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Record W2273592757 · doi:10.1139/cjc-2015-0533

Sensitive detection of bisphenol A based on a ratiometric electrochemical aptasensor

2016· article· en· W2273592757 on OpenAlexvenueno aff
Yunqing Liu, Xia Zhang, Junshuai Yang, Erhu Xiong, Xiaohua Zhang, Jinhua Chen

Bibliographic record

VenueCanadian Journal of Chemistry · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryDetection limitAptamerBisphenol AElectrochemistryMethylene blueElectrodeSelectivityColloidal goldCombinatorial chemistryComplementary DNAGlassy carbonBisphenolChromatographyNanoparticleNanotechnologyOrganic chemistryCyclic voltammetryBiochemistryMolecular biology

Abstract

fetched live from OpenAlex

A new ratiometric electrochemical aptasensor has been developed for highly sensitive and selective detection of bisphenol A (BPA). The double-stranded DNA (dsDNA), consisting of the BPA aptamer (DNA1) and methylene blue (MB)-labeled complementary DNA (cDNA), was immobilized on a gold nanoparticle (AuNP) modified glassy carbon (GC) electrode. In the presence of BPA, the specific BPA–aptamer interaction drove the release of the MB-labeled cDNA from the electrode surface. As a result, the oxidation peak current of MB (IMB) decreased and that of BPA (IBPA) increased. The peak current ratio (IBPA/IMB) of BPA and MB was linear with the concentration of BPA in the range from 1 to 100 pmol/L with a detection limit of 0.6 pmol/L. The detection limit is much lower than that obtained by most of the reported electrochemical methods. On the other hand, the developed aptasensor possesses good selectivity, reproducibility, and stability, and the related sensing structure is very simple, showing promising practical applications in BPA assays.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
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 head0.005
GPT teacher head0.215
Teacher spread0.210 · 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

Citations11
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Chemistry→Same topicAdvanced biosensing and bioanalysis techniques→French-language works237,207→