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Record W2471545014 · doi:10.1021/acs.analchem.5b02568

Desulfurization Activated Phosphorothioate DNAzyme for the Detection of Thallium

2015· article· en· W2471545014 on OpenAlexafffund
Po‐Jung Jimmy Huang, Mahsa Vazin, Juewen Liu

Bibliographic record

VenueAnalytical Chemistry · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDeoxyribozymeChemistryRNADNACleaveOligonucleotideThalliumDetection limitSubstrate (aquarium)Cleavage (geology)CofactorBiochemistryInorganic chemistryEnzymeChromatographyGene

Abstract

fetched live from OpenAlex

Thallium (Tl) is a highly toxic heavy metal situated between mercury and lead in the periodic table. While its neighbors have been thoroughly studied for DNA-based sensing, little is known about thallium detection. In this work, in vitro selection of RNA-cleaving DNAzymes is carried out using Tl(3+) as the target metal cofactor. Both normal DNA and phosphorothioate (PS)-modified DNA are tested for this purpose. While no Tl(3+)-dependent DNAzymes are obtained, a DNA oligonucleotide containing a single PS-modified RNA nucleotide is found to cleave by ∼7% by Tl(3+) at the RNA position. The remaining 93% are desulfurized. By hybridization of this PS-modified oligonucleotide with the Tm7 DNAzyme, the cleavage yield increases to ∼40% in the presence of Tl(3+) and Er(3+). Tm7 is an Er(3+)-dependent RNA-cleaving DNAzyme. It cleaves only the normal substrate but is completely inactive using the PS-modified substrate. Tl(3+) desulfurizes the PS substrate to the normal substrate to be cleaved by Tm7 and Er(3+). This system is engineered into a catalytic beacon for Tl(3+) with a detection limit of 1.5 nM, which is below its maximal contamination limit defined by the U.S. Environmental Protection Agency (10 nM).

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 score0.167
Threshold uncertainty score0.299

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 head0.020
GPT teacher head0.283
Teacher spread0.263 · 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

Citations36
Published2015
Admission routes2
Has abstractyes

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