Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 401

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Microfluidic filtration system to isolate extracellular vesicles from blood

Open access
Davies, Ryan T., Kim, Junho, Jang, Su Chul, Choi, Eun-Jeong, Gho, Yong Song, Park, Jaesung·2012·Lab on a Chip

Abstract

Extracellular vesicles are released by various cell types, particularly tumor cells, and may be potential targets for blood-based cancer diagnosis. However, studies performed on blood-borne vesicles to date have been limited by lack of effective, standardized purification strategies. Using in situ prepared nanoporous membranes, we present a simple strategy employing a microfluidic filtration system to isolate vesicles from whole blood samples. This method can be applied to purify nano-sized particles from blood allowing isolation of intact extracellular vesicles, avoiding the need for laborious and potentially damaging centrifugation steps or overly specific antibody-based affinity purification. Porous polymer monoliths were integrated as membranes into poly(methyl methacrylate) microfluidic chips by benchtop UV photopolymerization through a mask, allowing precise positioning of membrane elements while preserving simplicity of device preparation. Pore size could be manipulated by changing the ratio of porogenic solvent to prepolymer solution, and was tuned to a size proper for extraction of vesicles. Using the membrane as a size exclusion filter, we separated vesicles from cells and large debris by injecting whole blood under pressure through the microfluidic device. To enhance isolation purity, DC electrophoresis was employed as an alternative driving force to propel particles across the filter and increase the separation efficiency of vesicles from proteins. From the whole blood of melanoma-grown mice, we isolated extracellular vesicles and performed RT-PCR to verify their contents of RNA. Melan A mRNA derived from melanoma tumor cells were found enriched in filtered samples, confirming the recovery of vesicles via their cargo. This filtration system can be incorporated into other on-chip processes enabling integrated sample preparation for the downstream analysis of blood-based extracellular vesicles.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1039/c2lc41006k

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 401

Metadata

Authors
Davies, R. T., Kim, J., Jang, S. C., Choi, E.-J., Gho, Y. S., & Park, J.
Venue
Lab on a Chip
Published
2012
Volume
12
Issue
24
Pages
5202
ISSN
  • 1473-0189 (ISSN-L)
  • 1473-0197
OpenAlex
W1978688969
Cited by
401
References
1
FWCI
2.67
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.