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Record W2086899725 · doi:10.3390/toxins6082435

Selection and Characterization of a Novel DNA Aptamer for Label-Free Fluorescence Biosensing of Ochratoxin A

2014· article· en· W2086899725 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueToxins · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsAptamerSystematic evolution of ligands by exponential enrichmentBiosensorOchratoxin ANucleic acidOchratoxinDNASYBR Green IComputational biologyDetection limitSELEX Aptamer TechniqueBiologyMycotoxinChemistryMolecular biologyBiotechnologyBiochemistryChromatographyPolymerase chain reactionGeneRNA

Abstract

fetched live from OpenAlex

Nucleic acid aptamers are emerging as useful molecular recognition tools for food safety monitoring. However, practical and technical challenges limit the number and diversity of available aptamer probes that can be incorporated into novel sensing schemes. This work describes the selection of novel DNA aptamers that bind to the important food contaminant ochratoxin A (OTA). Following 15 rounds of in vitro selection, sequences were analyzed for OTA binding. Two of the isolated aptamers demonstrated high affinity binding and selectivity to this mycotoxin compared to similar food adulterants. These sequences, as well as a truncated aptamer (minimal sequence required for binding), were incorporated into a SYBR® Green I fluorescence-based OTA biosensing scheme. This label-free detection platform is capable of rapid, selective, and sensitive OTA quantification with a limit of detection of 9 nM and linear quantification up to 100 nM.

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.

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 score0.026
Threshold uncertainty score0.304

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 head0.259
Teacher spread0.248 · 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