MétaCan
Menu
Back to cohort
Record W2184145242 · doi:10.1039/c5cc08879h

Amplified binding-induced homogeneous assay through catalytic cycling of analyte for ultrasensitive protein detection

2015· article· en· W2184145242 on OpenAlexafffund
Junbo Chen, Bin Deng, Peng Wu, Feng Li, Xing‐Fang Li, X. Chris Le, Hongquan Zhang, Xiandeng Hou

Bibliographic record

VenueChemical Communications · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsAlberta Hospital EdmontonUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsDNAChemistryMolecular biologyBiophysicsFluorescenceAnalyteEndonucleaseRecombinant DNABiochemistryBiologyChromatographyGene

Abstract

fetched live from OpenAlex

By using the principle of binding-induced DNA assembly, we have developed a novel homogeneous assay that is able to convert an affinity protein binding event into a predesigned DNA assembly. The assembled DNA sequence can be ligated into an intact DNA strand and hundreds of DNA hairpins can be cleaved by a nicking endonuclease. Each cleavage releases a single-stranded DNA (ssDNA) probe that is initially caged in the DNA hairpin. This released ssDNA probe can then turn on the fluorescence signal by desorbing a fluorescently-labelled complementary DNA probe from graphene oxide through hybridization. We demonstrate that this homogeneous, isothermal, and amplifiable assay can be tailored to detect a number of proteins, including a cancer biomarker, human prostate specific antigen, at picomolar levels in both buffer and human serum samples.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.064
GPT teacher head0.337
Teacher spread0.274 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations23
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueChemical CommunicationsSame topicAdvanced biosensing and bioanalysis techniquesFrench-language works237,207