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Record W4248474704 · doi:10.1093/nar/gnf093

Tripartite molecular beacons

2002· article· en· W4248474704 on OpenAlexafffund
Razvan Nutiu

Bibliographic record

VenueNucleic Acids Research · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsMolecular beaconFluorophoreNucleic acidDNABiologyFlexibility (engineering)FluorescenceNucleic acid thermodynamicsCombinatorial chemistryCovalent bondChromophoreComputational biologyOligonucleotideBiochemistryBase sequenceChemistryPhysics

Abstract

fetched live from OpenAlex

Molecular beacons (MBs) are hairpin-like fluorescent DNA probes that have single-mismatch detection capability. Although they are extremely useful for many solution-based nucleic acid detections, MBs are expensive probes for applications that require the use of a large number of different DNA probes due to the high cost and tedious procedures associated with probe synthesis and purification. In addition, since both ends of MB probes are covalently modified with chromophores, they do not offer the flexibility for fluorophore change and the capability for surface immobilization through free DNA ends. In this report, we describe an alternative form of MB, denoted tripartite molecular beacon (TMB), that may help overcome these problems. A TMB uses an unmodified oligodeoxyribonucleotide that forms a MB-like structure with two universal single-stranded arms to bring on a universal pair of oligodeoxyribonucleotides modified separately with a fluorophore and a quencher. We found that TMBs are as effective as standard MBs in signaling the presence of matching nucleic acid targets and in precisely discriminating targets that differ by a single nucleotide. TMBs have the necessary flexibility that may make MBs more affordable for various nucleic acid detection 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)0.001
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 score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.044
GPT teacher head0.352
Teacher spread0.309 · 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

Citations29
Published2002
Admission routes2
Has abstractyes

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