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Record W1990911266 · doi:10.1179/joc.2007.19.2.146

Antimicrobial Efficacy of Gatifloxacin and Moxifloxacin with and without Benzalkonium Chloride Compared with Ciprofloxacin and Levofloxacin Against Methicillin- Resistant<i>Staphylococcus aureus</i>

2007· article· en· W1990911266 on OpenAlexaff
Joseph M. Blondeau, S. Borsos, Christine K. Hesje

Bibliographic record

VenueJournal of Chemotherapy · 2007
Typearticle
Languageen
FieldMedicine
TopicAntibiotics Pharmacokinetics and Efficacy
Canadian institutionsUniversity of SaskatchewanRoyal University Hospital
Fundersnot available
KeywordsGatifloxacinMoxifloxacinBenzalkonium chlorideLevofloxacinCiprofloxacinStaphylococcus aureusMicrobiologyAntimicrobialMedicineChemistryAntibioticsBacteriaBiology

Abstract

fetched live from OpenAlex

We compared the antimicrobial activity of gatifloxacin and moxifloxacin with and without benzalkonium chloride (BAK) against clinical isolates of methicillin-resistant Staphylococcus aureus (MRSA). Minimum inhibitory concentrations (MICs) against clinical isolates of MRSA were evaluated. Approximately 10(5 )CFU/ml of methicillinresistant S. aureus was added to Mueller-Hinton broth containing two-fold concentration increments of drug. For the evaluation of gatifloxacin with BAK, 50 microg/ml of BAK were added to the first well of the plate with gatifloxacin or moxifloxacin and then serially diluted. The combination of gatifloxacin or moxifloxacin with BAK was more active than either fluoroquinolone without BAK. The MICs ranged from <or=0.008 microg/ml to 0.125 microg/ml for gatifloxacin plus BAK, from 0.063 microg/ml to (3)8 microg/ml with unpreserved gatifloxacin from <0.004 to 0.25 for moxifloxacin plus BAK, and from <or=0.016 microg/ml to 16.0 microg/ml with unpreserved moxifloxacin. The combinations of gatifloxacin or moxifloxacin and BAK were highly active against MRSA in vitro, providing MICs that were approximately 2- to 500-fold lower than the MICs provided by either gatifloxacin or moxifloxacin without BAK.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.079
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.285
Teacher spread0.270 · 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.

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

Citations36
Published2007
Admission routes1
Has abstractyes

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