Evidence map›Paper›PMID 40442030›Full record

ArticleAnalytical chemistry2025

Programmable PCR-like Nonenzymatic DNA Molecular Circuit for Split-Free Autocatalytic Amplification.

Ting Li, Tat San Lau, Junyou Li, Kaiqi Hu, Man Lung Lee, Pin You Chen, Chi Chiu Wang, Hung-Wing Li

Abstract read
In one paragraph

Article in Analytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Ting LiDepartment of Chemistry, The Chinese University of Hong Kong, Shatin New Territories 999077, Hong Kong SAR, China.
Tat San LauDepartment of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Shatin New Territories 999077, Hong Kong SAR, China.
Junyou LiDepartment of Chemistry, The Chinese University of Hong Kong, Shatin New Territories 999077, Hong Kong SAR, China.
Kaiqi HuDepartment of Chemistry, The Chinese University of Hong Kong, Shatin New Territories 999077, Hong Kong SAR, China.
Man Lung LeeDepartment of Chemistry, The Chinese University of Hong Kong, Shatin New Territories 999077, Hong Kong SAR, China.
Pin You ChenDepartment of Chemistry, The Chinese University of Hong Kong, Shatin New Territories 999077, Hong Kong SAR, China.
Chi Chiu WangDepartment of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Shatin New Territories 999077, Hong Kong SAR, China.
Hung-Wing LiDepartment of Chemistry, The Chinese University of Hong Kong, Shatin New Territories 999077, Hong Kong SAR, China.ORCID 0000-0003-4840-1965

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nonenzymatic autocatalytic DNA circuits, capable of exponential signal amplification, exhibit superior amplification efficiency compared to traditional single or cascade DNA amplification circuits, which offer only linear or quadratic signal amplification. However, autocatalytic DNA circuits are currently limited by complicated splitting designs, low autocatalytic efficiency, the need for additional probes, and a lack of universal design principles. Herein, we developed a PCR-like split-free autocatalytic amplification (SAA) DNA circuit with a simple design but extraordinary autocatalytic efficiency for effective biosensing. The SAA system could consecutively perform multiple cycles of a three-step process upon initiation, target recognition, replicating, and recycling, which is programmed to mimic the basic three reaction steps of PCR and constantly yield numerous new split-free target replicates to expedite the whole reaction, ultimately producing an exponentially amplified signal. The PCR-like sigmoidal kinetics, the ability to accurately execute the programmed instructions, and the high autocatalytic capability of the SAA system are demonstrated, which achieves the same target replication as the PCR but without the need for enzymes and precise control of temperature. The SAA circuit, characterized by exponential signal amplification, simple design, and minimal components, offers a promising approach for developing highly efficient universal DNA circuits. This enables the analysis of low-abundance biomarkers with minimal signal leakage, holding significant potential for biochemical research and clinical diagnosis.

Indexed as

Biosensing TechniquesDNANucleic Acid Amplification TechniquesPolymerase Chain ReactionCatalysisDNA

Identifiers

PMID40442030
PMCPMC12163896

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.