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Record W3157515902 · doi:10.1128/aac.00514-21

Update on Multidrug Resistance Efflux Pumps in Acinetobacter spp.

2021· article· en· W3157515902 on OpenAlexafffund
Vanessa Kornelsen, Ayush Kumar

Bibliographic record

VenueAntimicrobial Agents and Chemotherapy · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsUniversity of Manitoba
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsEffluxAcinetobacterMultiple drug resistanceMicrobiologyAntibioticsBiologyAntibiotic resistanceAntimicrobialDrug resistanceAcinetobacter baumanniiBacteriaGeneticsPseudomonas aeruginosa

Abstract

fetched live from OpenAlex

Acinetobacter spp. have become of increased clinical importance as studies have shown the antimicrobial resistant potential of these species. Efflux pumps can lead to reduced susceptibility to a variety of antibiotics and are present in large number across Acinetobacter spp. There are six families of efflux pumps that have been shown to be of clinical relevance: the major facilitator superfamily (MFS), small multidrug resistance (SMR) family, ATP-binding cassette (ABC) family, multidrug and toxic compound extrusion (MATE) family, proteobacterial antimicrobial compound efflux (PACE) family, and the resistance-nodulation-division (RND) family. Much work has been done for understanding and characterizing the roles these efflux pumps play in relation to antimicrobial resistance and the physiology of these bacteria. RND efflux pumps, with their expansive substrate profiles, are a major component of Acinetobacter spp. antimicrobial resistance. New discoveries over the last decade have shed light on the complex regulation of these efflux pumps, leading to greater understanding and the potential of slowing the reduced susceptibility seen in these bacterial species.

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)0.000
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 score0.362
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.007
GPT teacher head0.241
Teacher spread0.234 · 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

Citations106
Published2021
Admission routes2
Has abstractyes

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