208
Teacher spread0.199 · 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

Citations11
Published2023
Admission routes3
Has abstractyes

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