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Record W2018957937 · doi:10.1039/b504580k

Voltammetric study of the ion-exchange binding of non-electroactive metal cations to DNA-modified surfaces

2005· article· en· W2018957937 on OpenAlexafffund
Li Su, Dipankar Sen, Hua‐Zhong Yu

Bibliographic record

VenueThe Analyst · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsDivalentChemistryElectrochemistryMetalInorganic chemistryRedoxMonolayerMetal ions in aqueous solutionTransition metalIonQualitative inorganic analysisCyclic voltammetryDNABinding constantIon exchangeElectrodeBinding sitePhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

We describe a simple electrochemical protocol for studying the ion-exchange binding of non-electroactive ions, specifically mono- and divalent metal cations of biological relevance (Mg(2+), Ca(2+), and K(+)), to DNA-modified surfaces. After incubation in a dilute solution of multiply charged transition metal complex (5.0 microM [Ru(NH(3))(6)]Cl(3)), gold electrodes modified with thiolate-DNA monolayers respond to the presence of these non-electroactive metal cations by producing significant changes in the cyclic voltammograms (i.e., decrease of the integrated charge and shift of formal potential) of the surface-bound redox complex ([Ru(NH(3))(6)](3+)). The divalent cations (particularly Mg(2+)) can be detected at very low concentrations (<10 microM), while the on-set value for K(+) is substantially higher (50 mM). The equilibrium binding constants for Mg(2+) and Ca(2+) to DNA-modified surfaces were calculated.

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 score0.004
Threshold uncertainty score0.252

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.291
Teacher spread0.277 · 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

Citations12
Published2005
Admission routes2
Has abstractyes

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