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Record W2984305548 · doi:10.1111/1462-2920.14860

Exploring bacterial pathogen community dynamics in freshwater beach sediments: A tale of two lakes

2019· article· en· W2984305548 on OpenAlexafffundabout
Danielle VanMensel, Subba Rao Chaganti, Ian G. Droppo, Christopher G. Weisener

Bibliographic record

VenueEnvironmental Microbiology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsEnvironment and Climate Change CanadaUniversity of Windsor
FundersUniversity of WindsorNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsBiologySedimentFreshwater ecosystemEcologyWater columnEcosystemVirulencePathogenWater qualityGeneMicrobiologyGenetics

Abstract

fetched live from OpenAlex

Pathogenic bacteria associated with freshwater ecosystems can pose significant health risks particularly where recreational water use is popular. Common water quality assessments involve quantifying indicator Escherichia coli within the water column but neglect to consider physical and geochemical factors and contributions from the sediment. In this study, we used high-throughput sequencing to investigate sediment microbial communities at four freshwater public beaches in southern Ontario, Canada and analysed community structure, function, and gene expression with relation to geographical characteristics. Our results indicate that beach sediments at the sediment-water interface could serve as potential sources of bacterial contamination under low-energy environments with tightly packed small sediment particles compared with high-energy environments. Further, the absence of pathogens but expression of pathogenic transcripts suggests occurrence of alternate gene acquisition. Pathogenicity at these locations included expression of Salmonella virulence factors, genes involved in pertussis, and antimicrobial resistance. Finally, we introduce a proposed universal bacterial pathogen model to consider the combined and synergistic processes used by these microbes. To our knowledge, this is the first study of its kind to investigate chemolithotrophic activity related to pathogens within bed sediment at freshwater beaches. This work helps advance current understanding of health risks in these environments.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0160.001

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 head0.018
GPT teacher head0.208
Teacher spread0.190 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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

Citations19
Published2019
Admission routes3
Has abstractyes

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