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Record W2129210180 · doi:10.1021/jp400565m

Strategies for the Immobilization of Bacteriophages on Gold Surfaces Monitored by Surface Plasmon Resonance and Surface Morphology

2013· article· en· W2129210180 on OpenAlexaff
Nancy Tawil, E. Sacher, Rosemonde Mandeville, Michel Meunier

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2013
Typearticle
Languageen
FieldEngineering
TopicBiosensors and Analytical Detection
Canadian institutionsRegroupement Québécois sur les Matériaux de PointeBioPhage Pharma (Canada)
Fundersnot available
KeywordsSurface plasmon resonanceBiosensorNanotechnologyColloidal goldChemistryPhysisorptionSurface modificationLysisMonolayerBacteriophageMaterials scienceBacteriaScanning electron microscopeBiophysicsNanoparticleEscherichia coliBiologyBiochemistryAdsorptionOrganic chemistry

Abstract

fetched live from OpenAlex

The use of bacteriophages as recognition elements for biosensing techniques has recently provoked much interest. Surface plasmon resonance, scanning electron microscopy, and atomic force microscopy were used for the real-time monitoring of the attachment of methicillin-resistant Staphylococcus aureus (MRSA) bacteriophages to gold using several immobilization methods. The MRSA bacterial capture efficiency of phage-functionalized surfaces was studied. We found that whereas the physisorption of phages to gold surfaces affects their biofunctionality, as expressed by their lysing efficiency of bacteria, phages bound via mixed self-assembled monolayers of l -cysteine and 11-mercaptoundecanoic acid permitted both the recognition and disruption of bacterial membranes. This is due to the formation of uniform islands on the gold surfaces, permitting an oriented positioning of the phages, thus better exposing their recognition proteins.

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 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 score0.047
Threshold uncertainty score0.226

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 head0.006
GPT teacher head0.209
Teacher spread0.203 · 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

Citations42
Published2013
Admission routes1
Has abstractyes

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