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Record W4401714784 · doi:10.1128/spectrum.01047-24

Exploring antimicrobial interactions between metal ions and quaternary ammonium compounds toward synergistic metallo-antimicrobial formulations

2024· article· en· W4401714784 on OpenAlexafffund
Andrii Lekhan, Raymond J. Turner

Bibliographic record

VenueMicrobiology Spectrum · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPhenothiazines and Benzothiazines Synthesis and Activities
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAntimicrobialAmmoniumBromideBiofilmChemistryBenzalkonium chlorideAmmonium bromideAntibioticsMetalMetal ions in aqueous solutionAntibiotic resistanceAmmonium chlorideCombinatorial chemistryMicrobiologyChromatographyBacteriaBiologyBiochemistryOrganic chemistryPulmonary surfactant

Abstract

fetched live from OpenAlex

ABSTRACT Multi-target antimicrobial agents are considered a viable alternative to target-specific antibiotics, resistance to which emerged as a global threat. Used centuries before the discovery of conventional antibiotics, metal(loid)-based antimicrobials (MBAs), which target multiple biomolecules within the bacterial cell, are regaining research interest. However, there is a significant limiting factor—the balance between cost and efficiency. In this article, we utilize a checkerboard assay approach to explore antimicrobial combinations of MBAs with commonly used quaternary ammonium compound (QAC) antiseptics in order to discover novel combinations with more pronounced antimicrobial properties than would be expected from a simple sum of antimicrobial effects of initial components. This phenomenon, called synergy, was herein demonstrated for several mixtures of Al3+with cetyltrimethylammonium bromide (CTAB) and TeO32- with benzalkonium chloride (BAC) and didecyldimethylammonium bromide (DDAB) against planktonic and biofilm growth of Pseudomonas aeruginosa ATCC27853. Biofilm growth of Escherichia coli ATCC25922 was synergistically inhibited by the Cu2 +and benzalkonium chloride (BAC) mixture. Multiple additive mixtures were identified for both organisms. The current study observed unexpected species and growth state specificities for the synergistic combinations. The benefit of synergistic mixtures will be captured in economy/efficiency optimization for antimicrobial applications in which MBAs and QACs are presently used. IMPORTANCE We are entering the antimicrobial resistance era (AMR), where resistance to antibiotics is becoming more and more prevalent. In order to address this issue, various approaches are being explored. In this article, we explore for synergy between two very different antimicrobials, the antiseptic class of quaternary ammonium compounds and antimicrobial metals. These two antimicrobials have very different actions. Considering a OneHealth approach to the problem, finding synergistic mixtures allows for greater efficacy at lower concentrations, which would also address antimicrobial pollution issues.

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 categoriesMeta-epidemiology (narrow)
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 score0.078
Threshold uncertainty score1.000

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 head0.054
GPT teacher head0.266
Teacher spread0.211 · 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.

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

Citations6
Published2024
Admission routes2
Has abstractyes

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