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Record W2131408058 · doi:10.1039/c5sc01870f

Constructing real-time, wash-free, and reiterative sensors for cell surface proteins using binding-induced dynamic DNA assembly

2015· article· en· W2131408058 on OpenAlexafffund
Yanan Tang, Zhi‐Xin Wang, Xiaolong Yang, Junbo Chen, Linan Liu, Weian Zhao, X. Chris Le, Feng Li

Bibliographic record

VenueChemical Science · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsCanadian Sleep SocietyAlberta Hospital EdmontonUniversity of AlbertaBrock University
FundersNatural Sciences and Engineering Research Council of CanadaBrock University
KeywordsDNACellSurface (topology)DNA-binding proteinBiophysicsChemistryComputer scienceBiological systemCell biologyNanotechnologyBiologyMaterials scienceBiochemistryGeneTranscription factorMathematics

Abstract

fetched live from OpenAlex

Cell surface proteins are an important class of biomarkers for fundamental biological research and for disease diagnostics and treatment. In this communication, we report a universal strategy to construct sensors that can achieve rapid imaging of cell surface proteins without any separation by using binding-induced dynamic DNA assembly. As a proof-of-principle, we developed a real-time and wash-free sensor for an important breast cancer biomarker, human epidermal growth factor receptor-2 (HER2). We then demonstrated that this sensor could be used for imaging and sensing HER2 on both fixed and live breast cancer cells. Additionally, we have also incorporated toehold-mediated DNA strand displacement reactions into the HER2 sensor, which allows for reiterating (switching on/off) fluorescence signals for HER2 from breast cancer cells in real-time.

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 score0.136
Threshold uncertainty score0.561

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 head0.020
GPT teacher head0.302
Teacher spread0.282 · 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

Citations64
Published2015
Admission routes2
Has abstractyes

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