Evidence map›Paper›PMID 28848651›Full record

ArticleJournal of materials chemistry. B2017

A General Strategy for Generating Gradients of Bioactive Proteins on Electrospun Nanofiber Mats by Masking with Bovine Serum Albumin.

Michael L Tanes, Jiajia Xue, Younan Xia

Abstract read
In one paragraph

Article in Journal of materials chemistry. B, 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
–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

13 citing papers in PubMed.

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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.

Michael L TanesThe Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332, United States.
Jiajia XueThe Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332, United States.
Younan XiaThe Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332, United States.

Funding

Nanofiber Conduits with a Honeycomb Structure for Repairing Large Defects in Thick NervesR01EB020050 · NIBIB · GEORGIA INSTITUTE OF TECHNOLOGY · PI BOULIS, NICHOLAS M, XIA, YOUNAN · 2015 to 2018
$1.7M
NIBIB NIH HHS R01 EB020050
6 · The paper itself

Abstract

Electrospun nanofibers are widely used in tissue engineering owing to their capability to mimic the structures and architectures of various types of extracellular matrices. However, it has been difficult to incorporate a biochemical cue into the physical cue provided by the nanofibers. Here we report a simple and versatile method for generating gradients of bioactive proteins on nanofiber mats. We establish that the adsorption of bovine serum albumin (BSA) onto nanofibers is a time- and concentration-dependent process. By linearly increasing the volume of BSA solution introduced into a container, a gradient in BSA is readily generated across the length of a vertically oriented strip of nanofibers. Next, the bare regions uncovered by BSA can be filled with the bioactive protein of interest. In demonstrating the potential application, we examine the outgrowth of neurites from dorsal root ganglion (DRG) isolated from chick embryos and then seeded on aligned polycaprolactone nanofibers covered by nerve growth factor (NGF) with a uniform coverage or in a gradient. In the case of uniform coverage, the neurites extending from DRG show essentially the same length on either side of the DRG cell mass. For the sample with a gradient in NGF, the neurites extending along the gradient (

Indexed as

ChemotaxisElectrospun nanofiberNeural tissue engineeringProtein gradient

Identifiers

PMID28848651
PMCPMC5571829

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Registered trials

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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.