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Record W2806401411 · doi:10.1149/ma2018-01/36/2133

Optimizing Surface Modifications for Quantum Dot Labelled DNA SAMs Using Electrochemistry Coupled Fluorescence Imaging

2018· article· en· W2806401411 on OpenAlexaff
Rochita Sundar, Dan Bizzotto

Bibliographic record

VenueECS Meeting Abstracts · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsQuantum dotFluorophoreFluorescenceElectrodeChemistryBiosensorMonolayerAnalytical Chemistry (journal)ElectrochemistryNanotechnologyMaterials scienceOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Electrochemical biosensors are being developed for detecting specific sequences of nucleic acids using DNA modified gold surfaces[1]. A single crystal gold bead electrode was used to study the arrangement on DNA on different gold surfaces[2]. The gold surface was prepared with a mercaptoundecanol (MUDOL) self-assembled monolayer (SAM). Using a specific desorption potential of -0.850 V/SCE, the MUDOL was reductively desorbed from the Au(111) facet. The defects in the SAM were passivated with a shorter alkylthiol, mercaptohexanol. Thiol modified DNA which is also labeled with a fluorophore was allowed to populate the 111 facet specifically. This was studied using fluorescence microscopy coupled with electrochemical control. A fluorescence image of the gold bead (Figure a) showed that only the 111 facets were modified. The density of the DNA modification was also evaluated using the reorientation of DNA based on the electrode charge density. At positive potentials the DNA was positioned close to the electrode and the fluorescence was quenched. At negative potentials the DNA was repelled and the fluorescence increased. This change in fluorescence is indicative of the density of DNA on the surface. The same approach will be used to assemble DNA modified Quantum Dots (QDs) onto the Au(111) facets. A complementary ssDNA was attached to a glutathione capped quantum dot vis a his-tag peptide. The QD labelled ssDNA was allowed to hybridize with the ssDNA on the gold electrode. Figure (b) is the cartoon depiction of such a layer. Recent research results will be described on the characterization of QD labelled DNA SAMs. The QDs due to their broad absorption and narrow emission spectrum also offer the advantage of building more complicated multiplexed systems in future. (1) Hsieh, K.; Ferguson, B. S.; Eisenstein, M.; Plaxco, K. W.; Soh, H. T. Integrated Electrochemical Microsystems for Genetic Detection of Pathogens at the Point of Care. Acc. Chem. Res. 2015, 48, 911–920. (2) Yu, Z. L.; Casanova-Moreno, J.; Guryanov, I.; Maran, F.; Bizzotto, D. Influence of Surface Structure on Single or Mixed Component Self-Assembled Monolayers via in Situ Spectroelectrochemical Fluorescence Imaging of the Complete Stereographic Triangle on a Single Crystal Au Bead Electrode. J. Am. Chem. Soc 2015, 137, 276–288. Figure 1

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.018
GPT teacher head0.291
Teacher spread0.273 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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