Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 159

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Matrix-dependent adhesion of vascular and valvular endothelial cells in microfluidic channels

Young, Edmond W. K., Wheeler, Aaron R., Simmons, Craig A.·2007·Lab on a Chip

Abstract

The interactions between endothelial cells and the underlying extracellular matrix regulate adhesion and cellular responses to microenvironmental stimuli, including flow-induced shear stress. In this study, we investigated the adhesion properties of primary porcine aortic endothelial cells (PAECs) and valve endothelial cells (PAVECs) in a microfluidic network. Taking advantage of the parallel arrangement of the microchannels, we compared adhesion of PAECs and PAVECs to fibronectin and type I collagen, two prominent extracellular matrix proteins, over a broad range of concentrations. Cell spreading was measured morphologically, based on cytoplasmic staining with a vital dye, while adhesion strength was characterized by the number of cells attached after application of shear stresses of 11, 110, and 220 dyn cm(-2). Results showed that PAVECs were more well spread on fibronectin than on type I collagen (P < 0.0001), particularly for coating concentrations of 100, 200, and 500 microg mL(-1). PAVECs also withstood shear significantly better on fibronectin than on collagen for 500 microg mL(-1). PAECs were more well spread on collagen compared to PAVECs (P < 0.0001), but did not have significantly better adhesion strength. These results demonstrate that cell adhesion is both cell-type and matrix dependent. Furthermore, they reveal important phenotypic differences between vascular and valvular endothelium, with implications for endothelial mechanobiology and the design of microdevices and engineered tissues.

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/b712486d

Cites

2 of 2 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 159

Metadata

Authors
Young, E. W. K., Wheeler, A. R., & Simmons, C. A.
Venue
Lab on a Chip
Published
2007
Volume
7
Issue
12
Pages
1759
ISSN
  • 1473-0189 (ISSN-L)
  • 1473-0197
OpenAlex
W2129162784
Cited by
159
References
2
FWCI
4.09
Type
journal article
Language
en
Open access
closed

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.