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Record W4406813777 · doi:10.1038/s44259-024-00074-z

Targeting Acinetobacter baumannii resistance-nodulation-division efflux pump transcriptional regulators to combat antimicrobial resistance

2025· review· en· W4406813777 on OpenAlexafffund
Ruwani L. Wimalasekara, Dawn White, Ayush Kumar

Bibliographic record

Venuenpj Antimicrobials and Resistance · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEffluxAcinetobacter baumanniiMicrobiologyAntimicrobialAntibiotic resistanceBiologyMultiple drug resistanceDrug resistanceBacteriaGeneticsAntibioticsPseudomonas aeruginosa

Abstract

fetched live from OpenAlex

Regulatory elements controlling gene expression fine-tune bacterial responses to environmental cues, including antimicrobials, to optimize survival. Acinetobacter baumannii, a pathogen notorious for antimicrobial resistance, relies on efficient efflux systems. Though the role of efflux systems in antibiotic expulsion are well recognized, the regulatory mechanisms controlling their expression remain understudied. This review explores the current understanding of these regulators, aiming to inspire strategies to combat bacterial resistance and improve therapeutic outcomes.

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 categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.294
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.012
GPT teacher head0.274
Teacher spread0.263 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations23
Published2025
Admission routes2
Has abstractyes

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