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Record W2029663014 · doi:10.1021/ac034318w

Voltammetric Procedure for Examining DNA-Modified Surfaces:  Quantitation, Cationic Binding Activity, and Electron-Transfer Kinetics

2003· article· en· W2029663014 on OpenAlexafffund
Hua‐Zhong Yu, Chuanyun Luo, Carlo G. Sankar, Dipankar Sen

Bibliographic record

VenueAnalytical Chemistry · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryElectron transferCationic polymerizationKineticsOligonucleotideDNARedoxReaction rate constantElectrolyteSupporting electrolyteBinding constantAnalyteElectrodeAnalytical Chemistry (journal)Inorganic chemistryPhysical chemistryChromatographyBinding siteOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

To examine DNA-modified surfaces, we have developed a simple, convenient, and reliable procedure based on the voltammetric response of multiply charged transition metal cations (such as [Ru(NH3)6]3+) bound electrostatically to the DNA probes. At micromolar concentrations of the redox molecules in the electrolyte, the reduction and oxidation waves resulting from the immobilized cations on DNA-modified electrodes are well defined, stable, and reproducible. The surface densities of both single- and double-stranded oligonucleotides were accurately determined by integration of the peak for reduction of [Ru(NH3)6]3+ to [Ru(NH3)6]2+. In addition, the binding constant and electron-transfer rate constant of [Ru(NH3)6]3+ on DNA-modified electrodes were evaluated with the help of classical models. The present research provides not only an applicable and simple protocol for the quantitation of DNA probes on chips but also a versatile and powerful tool for the investigation of the binding activity and electron-transfer kinetics of cationic analytes on DNA-modified surfaces.

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)0.001
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.022
GPT teacher head0.303
Teacher spread0.281 · 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

Citations135
Published2003
Admission routes2
Has abstractyes

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