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Record W2073387419 · doi:10.1021/ac501070a

Sensing Parts-per-Trillion Cd<sup>2+</sup>, Hg<sup>2+</sup>, and Pb<sup>2+</sup> Collectively and Individually Using Phosphorothioate DNAzymes

2014· article· en· W2073387419 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnalytical Chemistry · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsDeoxyribozymeChemistryLanthanideMetalSelectivityDetection limitCadmiumCleavage (geology)Mercury (programming language)Substrate (aquarium)CatalysisInorganic chemistryCombinatorial chemistryNanotechnologyOrganic chemistryIonChromatography

Abstract

fetched live from OpenAlex

Cadmium, mercury, and lead are collectively banned by many countries and regions in electronic devices due to their extremely high toxicity. To date, no sensing method can detect them as a group and also individually with sufficient sensitivity and selectivity. An RNA-cleaving DNAzyme (Ce13d) was recently reported to be active with trivalent lanthanides, which are hard Lewis acids. In this work, phosphorothioate (PS) modifications were systematically made on Ce13d. A single PS modification at the substrate cleavage site shifts the activity from being dependent on lanthanides to soft thiophilic metals. By incorporating the PS modification to another DNAzyme, a sensor array was prepared to detect each metal. Individual sensors have excellent sensitivity (limit of detection = 4.8 nM Cd(2+), 2.0 nM Hg(2+), and 0.1 nM Pb(2+)). This study provides a new route to obtain metal-specific DNAzymes by atomic replacement and also offers important mechanistic insights into metal binding and DNAzyme catalysis.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.209
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.261
Teacher spread0.249 · 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