MétaCan
Menu
Back to cohort
Record W3150409565 · doi:10.1002/anse.202100006

A Syringe‐Based DNAzyme Sensor for Bacterial Detection

2021· article· en· W3150409565 on OpenAlexaff
Sahar Esmaeili Samani, Erin M. McConnell, Dingran Chang, Meghan Rothenbroker, Carlos D. M. Filipe, Yingfu Li

Bibliographic record

VenueAnalysis & Sensing · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAgaroseDeoxyribozymeChemistryNitrocelluloseChromatographyBiosensorSyringeRNADetection limitEscherichia coliBiochemistry

Abstract

fetched live from OpenAlex

Abstract We present a simple approach for bacterial detection that uses a bead‐bound RNA‐cleaving DNAzyme (RcD) and a syringe. The RcD used in this study, F‐EC1, is fluorescently labelled and can be specifically activated by a protein target released specifically by E. coli . Upon immobilization on agarose beads, the kinetic behaviour of F‐EC1 remains similar to that in solution. The F‐EC1‐agarose system was able to detect as few as 1,000 CFUs of E. coli and retained high recognition specificity. A syringe‐based biosensor was subsequently designed, where F‐EC1‐bearing agarose beads were loaded onto a filter‐containing column. Upon incubation with an E. coli containing reaction mixture, the cleavage fragment released from the beads was filtered onto a nitrocellulose paper to be detected. The sensor was used to achieve the detection of E. coli in water, milk, and apple juice. This method is cost‐effective, simple to use, and can be adapted to other ligand‐responsive RNA‐cleaving DNAzymes.

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 score0.201
Threshold uncertainty score0.739

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.011
GPT teacher head0.274
Teacher spread0.262 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAnalysis & SensingSame topicAdvanced biosensing and bioanalysis techniquesFrench-language works237,207