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Record W2004709419 · doi:10.1186/1746-6148-8-225

Efficacy of clarithromycin on biofilm formation of methicillin-resistant Staphylococcus pseudintermedius

2012· article· en· W2004709419 on OpenAlexafffund
Matthew DiCicco, Suresh Neethirajan, Ameet Singh, J. Scott Weese

Bibliographic record

VenueBMC Veterinary Research · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial biofilms and quorum sensing
Canadian institutionsUniversity of Guelph
FundersOVC Pet TrustNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsStaphylococcus pseudintermediusBiofilmMicrobiologyClarithromycinIn vitroAntibioticsStaphylococcus aureusBiologyAntimicrobialStaphylococcusChemistryBacteriaBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Surgical site infections (SSIs) caused by biofilm-forming methicillin-resistant Staphylococcus pseudintermedius (MRSP) have emerged as the most common hospital-acquired infections in companion animals. No methods currently exist for the therapeutic remediation of SSIs caused by MRSP in biofilms. Clarithromycin (CLA) has been shown to prevent biofilm formation by Staphylococcus aureus. This study aims to assess the in vitro activity of CLA in eradicating MRSP biofilm formation on various materials. RESULTS: Quantitative assay results (P = 0.5126) suggest that CLA does not eradicate MRSP biofilm formation on polystyrene after 4 - 24 h growth periods. Scanning electron micrographs confirmed that CLA did not eradicate MRSP biofilm formed on orthopaedic implants. CONCLUSIONS: By determining the in vitro characteristics and activities of MRSP isolates alone and against antibiotics, in vitro models of biofilm related infections can be made. In vitro data suggests that CLA does not effectively eradicate S. pseudintermedius biofilms in therapeutic doses.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.130
GPT teacher head0.383
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), 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

Citations37
Published2012
Admission routes2
Has abstractyes

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