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Record W3012280487 · doi:10.3390/mi11030294

Simultaneous Determination of Four DNA bases at Graphene Oxide/Multi-Walled Carbon Nanotube Nanocomposite-Modified Electrode

2020· article· en· W3012280487 on OpenAlexafffund
Shuting Wang, Celia Ferrag, Meissam Noroozifar, Kağan Kerman

Bibliographic record

VenueMicromachines · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersUniversity of Toronto ScarboroughNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Research, Innovation and ScienceCanada Research ChairsUniversity of TorontoCanada Foundation for Innovation
KeywordsNanocompositeGrapheneDetection limitCarbon nanotubeMaterials scienceOxideElectrodeNanotubeNuclear chemistryThymineElectrochemistryGuanineAnalytical Chemistry (journal)Chemical engineeringNanotechnologyChemistryChromatographyPhysical chemistryDNA

Abstract

fetched live from OpenAlex

In this study, we developed a modified glassy carbon electrode (GCE) with graphene oxide, multi-walled carbon nanotube hybrid nanocomposite in chitosan (GCE/GO-MWCNT-CHT) to achieve simultaneous detection of four nucleobases (i.e., guanine (G), adenine (A), thymine (T) and cytosine (C)) along with uric acid (UA) as an internal standard. The nanocomposite was characterized using TEM and FT-IR. The linearity ranges were up to 151.0, 78.0, 79.5, 227.5, and 162.5 µM with a detection limit of 0.15, 0.12, 0.44, 4.02, 4.0, and 3.30 µM for UA, G, A, T, and C, respectively. Compared to a bare GCE, the nanocomposite-modified GCE demonstrated a large enhancement (~36.6%) of the electrochemical active surface area. Through chronoamperometric studies, the diffusion coefficients (D), standard catalytic rate constant (Ks), and heterogenous rate constant (Kh) were calculated for the analytes. Moreover, the nanocomposite-modified electrode was used for simultaneous detection in human serum, human saliva, and artificial saliva samples with recovery values ranging from 95% to 105%.

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 score0.010
Threshold uncertainty score0.900

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 head0.011
GPT teacher head0.255
Teacher spread0.244 · 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

Citations19
Published2020
Admission routes2
Has abstractyes

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