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Record W2803124414 · doi:10.15835/buasvmcn-vm:003017

Antibacterial Activity of Monolayer Graphene Film to Standardised Staphylococcus Aureus Strains

2018· article· en· W2803124414 on OpenAlexfundno aff
G. Gâjâilă, Iuliana Gâjâilă, B. A. Taşbac, Andrei Avram, Bianca Țîncu, Tiberiu Burinaru

Bibliographic record

VenueBulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca Veterinary Medicine · 2018
Typearticle
Languageen
FieldEngineering
TopicGraphene and Nanomaterials Applications
Canadian institutionsnot available
FundersCanada Excellence Research Chairs, Government of Canada
KeywordsGrapheneStaphylococcus aureusNanotechnologyAntibacterial activityBiocompatibilityMaterials scienceMonolayerSubstrate (aquarium)BacteriaMicrobiologyBiologyEcology

Abstract

fetched live from OpenAlex

Due to its unique, unanimously recognized properties and biocompatibility, graphene has wide potential applications in biology, biomedical science, environmental agriculture and biotechnology. The antibacterial effect of the graphene is presented in a large number of publications. Most studies reported in the specific literature were aimed mainly at understanding the interaction between graphene and graphene-based materials with cells and bacteria. Even so, there are conflicting results in some cases and there are also numerous controversies regarding the antibacterial effect of monolayer graphene film on different types of substrate.The study is aimed at testing the antibacterial activity of monolayer graphene film on a copper substrate that was covered with a Staphylococcus aureus culture, Gram-positive bacteria recognized for resilience in external environment. The antibacterial activity of the graphene was evaluated via cell-viability test. It has thus been observed that the bacterial suspension’s phisical contact with the a large-area graphene produces significant disturbances of the microorganism’s vital processes.This study may provide new insights for the better understanding of antibacterial actions of graphene applied on different substrates and opportunities for biomedical applications.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.938
Threshold uncertainty score0.839

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.026
GPT teacher head0.246
Teacher spread0.220 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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Same venueBulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca Veterinary MedicineSame topicGraphene and Nanomaterials ApplicationsFrench-language works237,207