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Record W2015878973 · doi:10.1021/ac902813y

Exploiting the Interaction of Metal Ions and Peptide Nucleic Acids−DNA Duplexes for the Detection of a Single Nucleotide Mismatch by Electrochemical Impedance Spectroscopy

2010· article· en· W2015878973 on OpenAlexafffund
Congjuan Li, Xiaohong Li, Xinhui Liu, Heinz‐Bernhard Kraatz

Bibliographic record

VenueAnalytical Chemistry · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsChemistryDielectric spectroscopyNucleic acidDNANucleotidePeptideIonPeptide nucleic acidMetal ions in aqueous solutionElectrochemistryMetalCombinatorial chemistryBiochemistryElectrodeOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

The interaction of the metal ions Mg(2+), Zn(2+), Ni(2+), and Co(2+) with DNA-peptide nucleic acid (PNA) films on a gold surface is studied by electrochemical impedance spectroscopy in the presence of [Fe(CN)(6)](3-/4-) as the redox probe. Impedance data were analyzed with the help of a modified Randles' equivalent circuit. Changes in the charge-transfer resistance, R(CT), decreases in the order of Ni(2+) > Co(2+) > Zn(2+) > Mg(2+). We interpret these results in terms of stronger interactions for Ni(2+) with the DNA-PNA film compared to the other metal ions, potentially involving interactions with the nucleobases, presumably with the N7 of purines or the N3 of pyrimidines. On the basis of these observations, Ni(2+) was chosen to probe the detection of a C-T mismatch in 15-mer PNA-DNA films. Using Ni(2+), it is possible to detect a single C-T mismatch. The resulting DeltaR(CT) is larger for the PNA-DNA hybrid compared to that for the identical 15-mer DNA-DNA hybrid.

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 score0.498

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 studies0.0000.001
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 head0.007
GPT teacher head0.244
Teacher spread0.237 · 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

Citations23
Published2010
Admission routes2
Has abstractyes

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