Evidence map›Paper›PMID 28529672›Full record

ArticleBiomicrofluidics2017

On-chip density-based purification of liposomes.

Siddharth Deshpande, Anthony Birnie, Cees Dekker

Open access · bronzeAbstract read
In one paragraph

Article in Biomicrofluidics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.7field-weighted citation impact, top 17% of its field
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

13 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
  2. Microfluidic Nanoparticle Separation for Precision Medicine.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
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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

3 authors at 1 institution in 1 country.

Siddharth DeshpandeDepartment of Bionanoscience, Kavli Institute of Nanoscience, Delft University of Technology, Van der Maasweg 9, 2629 HZ Delft, The Netherlands.
Anthony BirnieDepartment of Bionanoscience, Kavli Institute of Nanoscience, Delft University of Technology, Van der Maasweg 9, 2629 HZ Delft, The Netherlands.
Cees DekkerDepartment of Bionanoscience, Kavli Institute of Nanoscience, Delft University of Technology, Van der Maasweg 9, 2629 HZ Delft, The Netherlands.
Delft University of Technology · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to their cell membrane-mimicking properties, liposomes have served as a versatile research tool in science, from membrane biophysics and drug delivery systems to bottom-up synthetic cells. We recently reported a novel microfluidic method, Octanol-assisted Liposome Assembly (OLA), to form cell-sized, monodisperse, unilamellar liposomes with excellent encapsulation efficiency. Although OLA provides crucial advantages over alternative methods, it suffers from the presence of 1-octanol droplets, an inevitable by-product of the production process. These droplets can adversely affect the system regarding liposome stability, channel clogging, and imaging quality. In this paper, we report a density-based technique to separate the liposomes from droplets, integrated on the same chip. We show that this method can yield highly pure (>95%) liposome samples. We also present data showing that a variety of other separation techniques (based on size or relative permittivity) were unsuccessful. Our density-based separation approach favourably decouples the production and separation module, thus allowing freshly prepared liposomes to be used for downstream on-chip experimentation. This simple separation technique will make OLA a more versatile and widely applicable tool.

Identifiers

PMID28529672
PMCPMC5422205
OpenAlexW2614023144

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.