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Chloraminated drinking water does not generate bacterial resistance to antibiotics in Pseudomonas aeruginosa biofilms

2008· article· en· W2089434222 on OpenAlexaff
Dawn Julie Jurgens, Syed A. Sattar, Thien‐Fah Mah

Bibliographic record

VenueLetters in Applied Microbiology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMicrobiologyPseudomonas aeruginosaTobramycinCiprofloxacinBiofilmChloramineGentamicinAntibioticsRifampicinChloramphenicolAntibiotic resistanceDisinfectantBacteriaChemistryBiologyChlorine

Abstract

fetched live from OpenAlex

AIM: To determine if exposure of Pseudomonas aeruginosa biofilms to chloraminated drinking water can lead to individual bacteria with resistance to antibiotics. METHODS AND RESULTS: Biofilms of P. aeruginosa PA14 were grown in drinking water in a Kadouri drip-fed reactor; the biofilms were treated with either 0.5 mg l(-1) or 1.0 mg l(-1) of chloramine for 15 or 21 days; control biofilms were grown in water without chloramine. Fewer isolates with antibiotic resistance were obtained from the chloramine-treated biofilms as compared to the control. Minimum inhibitory concentrations (MIC) for selected antibiotic-resistant isolates were determined using ciprofloxacin, tobramycin, gentamicin, rifampicin and chloramphenicol. All of the isolates tested had increased resistance over the wildtype to ciprofloxacin, rifampicin and chloramphenicol, but were not resistant to tobramycin or gentamicin. CONCLUSIONS: Under these test conditions, there was no detectable increase in antibiotic resistance in P. aeruginosa exposed as biofilms to disinfectant residues in chloraminated drinking water. SIGNIFICANCE AND IMPACT OF THE STUDY: Chloramine in drinking water, while unable to kill biofilm bacteria, does not increase the potential of P. aeruginosa to become resistant to antibiotics.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.670

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)0.0000.001

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 head0.007
GPT teacher head0.185
Teacher spread0.178 · 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 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

Citations14
Published2008
Admission routes1
Has abstractyes

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