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Record W3002422142 · doi:10.1039/c9an02612f

Sensitivity of a classic DNAzyme for Pb<sup>2+</sup> modulated by cations, anions and buffers

2020· article· en· W3002422142 on OpenAlexafffund
Wei Ren, Po‐Jung Jimmy Huang, Meilin He, Mingsheng Lyu, Changhai Wang, Shujun Wang, Juewen Liu

Bibliographic record

VenueThe Analyst · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsRegional Municipality of WaterlooUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaNational Key Research and Development Program of ChinaPriority Academic Program Development of Jiangsu Higher Education InstitutionsNorthern Arizona University
KeywordsDeoxyribozymeChemistrySensitivity (control systems)Salt (chemistry)Inorganic chemistrySelectivityAnalytical Chemistry (journal)Physical chemistryChromatographyCatalysisDetection limitOrganic chemistry

Abstract

fetched live from OpenAlex

GR5 is the first reported DNAzyme, which has RNA cleavage activity in the presence of Pb2+. Due to its excellent selectivity, GR5 has been a popular DNAzyme for developing biosensors for Pb2+. The activity of DNAzymes is often affected by pH and salt, which may in turn affect the sensitivity of related sensors. Although pH can be readily controlled by using a buffer, the effect of salt is more complex. To have a systematic understanding, we herein measured the cleavage activity of GR5 in various concentrations of Na+ and Mg2+. Both metals inhibited the DNAzyme with Pb2+, and the inhibition constants were 1.8 mM Mg2+ and 33.4 mM Na+. For anions, F- inhibited GR5 more strongly than Br-, while Cl- was the least inhibiting anion, which was consistent with the solubility of their lead salts. The reaction can work similarly in many Good's buffers, while phosphate buffer should be avoided. Finally, GR5 is an optimal sequence based on the truncation and elongation studies. This study reveals important solution conditions that should be considered when designing and testing related biosensors for metal detection.

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 score0.058
Threshold uncertainty score0.310

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 head0.012
GPT teacher head0.257
Teacher spread0.245 · 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

Citations24
Published2020
Admission routes2
Has abstractyes

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