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Record W4401687113 · doi:10.1371/journal.pone.0305315

Growth dynamics of Escherichia coli cells on a surface having AgNbO3 antimicrobial particles

2024· article· en· W4401687113 on OpenAlexafffund
Cyrus Talebpour, Fereshteh Fani, Hossein Salimnia, Marc Ouellette, Houshang Alamdari

Bibliographic record

VenuePLoS ONE · 2024
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsEscherichia coliAntimicrobialMicrobiologyChemistryBiologyBiochemistry

Abstract

fetched live from OpenAlex

The morphological dynamics of microbial cell proliferation on an antimicrobial surface at an early growth stage was studied with Escherichia coli on the surface of a gel supplied with AgNbO3 antimicrobial particles. We demonstrated an inhibitory surface concentration, analogous to minimum inhibitory concentration, beyond which the growth of colonies and formation of biofilm are inhibited. In contrast, at lower concentrations of particles, after a lag time the cells circumvent the antimicrobial activity of the particles and grow with a rate similar to the case in the absence of particles. The lag time depends on the surface concentration of the particles and amounts to 2 h at a concentration of ½ minimum inhibitory concentration. The applicability of these findings, in terms of estimating inhibitory surface concentration, was tested in the case of antimicrobial polymethyl methacrylate (PMMA) bone cement.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.028
GPT teacher head0.224
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2024
Admission routes2
Has abstractyes

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