Evidence map›Paper›PMID 28239606›Full record

ArticleFrontiers in bioengineering and biotechnology2017

Influence of Additive Manufactured Scaffold Architecture on the Distribution of Surface Strains and Fluid Flow Shear Stresses and Expected Osteochondral Cell Differentiation.

Wim J Hendrikson, Anthony J Deegan, Ying Yang, Clemens A van Blitterswijk, Nico Verdonschot, Lorenzo Moroni, Jeroen Rouwkema

Abstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Challenges in computational fluid dynamics applications for bone tissue engineering.Proceedings. Mathematical, physical, and engineering sciences · 2022
    Review
  9. Review
  10. Review
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Review
  17. Review
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

7 authors.

Wim J HendriksonDepartment of Tissue Regeneration, MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente , Enschede , Netherlands.
Anthony J DeeganInstitute for Science and Technology in Medicine, School of Medicine, Keele University , Stoke on Trent , UK.
Ying YangInstitute for Science and Technology in Medicine, School of Medicine, Keele University , Stoke on Trent , UK.
Clemens A van BlitterswijkDepartment of Tissue Regeneration, MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, Netherlands; Complex Tissue Regeneration Department, MERLN Institute for Technology Inspired Regenerative Medicine, University of Maastricht, Maastricht, Netherlands.
Nico VerdonschotDepartment of Biomechanical Engineering, MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, Netherlands; Orthopaedic Research Laboratory, Radboud Nijmegen Medical Centre, Nijmegen, Netherlands.
Lorenzo MoroniDepartment of Tissue Regeneration, MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, Netherlands; Complex Tissue Regeneration Department, MERLN Institute for Technology Inspired Regenerative Medicine, University of Maastricht, Maastricht, Netherlands.
Jeroen RouwkemaDepartment of Biomechanical Engineering, MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente , Enschede , Netherlands.

Funding

British Heart Foundation FS/12/48/29719
6 · The paper itself

Abstract

Scaffolds for regenerative medicine applications should instruct cells with the appropriate signals, including biophysical stimuli such as stress and strain, to form the desired tissue. Apart from that, scaffolds, especially for load-bearing applications, should be capable of providing mechanical stability. Since both scaffold strength and stress-strain distributions throughout the scaffold depend on the scaffold's internal architecture, it is important to understand how changes in architecture influence these parameters. In this study, four scaffold designs with different architectures were produced using additive manufacturing. The designs varied in fiber orientation, while fiber diameter, spacing, and layer height remained constant. Based on micro-CT (μCT) scans, finite element models (FEMs) were derived for finite element analysis (FEA) and computational fluid dynamics (CFD). FEA of scaffold compression was validated using μCT scan data of compressed scaffolds. Results of the FEA and CFD showed a significant impact of scaffold architecture on fluid shear stress and mechanical strain distribution. The average fluid shear stress ranged from 3.6 mPa for a 0/90 architecture to 6.8 mPa for a 0/90 offset architecture, and the surface shear strain from 0.0096 for a 0/90 offset architecture to 0.0214 for a 0/90 architecture. This subsequently resulted in variations of the predicted cell differentiation stimulus values on the scaffold surface. Fluid shear stress was mainly influenced by pore shape and size, while mechanical strain distribution depended mainly on the presence or absence of supportive columns in the scaffold architecture. Together, these results corroborate that scaffold architecture can be exploited to design scaffolds with regions that guide specific tissue development under compression and perfusion. In conjunction with optimization of stimulation regimes during bioreactor cultures, scaffold architecture optimization can be used to improve scaffold design for tissue engineering purposes.

Indexed as

additive manufacturingcell differentiationCFDFEAscaffold architecturetissue engineering

Identifiers

PMID28239606
PMCPMC5300985

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.