Evidence map›Paper›PMID 40102380›Full record

ArticleNature communications2025

Real-time label-free imaging of living crystallization-driven self-assembly.

Yujie Guo, Tianlai Xia, Vivien Walter, Yujie Xie, Julia Y Rho, Laihui Xiao, Rachel K O'Reilly, Mark I Wallace

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
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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.

Yujie Guo *Department of Chemistry, King's College London, London, UK.ORCID http://orcid.org/0009-0003-8411-8400
Tianlai Xia *School of Chemistry, University of Birmingham, Birmingham, UK.ORCID http://orcid.org/0000-0002-4391-0296
Vivien WalterDepartment of Engineering, King's College London, London, UK.ORCID http://orcid.org/0000-0003-3203-9543
Yujie XieSchool of Chemistry, University of Birmingham, Birmingham, UK.ORCID http://orcid.org/0000-0002-6024-7019
Julia Y RhoSchool of Chemistry, University of Birmingham, Birmingham, UK.
Laihui XiaoSchool of Chemistry, University of Birmingham, Birmingham, UK.ORCID http://orcid.org/0000-0002-3412-0954
Rachel K O'ReillySchool of Chemistry, University of Birmingham, Birmingham, UK. r.oreilly@bham.ac.uk.ORCID http://orcid.org/0000-0002-1043-7172
Mark I WallaceDepartment of Chemistry, King's College London, London, UK. mark.wallace@kcl.ac.uk.ORCID http://orcid.org/0000-0002-5692-8313

Funding

RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) BB/R001790/1Wellcome TrustWellcome Trust (Wellcome) 224327/Z/21/Z
6 · The paper itself

Abstract

Living crystallization-driven self-assembly (CDSA) of semicrystalline block copolymers is a powerful method for the bottom-up construction of uniform polymer microstructures with complex hierarchies. Improving our ability to engineer such complex particles demands a better understanding of how to precisely control the self-assembly process. Here, we apply interferometric scattering (iSCAT) microscopy to observe the real-time growth of individual poly(ε-caprolactone)-based fibers and platelets. This label-free method enables us to map the role of key reaction parameters on platelet growth rate, size, and morphology. Furthermore, iSCAT provides a contrast mechanism for studying multi-annulus platelets formed via the sequential addition of different unimers, offering insights into the spatial distribution of polymer compositions within a single platelet.

Indexed as

Blood PlateletsPolyestersCrystallizationHumansInterferometryMicroscopy, InterferencepolycaprolactonePolyesters

Identifiers

PMID40102380
PMCPMC11920093

What OpenQuestion holds

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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.