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Record W4294628310 · doi:10.3389/frans.2022.994394

An all-deoxyribonucleic acid circuit for detection of human telomerase activity in solution and on paper

2022· article· en· W4294628310 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

VenueFrontiers in Analytical Science · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTelomeraseG-quadruplexDNAGuanineTelomereFluorescenceDuplex (building)Combinatorial chemistryChemistryBiophysicsCancer cellMolecular biologyBiochemistryBiologyCancerNucleotideGeneticsGenePhysicsOptics

Abstract

fetched live from OpenAlex

We report on the design of a simple all-DNA circuit with dual functions of signal amplification and signal reporting and its use for detection of human telomerase activity from cancer cells. The system utilizes a catalytic hairpin assembly (CHA) reaction for amplification, which produces split G-quadruplex outputs that assemble to form complete guanine quadruplex structures as reporting modules. As designed, a linear DNA sequence (the target) functions as a catalyst to drive cyclic programmed assembly of two hairpins, producing a DNA duplex with two guanine-rich sequences that assemble to form a complete Gq structure. The formation of the Gq element allows either fluorescence or colorimetric detection of the target. Examples are provided to demonstrate fluorescence detection of cancer cells’ telomerase activities in solution and the first example of a CHA-modulated colorimetric assay for detecting telomerase activities of cancer cells using a simple paper device.

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)0.001
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 score0.017
Threshold uncertainty score0.271

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 head0.015
GPT teacher head0.299
Teacher spread0.284 · 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