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Record W2834299213 · doi:10.1002/cbic.201800322

An in Vitro–Selected DNAzyme Mutant Highly Specific for Na<sup>+</sup> under Slightly Acidic Conditions

2018· article· en· W2834299213 on OpenAlexafffund
Lingzi Ma, Juewen Liu

Bibliographic record

VenueChemBioChem · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDeoxyribozymeMutantIn vitroChemistryBiochemistryBiophysicsBiologyDNAGene

Abstract

fetched live from OpenAlex

Abstract Sodium is one of the most common metal ions in biology; however, DNA‐based sodium probes have only been reported recently. A Na + ‐specific RNA‐cleaving DNAzyme named NaA43 is active with Na + alone. In this work, we were using Co(NH 3 ) 6 3+ as the intended metal cofactor for in vitro selection, but obtained a mutant of the NaA43 DNAzyme. The mutant was named NaH1, and differs from NaA43 by only two nucleotides. NaA43 has an optimal pH of 7.0, whereas the optimal pH for NaH1 is 6.0. This difference might be due to our selection having been performed at pH 6.0. NaH1 also displays an excellent selectivity for sodium relative to other competing monovalent ions, as well as a fast catalytic rate of (0.11±0.01) min −1 with 50 m m Na + . At low Na + concentrations, the selected DNAzyme exhibited a higher cleavage rate than NaA43 and thus a tighter apparent K d of (12.0±1.6) m m Na + . Furthermore, the NaH1 DNAzyme was engineered into a fluorescent Na + biosensor by attaching a fluorophore/quencher pair to the DNAzyme with a detection limit of 223 μ m Na + . Preliminary work on detection of Na + in serum was demonstrated as well. This study provides a useful mutant that works in a slightly acidic environment, which might be useful for sensing Na + in acidic in vivo environments.

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 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 score0.008
Threshold uncertainty score1.000

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 head0.276
Teacher spread0.264 · 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.

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

Citations20
Published2018
Admission routes2
Has abstractyes

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