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Record W2757950305 · doi:10.3390/nano7100296

Poly-L-arginine Coated Silver Nanoprisms and Their Anti-Bacterial Properties

2017· article· en· W2757950305 on OpenAlexaff
Fouzia Tanvir, Atif Yaqub, Shazia Tanvir, William A. Anderson

Bibliographic record

VenueNanomaterials · 2017
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPolyvinylpyrrolidoneZeta potentialSilver nanoparticleNanocompositeDynamic light scatteringAntimicrobialNanoparticleMaterials scienceNuclear chemistryAntibacterial activityChemical engineeringChemistryNanotechnologyPolymer chemistryBacteriaOrganic chemistry

Abstract

fetched live from OpenAlex

The aim of this study was to test the effect of two different morphologies of silver nanoparticles, spheres, and prisms, on their antibacterial properties when coated with poly-L-arginine (poly-Arg) to enhance the interactions with cells. Silver nanoparticle solutions were characterized by UV–visible spectroscopy, transmission electron microscopy, dynamic light scattering, zeta potential, as well as antimicrobial tests. These ultimately showed that a prismatic morphology exhibited stronger antimicrobial effects against Escherichia coli, Pseudomonas aeruginosa and Salmonella enterica. The minimum bactericidal concentration was found to be 0.65 μg/mL in the case of a prismatic AgNP-poly-Arg-PVP (silver nanoparticle-poly-L-arginine-polyvinylpyrrolidone) nanocomposite. The anticancer cell activity of the silver nanoparticles was also studied, where the maximum effect against a HeLa cell line was 80% mortality with a prismatic AgNP-poly-Arg-PVP nanocomposite at a concentration of 11 μg/mL. The antimicrobial activity of these silver nanocomposites demonstrates the potential of such coated silver nanoparticles in the area of nano-medicine.

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 categoriesScholarly communication, Insufficient payload (model declined to judge)
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 score0.013
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.029
GPT teacher head0.246
Teacher spread0.216 · 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

Citations38
Published2017
Admission routes1
Has abstractyes

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