Evidence map›Paper›PMID 40169377›Full record

ArticleAngewandte Chemie (International ed. in English)2025

Fast and Autonomous Mannosylated Nanomotors for Dynamic Cancer Cell Targeting.

Yuechi Liu, Roberto Terracciano, Jari Scheerstra, Gokhan Yilmaz, Hanglong Wu, Pascal Welzen, Shoupeng Cao, Tania Patino Padial, Loai Abdelmohsen, Jingxin Shao and 3 more

Abstract read
In one paragraph

Article in Angewandte Chemie (International ed. in English), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Fast and Autonomous Mannosylated Nanomotors for Dynamic Cancer Cell Targeting.Angewandte Chemie (International ed. in English) · 2025
    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.

Yuechi LiuBio-Organic Chemistry, Institute of Complex Molecular Systems, Eindhoven University of Technology, Helix, P. O. Box 513, Eindhoven, 5600 MB, the Netherlands.
Roberto TerraccianoDepartment of Chemistry, University of Warwick, Coventry, CV4 7AL, UK.
Jari ScheerstraBio-Organic Chemistry, Institute of Complex Molecular Systems, Eindhoven University of Technology, Helix, P. O. Box 513, Eindhoven, 5600 MB, the Netherlands.
Gokhan YilmazDepartment of Chemistry, University of Warwick, Coventry, CV4 7AL, UK.
Hanglong WuBio-Organic Chemistry, Institute of Complex Molecular Systems, Eindhoven University of Technology, Helix, P. O. Box 513, Eindhoven, 5600 MB, the Netherlands.
Pascal WelzenBio-Organic Chemistry, Institute of Complex Molecular Systems, Eindhoven University of Technology, Helix, P. O. Box 513, Eindhoven, 5600 MB, the Netherlands.
Shoupeng CaoCollege of Polymer Science and Engineering, Sichuan University, Chengdu, 610065, P.R. China.
Tania Patino PadialBio-Organic Chemistry, Institute of Complex Molecular Systems, Eindhoven University of Technology, Helix, P. O. Box 513, Eindhoven, 5600 MB, the Netherlands.
Loai AbdelmohsenBio-Organic Chemistry, Institute of Complex Molecular Systems, Eindhoven University of Technology, Helix, P. O. Box 513, Eindhoven, 5600 MB, the Netherlands.
Jingxin ShaoBio-Organic Chemistry, Institute of Complex Molecular Systems, Eindhoven University of Technology, Helix, P. O. Box 513, Eindhoven, 5600 MB, the Netherlands.
Bingbing SunBio-Organic Chemistry, Institute of Complex Molecular Systems, Eindhoven University of Technology, Helix, P. O. Box 513, Eindhoven, 5600 MB, the Netherlands.
C Remzi BecerDepartment of Chemistry, University of Warwick, Coventry, CV4 7AL, UK.
Jan C M van HestBio-Organic Chemistry, Institute of Complex Molecular Systems, Eindhoven University of Technology, Helix, P. O. Box 513, Eindhoven, 5600 MB, the Netherlands.

Funding

European Union's Horizon 2020Marie Skłodowska-Curie 859416The Dutch Ministry of Education, Culture and Science, Gravitation Program 024.005.020The Dutch Ministry of Education, Culture and Science, Gravitation Program Spinoza premium SPI 72-259
6 · The paper itself

Abstract

An attractive strategy in cancer cell therapy is to employ motile nanoparticles that can actively search for their target. Herein, we introduce mannosylated compartmentalized cross-linked enzyme-driven nanomotors (c-CLEnM), which exhibit specific and efficient targeting of Hep G2 cells through elevated autonomous motion. In this design, we constructed biodegradable bowl-shaped stomatocytes encapsulating the enzymes glucose oxidase (GOx) and catalase (CAT) within their nanocavity. A subsequent enzyme crosslinking reaction was performed to guarantee their stability. Furthermore, the c-CLEnM were surface modified with a mannose-functional glycopolymer, enabling binding with receptors expressed on Hep G2 cells. Interestingly, the targeting ligands on the nanomotors not only improved their specificity toward cancer cells but also enhanced motility. Compared to the non-mannosylated nanomotors, mannosylated c-CLEnM exhibited enhanced motion and higher targeting efficiency to cells in glucose-containing ionic environments. The unexpected acceleration in speed resulted from the surface modification of these nanomotors with a glycopolymer layer, which increased the zeta potential and created a shielding effect that mitigated the influence of the surrounding ions. This nanomotor design highlights the synergistic effect of functional glycopolymer modification on cellular uptake, adding an additional level of control to nanomotors for application in cancer therapy.

Indexed as

Glucose OxidaseMannoseNanoparticlesNeoplasmsCatalaseHep G2 CellsHumansCatalaseGlucose OxidaseMannoseCancer cell targetingEnhanced autonomous motionMannosylated enzymatic nanomotorsStomatocytes

Identifiers

PMID40169377
PMCPMC12124440

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.