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Record W2886516542 · doi:10.1002/cbic.201800368

Cellular Studies of an Aminoglycoside Potentiator Reveal a New Inhibitor of Aminoglycoside Resistance

2018· article· en· W2886516542 on OpenAlexafffund
Jinming Guan, Kenward Vong, Kathleen Wee, Johans Fakhoury, Edie Dullaghan, Karine Auclair

Bibliographic record

VenueChemBioChem · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNeurological diseases and metabolism
Canadian institutionsCentre for Drug Research and DevelopmentMcGill University
FundersCanadian Institutes of Health ResearchChina Scholarship Council
KeywordsAminoglycosidePotentiatorProdrugAntibioticsChemistryBacteriaPharmacologyMicrobiologyBiologyBiochemistryGenetics

Abstract

fetched live from OpenAlex

Aminoglycosides are a group of broad-spectrum antibiotics that have been used in the clinic for almost a century. The rapid spread of bacterial genes coding for aminoglycoside-modifying enzymes has, however, dramatically decreased the utility of aminoglycosides. We have previously reported several aminoglycoside potentiators that work by inhibiting aminoglycoside N-6'-acetyltransferase, one of the most common determinants of aminoglycoside resistance. Among these, prodrugs that combine the structure of an aminoglycoside with that of pantothenate into one molecule are especially promising. We report here a series of cellular studies to investigate the activity and mechanism of action of these prodrugs further. Our results reveal a new aminoglycoside resistance inhibitor, as well as the possibility that these prodrugs are transformed into more than one inhibitor in bacteria. We also report that the onset of the potentiators is rapid. Their low cell cytotoxicity, good stability, and potentiation of various aminoglycosides, against both Gram-positive and Gram-negative bacteria, make them interesting compounds for the development of new drugs.

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)0.001
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 score0.002
Threshold uncertainty score0.812

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.055
GPT teacher head0.304
Teacher spread0.249 · 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

Citations8
Published2018
Admission routes2
Has abstractyes

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