Evidence map›Paper›PMID 42567863›Full record

ArticleNature communications2026

Angstrom-fluidic chemical synapses for accurate cancer diagnosis.

Jing Zhao, Qun Ma, Xueqin Luo, Hong Liu, Shijun Xu, Gangping Lian, Yang Liu, Huageng Liang, Lei Zhou, Meihua Lin and 2 more

Abstract read
In one paragraph

Article in Nature communications, 2026. 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. Review
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

12 authors.

Jing ZhaoState Key Laboratory of Geomicrobiology and Environmental Changes, Engineering Research Center of Nano-Geomaterials of Ministry of Education, Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan, PR China.
Qun MaState Key Laboratory of Geomicrobiology and Environmental Changes, Engineering Research Center of Nano-Geomaterials of Ministry of Education, Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan, PR China. maqun@cug.edu.cn.
Xueqin LuoState Key Laboratory of Geomicrobiology and Environmental Changes, Engineering Research Center of Nano-Geomaterials of Ministry of Education, Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan, PR China.
Hong LiuState Key Laboratory of Geomicrobiology and Environmental Changes, Engineering Research Center of Nano-Geomaterials of Ministry of Education, Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan, PR China.
Shijun XuState Key Laboratory of Geomicrobiology and Environmental Changes, Engineering Research Center of Nano-Geomaterials of Ministry of Education, Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan, PR China.
Gangping LianState Key Laboratory of Geomicrobiology and Environmental Changes, Engineering Research Center of Nano-Geomaterials of Ministry of Education, Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan, PR China.
Yang LiuState Key Laboratory of Geomicrobiology and Environmental Changes, Engineering Research Center of Nano-Geomaterials of Ministry of Education, Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan, PR China.
Huageng LiangDepartment of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Lei ZhouState Key Laboratory of Biopharmaceutical Preparation and Delivery, PLA Key Laboratory of Biopharmaceutical Production & Formulation Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing, China. zhoulei17@ipe.ac.cn.
Meihua LinState Key Laboratory of Geomicrobiology and Environmental Changes, Engineering Research Center of Nano-Geomaterials of Ministry of Education, Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan, PR China. linmh@cug.edu.cn.
Wei GuoBiosafety Research Center Yangtze River Delta in Zhangjiagang, Suzhou, China. wguo@iccas.ac.cn.ORCID 0000-0003-3127-2394
Fan XiaState Key Laboratory of Geomicrobiology and Environmental Changes, Engineering Research Center of Nano-Geomaterials of Ministry of Education, Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan, PR China. xiafan@cug.edu.cn.ORCID 0000-0001-7705-4638

Funding

National Natural Science Foundation of China (National Science Foundation of China) 22574148National Natural Science Foundation of China (National Science Foundation of China) U24A20502
6 · The paper itself

Abstract

Artificial chemical synapses, which specifically identify, transmit, and process molecular information, find promising applications in precision medical diagnosis, neural-electronic interface, and in-memory computing. However, to implement biomarker-triggered neuronal excitability modulation with artificial iontronic devices remains a significant challenge. Herein, we demonstrate a capture DNA integrated angstrom-fluidic chemical synapse in which the intramembrane ionic conductance can be switched between excitatory and inhibitory states by specific DNA-target interactions on the outer membrane surface. Experimental results and theoretical calculations unveil that capture of specific biomarker results in a bidirectional space charge polarization, and establishes opposite local concentration gradient at the membrane surface. Driven by this reversible concentration gradient, cation influx or efflux modulate the number density of ionic charge carriers inside the membrane, analogy to the hyperpolarization and depolarization modes of biological chemical synapses. Using a convolutional neural network algorithm to process the ionic conductance enhancement and depletion signals, we develop a diagnostic approach for early prostate cancer with 100% accuracy for both retrospective analysis of 105 clinical specimens, and prospective double-blind trials (n = 10). This work sheds light on artificial chemical synapses based medical diagnosis, and provides a blueprint for neural-like iontronic network for chemical information processing.

Indexed as

Prostatic NeoplasmsSynapsesAlgorithmsConvolutional Neural NetworksDNAHumansDNA

Identifiers

PMID42567863
PMCPMC13451200

What OpenQuestion holds

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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.