MétaCan
Menu
Back to cohort
Record W2322197845 · doi:10.1021/am5007029

DNA Molecular Beacon-Based Plastic Biochip: A Versatile and Sensitive Scanometric Detection Platform

2014· article· en· W2322197845 on OpenAlexaff
Xiaoli Shi, Jing Wen, Yunchao Li, Yue Zheng, Jianjun Zhou, Xiaohong Li, Hua‐Zhong Yu

Bibliographic record

VenueACS Applied Materials & Interfaces · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsBiochipMolecular beaconMaterials scienceStreptavidinNanotechnologyDNABiosensorCombinatorial chemistryOligonucleotideBiotinColloidal goldNanoparticleChemistryBiochemistry

Abstract

fetched live from OpenAlex

In this paper, we report a novel DNA molecular beacon (MB)-based plastic biochip platform for scanometric detection of a range of analytical targets. Hairpin DNA strands, which are dually modified with amino and biotin groups at their two ends are immobilized on a disposable plastic (polycarbonate) substrate as recognition element and gold nanoparticle-assisted silver-staining as signal reading protocol. Initially, the immobilized DNA probes are in their folded forms; upon target binding the hairpin secondary structure of the probe strand is "forced" open (i.e., converted to the unfolded state). Nanogold-streptavidin conjugates can then bind the terminal biotin groups and promote the deposition of rather large silver particles which can be either directly visualized or quantified with a standard flatbed scanner. We demonstrate that with properly designed probe sequences and optimized preparation conditions, a range of molecular targets, such as DNA strands, proteins (thrombin) and heavy metal ions (Hg(2+)), can be detected with high sensitivity and excellent selectivity. The detection can be done in both standard physiological buffers and real world samples. This constitutes a platform technology for performing rapid, sensitive, cost-effective, and point-of-care (POC) chemical analysis and medical diagnosis.

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 score0.005
Threshold uncertainty score0.860

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 head0.005
GPT teacher head0.218
Teacher spread0.213 · 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

Citations31
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueACS Applied Materials & InterfacesSame topicAdvanced biosensing and bioanalysis techniquesFrench-language works237,207