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

2011· article· en· W1692755931 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.863
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
Bibliometrics0.0010.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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