MétaCan
Menu
Back to cohort

Transcriptional analysis of antibiotic resistance and virulence genes in multiresistant hospital-acquired MRSA

2011· article· en· W1692755931 on OpenAlexaff
Mireille Pruneau, Gabriel Mitchell, Hélène Moisan, Émilie Dumont-Blanchette, Christian L. Jacob, François Malouin

Bibliographic record

VenueFEMS Immunology & Medical Microbiology · 2011
Typearticle
Languageen
FieldMedicine
TopicAntimicrobial Resistance in Staphylococcus
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsVirulenceMicrobiologyStaphylococcus aureusAntibioticsBiologyEffluxAntibiotic resistanceGeneMethicillin-resistant Staphylococcus aureusStaphylococcal infectionsDrug resistancePhenotypeAntibacterial agentBacteriaGenetics

Abstract

fetched live from OpenAlex

The staphylococcal chromosome cassette mec cannot solely explain the multiresistance phenotype or the relatively mild virulence profile of hospital-acquired methicillin-resistant Staphylococcus aureus (HA-MRSA). This study reports that several multiresistant HA-MRSA strains differently expressed genes that may support antibiotic resistance, modify the bacterial surface and influence the pathogenic process. Genes encoding efflux pumps (norA, arsB, emrB) and the macrolide resistance gene ermA were found to be commonly expressed by HA-MRSA strains, but not in the archetypal MRSA strain COL. At equivalent cell density, the agr system was considerably less activated in all MRSA strains (including COL) in comparison with a prototypic antibiotic-susceptible strain. These results are in contrast to those observed in recent community-acquired MRSA isolates and may partly explain how multiresistant HA-MRSA persist in the hospital setting.

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)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.015
GPT teacher head0.251
Teacher spread0.235 · 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

Citations22
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueFEMS Immunology & Medical MicrobiologySame topicAntimicrobial Resistance in StaphylococcusFrench-language works237,207