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Record W2759436120 · doi:10.1021/jacs.7b07241

In Vitro Selection of Diversely Functionalized Aptamers

2017· article· en· W2759436120 on OpenAlexaff
Dehui Kong, Wayland Yeung, Ryan Hili

Bibliographic record

VenueJournal of the American Chemical Society · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsYork University
FundersNational Cancer Institute
KeywordsAptamerChemistryNucleic acidOligonucleotideThrombinDNACombinatorial chemistryDissociation constantComonomerSystematic evolution of ligands by exponential enrichmentDNA ligaseBiochemistryPolymerizationRNAPolymerMolecular biologyOrganic chemistryPlatelet

Abstract

fetched live from OpenAlex

We describe the application of T4 DNA ligase-catalyzed DNA templated oligonucleotide polymerization toward the evolution of a diversely functionalized nucleic acid aptamer for human α-thrombin. Using a 256-membered ANNNN comonomer library comprising 16 sublibraries modified with different functional groups, a highly functionalized aptamer for thrombin was raised with a dissociation constant of 1.6 nM. The aptamer was found to be selective for thrombin and required the modifications for binding affinity. This study demonstrates the most differentially functionalized nucleic acid aptamer discovered by in vitro selection and should enable the future exploration of functional group dependence during the evolution of nucleic acid polymer activity.

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 score0.006
Threshold uncertainty score0.181

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 head0.009
GPT teacher head0.278
Teacher spread0.269 · 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

Citations84
Published2017
Admission routes1
Has abstractyes

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