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Record W2016081276 · doi:10.1021/nn8000774

Picomolar Detection of Protease Using Peptide/Single Walled Carbon Nanotube/Gold Nanoparticle-Modified Electrode

2008· article· en· W2016081276 on OpenAlexaff
Khaled A. Mahmoud, Sabahudin Hrapovic, John H. T. Luong

Bibliographic record

VenueACS Nano · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsNational Research Council CanadaBiotechnology Research Institute
Fundersnot available
KeywordsMaterials scienceCarbon nanotubeCyclic voltammetryColloidal goldElectrodeDielectric spectroscopyRaman spectroscopyNanoparticleDetection limitFerroceneNanotechnologyElectrochemistryAnalytical Chemistry (journal)ChemistryOrganic chemistryChromatography

Abstract

fetched live from OpenAlex

Picomolar electrochemical detection of human immunodeficiency virus type-1 protease (HIV-1 PR) using ferrocene (Fc)-pepstatin-modified surfaces has been presented. Gold electrode surface was modified with gold nanoparticles (AuNP) or thiolated single walled carbon nanotubes/gold nanoparticles (SWCNT/AuNP). Thiol-terminated Fc-pepstatin was then self-assembled on such surfaces as confirmed by Raman spectroscopy and scanning electron microscope. The interaction between the Fc-pepstatin-modified substrates and HIV-1 PR was studied by cyclic voltammetry and electrochemical impedance spectroscopy. Both electrode materials showed enhanced electrochemical responses to increasing concentrations of HIV-1 PR with shifting to higher potentials as well as decrease in the overall signal intensity. However, the sensing electrode modified with thiolated SWCNTs/AuNPs showed remarkable detection sensitivity with an estimated detection limit of 0.8 pM.

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)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.017
GPT teacher head0.250
Teacher spread0.233 · 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
GenreMethods

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

Citations122
Published2008
Admission routes1
Has abstractyes

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