Evidence map›Paper›PMID 42814125›Full record

ReviewEuropean biophysics journal : EBJ2026

Electric-field manipulation of giant vesicles: new frontiers in membrane electromechanics.

Rumiana Dimova, Elias Sabri

Abstract readReview
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In one paragraph

Review in European biophysics journal : EBJ, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Rumiana DimovaMax Planck Institute of Colloids and Interfaces, Science Park Golm, 14476, Potsdam, Germany. Rumiana.dimova@mpikg.mpg.de.ORCID http://orcid.org/0000-0002-3872-8502
Elias SabriMax Planck Institute of Colloids and Interfaces, Science Park Golm, 14476, Potsdam, Germany.ORCID http://orcid.org/0000-0002-6451-6458

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Giant unilamellar vesicles (GUVs) are a powerful model system whose response to electric fields constitutes a strategy to directly assess membrane material properties. In the last few years, the field has advanced in both conceptual scope and experimental precision. Electric-field manipulation of GUVs remains a versatile platform for extracting membrane mechanical, electrical, and rheological properties with single-vesicle resolution, while increasingly extending from a diagnostic tool into an actuation mechanism. Here, we summarize classical electrodeformation and electroporation methodologies and review recent developments that push these approaches toward greater biological realism, including compound vesicles as nucleate-cell mimics, resting-membrane-potential- and ion-dependent poration, phase-transition electromechanics, and cytoskeleton-loaded, field-responsive membranes. We also discuss how electric fields are combined with other stimuli, such as light and biochemical cues, and repurposed to drive active, motile vesicle assemblies and to fabricate tailored lipid architectures at high throughput. We further highlight theoretical work on electromechanical coupling, membrane charging dynamics, and vesicle shape landscapes under electric stress. We close by outlining remaining challenges, from reproducibility across preparation protocols to bridging model membranes and living cells, and future opportunities for automated, high-throughput, and multimodal electromechanical studies of biomimetic membranes.

Indexed as

ElectrodeformationElectromechanical couplingElectroporationGiant unilamellar vesiclesMembrane mechanicsPhotoswitchable lipids

Identifiers

What OpenQuestion holds

Textmetadata
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.