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Record W3080284944 · doi:10.1016/j.envint.2020.106035

A global multinational survey of cefotaxime-resistant coliforms in urban wastewater treatment plants

2020· article· en· W3080284944 on OpenAlexaff
R Marano, Telma Fernandes, Célia M. Manaia, Olga C. Nunes, Donald A. Morrison, Thomas U. Berendonk, Norbert Kreuzinger, Tanel Tenson, Gianluca Corno, Despo Fatta‐Kassinos, Christophe Merlin, Edward Topp, Édouard Jurkevitch, Leonie Henn, Andrew Scott, Stefanie Heß, Katarzyna Ślipko, Mailis Laht, Veljo Kisand, Andrea Di Cesare, Popi Karaolia, Stella G. Michael, Alice L. Petre, Roberto Rosal, Amy Pruden, Virginia Riquelme, Ana Agüera, Belén Esteban, Aneta Łuczkiewicz, Agnieszka Kalinowska, Anne Frances Clare Leonard, William H. Gaze, Anthony A. Adegoke, Thor Axel Stenström, Alfieri Pollice, Carlo Salerno, Carsten Ulrich Schwermer, Paweł Krzemiński, Hélène Guilloteau, Erica Donner, Barbara Drigo, Giovanni Libralato, Marco Guida, Helmut Bürgmann, Karin Beck, Hemda Garelick, Marta Tacão, Isabel Henriques, Isabel Martínez‐Alcalá, José Manuel Guillén-Navarro, Magdalena Popowska, Marta Piotrowska, Marcos Quintela‐Baluja, Joshua T. Bunce, María Inmaculada Polo-López, Samira Nahim–Granados, Marie‐Noëlle Pons, Milena Milaković, Nikolina Udiković‐Kolić, Jérôme Ory, Traore Ousmane, Pilar Caballero, Antoni Oliver, Sara Rodríguez‐Mozaz, José Luís Balcázar, Thomas Jäger, Thomas Schwartz, Ying Yang, Shichun Zou, Yunho Lee, Younggun Yoon, Bastian Herzog, Heidrun Mayrhofer, Om Prakash, Yogesh Nimonkar, Ester Heath, Anna Baraniak, Joana Abreu-Silva, Manika Choudhury, Leonardo Pantoja Muñoz, Stela Križanović, Gianluca Brunetti, Ayella Maile-Moskowitz, Connor Brown, Eddie Cytryn

Bibliographic record

VenueEnvironment International · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsAgriculture and Agri-Food CanadaWestern University
FundersMedical Research CouncilNatural Environment Research CouncilEuropean Cooperation in Science and TechnologySight Research UKJoint Programming Initiative Water challenges for a changing world
KeywordsFecal coliformAntibiotic resistanceCefotaximeWastewaterSewage treatmentSewageEffluentVeterinary medicineEnvironmental healthEnvironmental scienceBiologyEnvironmental engineeringAntibioticsMicrobiologyMedicineWater qualityEcology

Abstract

fetched live from OpenAlex

The World Health Organization Global Action Plan recommends integrated surveillance programs as crucial strategies for monitoring antibiotic resistance. Although several national surveillance programs are in place for clinical and veterinary settings, no such schemes exist for monitoring antibiotic-resistant bacteria in the environment. In this transnational study, we developed, validated, and tested a low-cost surveillance and easy to implement approach to evaluate antibiotic resistance in wastewater treatment plants (WWTPs) by targeting cefotaxime-resistant (CTX-R) coliforms as indicators. The rationale for this approach was: i) coliform quantification methods are internationally accepted as indicators of fecal contamination in recreational waters and are therefore routinely applied in analytical labs; ii) CTX-R coliforms are clinically relevant, associated with extended-spectrum β-lactamases (ESBLs), and are rare in pristine environments. We analyzed 57 WWTPs in 22 countries across Europe, Asia, Africa, Australia, and North America. CTX-R coliforms were ubiquitous in raw sewage and their relative abundance varied significantly (<0.1% to 38.3%), being positively correlated (p < 0.001) with regional atmospheric temperatures. Although most WWTPs removed large proportions of CTX-R coliforms, loads over 103 colony-forming units per mL were occasionally observed in final effluents. We demonstrate that CTX-R coliform monitoring is a feasible and affordable approach to assess wastewater antibiotic resistance status.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.064
Threshold uncertainty score0.443

Codex and Gemma teacher scores by category

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 communication0.0000.000
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 head0.015
GPT teacher head0.239
Teacher spread0.224 · 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 teacher head, 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

Citations85
Published2020
Admission routes1
Has abstractyes

Explore more

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