MétaCan
Menu
Back to cohort
Record W4380680896 · doi:10.1038/s41545-023-00261-x

Transition of antimicrobial resistome in wastewater treatment plants: impact of process configuration, geographical location and season

2023· article· en· W4380680896 on OpenAlexfundno aff
Ryo Honda, Norihisa Matsuura, Sovannlaksmy Sorn, Sawako Asakura, Yuta Morinaga, Than Van Huy, Muhammad Adnan Sabar, Yalkhin Masakke, Hiroe Hara-Yamamura, Toru Watanabe

Bibliographic record

Venuenpj Clean Water · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsnot available
FundersInstitute of GeneticsJST-Mirai ProgramJapan Science and Technology AgencyJapan Society for the Promotion of ScienceKurita Water and Environment Foundation
KeywordsResistomeEffluentWastewaterSewage treatmentAntimicrobialActivated sludgeEffluxBiologyMetagenomicsAntibioticsBiomass (ecology)Antibiotic resistanceMicrobiologyBiotechnologyEnvironmental engineeringEnvironmental scienceEcologyBiochemistry

Abstract

fetched live from OpenAlex

Abstract Antimicrobial resistome in wastewater treatment plants was investigated via shotgun metagenomic analysis over a variety of geographical locations, seasons, and biological treatment configurations. The results revealed that the transition of the antimicrobial resistome occurred at two locations during wastewater treatment, which resulted in a distinctive antimicrobial resistome in influent wastewater, activated sludge, and treated effluent. The antimicrobial resistome in influent wastewater was characterized by a high abundance of antibiotic resistance genes (ARGs) on clinically important drugs, whereas sludge retained a higher abundance of multidrug ARGs associated with efflux pump. Seasonality was the primary factor affecting antimicrobial resistome in influent wastewater, which partially succeeded to the subsequent resistome of activated sludge and treated effluent. Importantly, some ARGs on clinically important drugs in influent wastewater passed through the biological treatment to be discharged in the treated effluent, except in the membrane bioreactor process.

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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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

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 head0.016
GPT teacher head0.278
Teacher spread0.262 · 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

Citations55
Published2023
Admission routes1
Has abstractyes

Explore more

Same venuenpj Clean WaterSame topicPharmaceutical and Antibiotic Environmental ImpactsFrench-language works237,207