MétaCan
Menu
Back to cohort
Record W3090930135 · doi:10.1093/nar/gkaa800

Evolution of a highly functional circular DNA aptamer in serum

2020· article· en· W3090930135 on OpenAlexafffund
Yu Mao, Jimmy Gu, Dingran Chang, Lei Wang, Lili Yao, Qihui Ma, Zhaofeng Luo, Hao Qu, Yingfu Li, Lei Zheng

Bibliographic record

VenueNucleic Acids Research · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsMcMaster University
FundersNational Key Research and Development Program of ChinaNatural Sciences and Engineering Research Council of CanadaChina Postdoctoral Science Foundation
KeywordsBiologyAptamerDNACircular DNAGeneticsComputational biologyBase sequenceEvolutionary biologyGeneGenome

Abstract

fetched live from OpenAlex

Circular DNA aptamers are powerful candidates for therapeutic applications given their dramatically enhanced biostability. Herein we report the first effort to evolve circular DNA aptamers that bind a human protein directly in serum, a complex biofluid. Targeting human thrombin, this strategy has led to the discovery of a circular aptamer, named CTBA4T-B1, that exhibits very high binding affinity (with a dissociation constant of 19 pM), excellent anticoagulation activity (with the half maximal inhibitory concentration of 90 pM) and high stability (with a half-life of 8 h) in human serum, highlighting the advantage of performing aptamer selection directly in the environment where the application is intended. CTBA4T-B1 is predicted to adopt a unique structural fold with a central two-tiered guanine quadruplex capped by two long stem-loops. This structural arrangement differs from all known thrombin binding linear DNA aptamers, demonstrating the added advantage of evolving aptamers from circular DNA libraries. The method described here permits the derivation of circular DNA aptamers directly in biological fluids and could potentially be adapted to generate other types of aptamers for therapeutic applications.

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 score0.031
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.037
GPT teacher head0.318
Teacher spread0.281 · 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

Citations49
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueNucleic Acids ResearchSame topicAdvanced biosensing and bioanalysis techniquesFrench-language works237,207