Evidence map›Paper›PMID 40183490›Full record

ArticleACS nano2025

On-the-Fly Microfluidic Control of Giant Vesicle Compositions Validated by DNA Surface Charge Sensors.

Marcus Fletcher, Yuval Elani

Abstract read
In one paragraph

Article in ACS nano, 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. Review
  3. 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

2 authors.

Marcus FletcherDepartment of Chemical Engineering, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom.ORCID 0000-0003-3036-1168
Yuval ElaniDepartment of Chemical Engineering, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom.ORCID 0000-0002-9603-2490

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The specific lipid composition of cell membrane microenvironments plays a critical role in regulating a range of cellular processes such as integral and peripheral membrane protein function, cell morphology, and membrane potential. However, harnessing similar complex capabilities in artificial membrane mimics remains challenging. In large part, progress has been slow due to a scarcity of techniques for both (i) accurately quantifying composition-dependent properties of artificial cell models at the single-vesicle level and (ii) efficiently exploring large multidimensional composition spaces. Here, we address both challenges by first developing an assay for quantitatively sensing giant unilamellar vesicle (GUV) membrane surface potentials using a fluorescent cholesterol-labeled DNA duplex sensor. We then devised a microfluidic vesicle assembly line enabling the continuous, on-chip production of lipid vesicles with variable compositions. This enabled real-time, on-the-fly adjustment of membrane compositions and biophysical properties as vesicles were being produced, followed by membrane analysis using our assay. Analysis of the association of our DNA fluorescent probe with single vesicles reveals that we may quantify the surface potential of vesicle membranes

Indexed as

DNAMicrofluidic Analytical TechniquesMicrofluidicsUnilamellar LiposomesCholesterolFluorescent DyesSurface PropertiesCholesterolDNAFluorescent DyesUnilamellar LiposomesDNA nanotechnologyGiant Unilamellar Vesicleslipid compositionmembrane surface chargemicrofluidics

Identifiers

PMID40183490
PMCPMC12004935

What OpenQuestion holds

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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.