Evidence map›Paper›PMID 40936648›Full record

ReviewCyborg and bionic systems (Washington, D.C.)2025

Advanced Imaging Strategies Based on Intelligent Micro/Nanomotors.

Dang Zhang, Liang Lin, Chao Deng, Mohamed Syazwan Osman, Paul E D Soto Rodriguez, Fei Han, Mingyu Li, Lei Wang

Abstract readReview
In one paragraph

Review in Cyborg and bionic systems (Washington, D.C.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Review
  9. Review
  10. Embodied Cross-Domain Intelligence in Biomedical Microrobots: A Review.Cyborg and bionic systems (Washington, D.C.) · 2026
    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

8 authors.

Dang ZhangState Key Laboratory of Advanced Inorganic Fibers and Composites, School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin 150001, China.
Liang LinWenzhou Jiayuan Biotechnology Co., Ltd., Wenzhou 325000, China.
Chao DengCollege of Chemistry and Materials Engineering, Wenzhou University, Wenzhou 325027, China.
Mohamed Syazwan OsmanEMZI-UiTM Nanoparticles Colloids & Interface Industrial Research Laboratory (EMZI NANO-CORE), Faculty of Chemical Engineering, Universiti Teknologi MARA, Cawangan Pulau Pinang, 13500 Permatang Pauh, Pulau Pinang, Malaysia.
Paul E D Soto RodriguezInstituto de Estudios Avanzados IUDEA, Departamento de Física, Universidad de La Laguna C/Astrofísico Francisco Sánchez, s/n.E-38203 Tenerife, Spain.
Fei HanState Key Laboratory of Advanced Inorganic Fibers and Composites, School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin 150001, China.
Mingyu LiSchool of Science, Wuhan University of Technology, Wuhan 430070, China.
Lei WangState Key Laboratory of Advanced Inorganic Fibers and Composites, School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin 150001, China.ORCID https://orcid.org/0000-0002-9522-3623

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biological imaging has revolutionized tissue analysis by revealing morphological and physiological dynamics, yet faces inherent limitations in penetration depth and resolution. Micro/nanomotors (MNMs), with autonomous propulsion and spatiotemporal control, offer transformative solutions to traditional static imaging paradigms. These dynamic contrast agents enhance detection sensitivity in ultrasound, fluorescence, photoacoustic, and magnetic resonance imaging via motion-amplified signal modulation, enabling real-time tracking of subcellular events and microenvironmental changes. While MNMs-enhanced bioimaging has advanced rapidly, systematic analysis of their mechanisms and challenges remains limited. Based on our research experience in this field, this paper first summarizes the signal-enhancing mechanisms of MNMs in single-modal imaging. It then explores multimodal applications through MNMs-probe design and discusses artificial intelligence-driven intelligent MNMs for precision imaging. Finally, challenges and outlook are outlined, aiming to provide a theoretical framework and research roadmap for MNMs-mediated bioimaging technologies.

Identifiers

PMID40936648
PMCPMC12420953

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.