Evidence map›Paper›PMID 41721566›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Real-Time Digital Micromotor Tracking-Enabled Ultrasensitive Immunoassay.

Jingjing Shi, Zuhua Yu, Hui Tian, Wenjiao Fan, Yuanyuan Sun, Wei Ren, Chenghui Liu

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 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

7 authors.

Jingjing ShiSchool of Chemistry & Chemical Engineering, Shaanxi Normal University, Xi'an, P. R. China.
Zuhua YuSchool of Cyber Science and Engineering, Zhengzhou University, Zhengzhou, P. R. China.
Hui TianSchool of Cyber Science and Engineering, Zhengzhou University, Zhengzhou, P. R. China.
Wenjiao FanSchool of Chemistry & Chemical Engineering, Shaanxi Normal University, Xi'an, P. R. China.
Yuanyuan SunDepartment of Translational Medicine Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, P. R. China.
Wei RenSchool of Chemistry & Chemical Engineering, Shaanxi Normal University, Xi'an, P. R. China.ORCID https://orcid.org/0000-0002-6537-6039
Chenghui LiuSchool of Chemistry & Chemical Engineering, Shaanxi Normal University, Xi'an, P. R. China.

Funding

Fundamental Research Funds for the Central Universities GK202501013Innovation Capability Support Program of Shaanxi Province 2025RS-CXTD-058National Natural Science Foundation of China 22074088National Natural Science Foundation of China 82402751Natural Science Basic Research Program of Shaanxi 2025JC-YBMS-117Natural Science Foundation of Henan Province 242300421474Program for Changjiang Scholars and Innovative Research Team in University IRT_15R43
6 · The paper itself

Abstract

Digital bioassays are emerging as a pivotal technology in disease prevention and diagnostics due to their single-molecule level detection capability. However, elaborate microchamber fabrication, high-end equipment, and skilled manipulation are required to enable the end - point digital signal readout. Herein, we propose a novel concept of artificial intelligence (AI)-facilitated real-time digital micromotor tracking-enabled immunoassay (AI-dMIA), which leverages a self-developed multi-microparticle tracking system to monitor micromotor motion trajectories in a real-time manner for digital protein analysis. In this design, even a single molecule-bridged immunobinding event on the fully-open microparticle's surface can induce obvious motion behaviors and trajectories, forming a positive micromotor that can be accurately tracked and discriminated from the negative ones in real time by a bright-field microscope integrated with the AI algorithm. The AI-dMIA gets rid of the complex process of microchamber fabrication and fluorescence signal yielding/amplification to generate digital counting events. It also exhibits powerful processing capacity to simultaneously track up to thousands of motor trajectories on a large scale, no longer requiring the high-end equipment that is essential to traditional end-point digital bioassays. The AI-dMIA not only demonstrates a robust immunosensing approach but also provides a new alternative for developing next-generation digital micromotor-based platforms.

Indexed as

Artificial IntelligenceBiosensing TechniquesAlgorithmsHumansImmunoassayIntelligent Systemsartificial intelligencedigital biosensingimmunoassaymicromotortrajectory tracking

Identifiers

PMID41721566
PMCPMC13137832

What OpenQuestion holds

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Registered trials

None linked

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.