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Record W4388793477 · doi:10.1093/jambio/lxad258

Planktonic and biofilm states of <i>Staphylococcus aureus</i> isolated from bone and joint infections and the <i>in vitro</i> effect of orally available antibiotics

2023· article· en· W4388793477 on OpenAlexaboutno aff
Eduardo Pérez-Alba, Samantha Flores-Treviño, Verónica Villarreal-Salazar, Paola Bocanegra‐Ibarias, Félix Vílchez‐Cavazos, Adrián Camacho-Ortíz

Bibliographic record

VenueJournal of Applied Microbiology · 2023
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Infections and Treatments
Canadian institutionsnot available
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsBiofilmMoxifloxacinMicrobiologyAntibioticsStaphylococcus aureusDoxycyclineAntimicrobialMinimum inhibitory concentrationBiologyMedicineBacteria

Abstract

fetched live from OpenAlex

AIMS: To demonstrate the in vitro activity of orally available antibiotics against Staphylococcus aureus isolated from bone or orthopedic implant materials. The biofilm eradication of the combination of three antibiotics was also assessed. METHODS AND RESULTS: Clinical isolates from orthopedic infection samples were collected, and S. aureus isolates were classified according to their biofilm production and composition. Almost all S. aureus isolates (n = 36, 97.3%) produced biofilm and the major biofilm components were polysaccharides. Antimicrobial susceptibility was determined in planktonic (minimal inhibitory concentration; MIC) and biofilm cells (minimal biofilm eradication concentration; MBEC) using the MBEC Calgary Device. Overall, the MBEC ranged higher than the MIC. When combined at borderline-susceptible concentrations, moxifloxacin-rifampin and doxycycline-rifampin were both able to eradicate biofilms in a third of the strains whereas the doxycycline-moxifloxacin combination proved ineffective at eradicating biofilm, inhibiting it only in three strains. CONCLUSIONS: We propose rifampin in combination with moxifloxacin or doxycycline for the design of clinical trials of bone and/or orthopedic device infection without proper debridement or material retention.

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 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 score0.045
Threshold uncertainty score0.315

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 studies0.0000.000
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 head0.005
GPT teacher head0.215
Teacher spread0.210 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

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