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Fluoroquinolone Resistance in Clinical Isolates of <i>Streptococcus pneumoniae</i> : Contributions of Type II Topoisomerase Mutations and Efflux to Levels of Resistance

2000· article· en· W2147990519 on OpenAlexafffund
Darrin J. Bast, Donald E. Low, Carla Duncan, Laurie Kilburn, Lionel A. Mandell, Ross Davidson, Joyce C. S. de Azavedo

Bibliographic record

VenueAntimicrobial Agents and Chemotherapy · 2000
Typearticle
Languageen
FieldMedicine
TopicPneumonia and Respiratory Infections
Canadian institutionsQueen Elizabeth II Health Sciences CentreUniversity Health NetworkUniversity of TorontoDalhousie UniversityHamilton Health SciencesMcMaster University
FundersMedical Research CouncilMedical Research Council Canada
KeywordsEffluxCiprofloxacinBiologyMicrobiologyStreptococcus pneumoniaeTopoisomerase IVAmino acid substitutionQuinoloneAmino acidCross-resistanceStreptococcaceaeMutationDNA gyraseGeneticsGeneAntibioticsEscherichia coli

Abstract

fetched live from OpenAlex

We report on amino acid substitutions in the quinolone resistance-determining region of type II topisomerases and the prevalence of reserpine-inhibited efflux for 70 clinical isolates of S. pneumoniae for which the ciprofloxacin MIC is >/=4 microgram/ml and 28 isolates for which the ciprofloxacin MIC is </=2 microgram/ml. The amino acid substitutions in ParC conferring low-level resistance (MICs, 4 to 8 microgram/ml) included Phe, Tyr, and Ala for Ser-79; Asn, Ala, Gly, Tyr, and Val for Asp-83; Asn for Asp-78; and Pro for Ala-115. Isolates with intermediate-level (MICs, 16 to 32 microgram/ml) and high-level (MICs, 64 microgram/ml) resistance harbored substitutions of Phe and Tyr for Ser-79 or Asn and Ala for Asp-83 in ParC and an additional substitution in GyrA which included either Glu-85-Lys (Gly) or Ser-81-Phe (Tyr). Glu-85-Lys was found exclusively in isolates with high-level resistance. Efflux contributed primarily to low-level resistance in isolates with or without an amino acid substitution in ParC. The impact of amino acid substitutions in ParE was minimal, and no substitutions in GyrB were identified.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.685
Threshold uncertainty score0.431

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 head0.017
GPT teacher head0.314
Teacher spread0.297 · 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

Citations121
Published2000
Admission routes2
Has abstractyes

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