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Record W2593630478 · doi:10.5203/pmuser.201620560

Are aquatic snails reservoirs and vectors of microbes bearing antibiotic resistant genes

2016· article· en· W2593630478 on OpenAlexafffund
Angela Reeves, Chelsea Lobson, Jonathan K. Challis, Dana Moore, Mark L. Hanson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Manitoba
KeywordsSnailBiologyMicrobiomeFreshwater snailMicrobiologyZoologyEcology

Abstract

fetched live from OpenAlex

The role of Stagnicola elodes, a freshwater snail, as a reservoir and vector for transporting antibiotic resistant genes (ARGs) was explored under laboratory conditions. We hypothesized that ARG-bearing microorganisms would become part of the snail gut microbiome allowing ARGs to be spread from their initial point of origin should snails be transported or the input of pharmaceuticals cease. We exposed snails in jars for 14 days wherein they grazed on biofilms that contained microbes resistant to the antibiotic sulfamethoxazole (SMX). Snails were then transferred to fresh media with no SMX for either a 7-day hibernation or depuration period. SMX-related ARGs were quantified in the 14-day treatment and 7-day depuration and hibernation systems. On day 14, treated jars had 6.6% of SMX resistant genes in the water phase, and the 7-day hibernation and depuration vessels had an average of 3.9% and 1.4%, respectively, relative to the total water-borne microbial community. Methods of extracting snail samples for SMX-related ARGs were unsuccessful. This was attributed to the snails’ having extensive mucus sugars that interfere with extraction. Our findings suggest that ARGs could be transferred to new environments from snails excreting gut flora in their feces, warranting further investigation.

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 score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.029
GPT teacher head0.261
Teacher spread0.232 · 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
Published2016
Admission routes2
Has abstractyes

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