Evidence map›Paper›PMID 40779238›Full record

ArticleMolecular biomedicine2025

High sensitivity detection of Hepatitis B virus RNA based on 3D-DNA nanomachine and protein nanopore sensing.

Shixin Yan, Chuipeng Kong, Jiazhe Cheng, Zhuoyun Tang, Ke Sun, Shanchuan Chen, Minghan Li, Chengyan Tao, Yue Li, Yanhua Zhao and 3 more

Abstract read
In one paragraph

Article in Molecular biomedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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

13 authors.

Shixin Yan *Department of Laboratory Medicine, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, 610041, China.
Chuipeng Kong *Key Laboratory of Green Chemistry & Technology of Ministry of Education, College of Chemistry, Sichuan University, Chengdu, 610041, China.
Jiazhe Cheng *Department of Laboratory Medicine, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, 610041, China.
Zhuoyun Tang *Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, 610041, China.
Ke SunDepartment of Laboratory Medicine, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, 610041, China.
Shanchuan ChenDepartment of Laboratory Medicine, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, 610041, China.
Minghan LiDepartment of Laboratory Medicine, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, 610041, China.
Chengyan TaoDepartment of Laboratory Medicine, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, 610041, China.
Yue LiDepartment of Laboratory Medicine, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, 610041, China.
Yanhua ZhaoDepartment of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, 610041, China.
Chuanmin TaoDepartment of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, 610041, China. taocm@scu.edu.cn.
Jia GengDepartment of Laboratory Medicine, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, 610041, China. geng.jia@scu.edu.cn.ORCID http://orcid.org/0000-0003-4753-1039
Feng LiKey Laboratory of Green Chemistry & Technology of Ministry of Education, College of Chemistry, Sichuan University, Chengdu, 610041, China. windtalker1205@scu.edu.cn.

Funding

1·3·5 project for disciplines of excellence, West China Hospital, Sichuan University ZYYC23015China Postdoctoral Science Foundation 2024M752201National Natural Science Foundation of China 32301258the Institutional Research Fund from Sichuan University 2021SCUNL105the Key-Area Research and Development Program of Guangdong Province No. 2023B0101200014the National Key R&D Program of China 2023YFB3208303the National Key Research and Development Program of China No. 2022YFB3205600the National Natural Science Foundation of China 22074099the National Natural Science Foundation of China 22204112the Science and Technology Major Project of Tibetan Autonomous Region of China XZ202201ZD0001G
6 · The paper itself

Abstract

Serum Hepatitis B virus (HBV) RNA serves as a non-invasive biomarker for monitoring chronic hepatitis B and guiding treatment decisions. However, current diagnostic tests relying on Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR) require centralized facilities and tedious operational steps, and there is currently no standardized HBV RNA detection method. Herein, we describe the rapid amplification-free detection of HBV RNA in clinical serum samples via a nanopore sensing method. Our method involves the design of a DNA nanomachine capable of translation of each target HBV RNA into a large amount of 7-nt single-strand DNA (ssDNA) as signal reporters that produce blockage features when passing through an alpha-hemolysin (α-HL) nanopore, the target can be quantified by identifying the frequency of this blockage occurrence. We demonstrate that this unique nanopore sensing feature not only distinguishes Signal Report (SR) DNA from interfering nucleic acids in clinical serum samples but also ensures a high assay sensitivity with a limit-of-detection (LOD) at 12.5 fM. The clinical potential of this method was validated through testing serum samples from 26 HBV-infected-patients and 7 healthy-participants. When compared with the RT-qPCR method, it showed only one false result, achieving an accuracy rate of 97.0%. Additionally, testing results for 18 cases during the treatment period demonstrated that our method's conclusions on continued treatment and drug discontinuation were highly consistent with clinical diagnoses, with an accuracy rate of 100%. Therefore, the method developed in this study expands the clinical applications of 3D DNA nanomachine and nanopore sensing technology in clinical detection.

Indexed as

Biosensing TechniquesHepatitis B virusNanoporesRNA, ViralDNA, Single-StrandedHemolysin ProteinsHumansLimit of DetectionDNA, Single-StrandedHemolysin ProteinsRNA, Viral3D-DNA nanomachineClinical detectionHepatitis B virus RNANanopore sensingssDNA

Identifiers

PMID40779238
PMCPMC12334395

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.