Evidence map›Paper›PMID 31788785›Full record

ArticleBiotechnology and bioengineering2020

Computational fluid dynamic analysis of bioprinted self-supporting perfused tissue models.

T J Sego, Matthew Prideaux, Jane Sterner, Brian Paul McCarthy, Ping Li, Lynda F Bonewald, Burcin Ekser, Andres Tovar, Lester Jeshua Smith

Abstract read
In one paragraph

Article in Biotechnology and bioengineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Computational approaches in bioprinting processes.Nature reviews bioengineering · 2026
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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

9 authors.

T J SegoDepartment of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana.ORCID 0000-0002-4274-656X
Matthew PrideauxIndiana Center for Musculoskeletal Health, Indiana University, Indianapolis, Indiana.ORCID 0000-0001-9211-9698
Jane SternerRadiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana.ORCID 0000-0002-9024-1355
Brian Paul McCarthyRadiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana.ORCID 0000-0001-5366-7114
Ping LiDivision of Transplant Surgery, Department of Surgery, Indiana University School of Medicine, Indianapolis, Indiana.ORCID 0000-0003-1055-9505
Lynda F BonewaldIndiana Center for Musculoskeletal Health, Indiana University, Indianapolis, Indiana.ORCID 0000-0002-5536-9943
Burcin EkserDivision of Transplant Surgery, Department of Surgery, Indiana University School of Medicine, Indianapolis, Indiana.ORCID 0000-0003-0741-8007
Andres TovarDepartment of Mechanical and Energy Engineering, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana.ORCID 0000-0003-2727-6587
Lester Jeshua SmithRadiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana.ORCID 0000-0003-4950-7569

Funding

Indiana Clinical and Translational Sciences InstituteUL1TR001108 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI DENNE, SCOTT C., SHEKHAR, ANANTHA · 2013 to 2017
$23.3M
Regenova Bio 3D PrinterS10OD023595 · OD · INDIANA UNIVERSITY INDIANAPOLIS · PI SMITH, LESTER J. · 2017 to 2017
$450k
Indiana Center for Musculoskeletal HealthIndiana Clinical and Translational Sciences Institute VFR-457-EkserIndiana University Department of Radiology and Imaging SciencesNCATS NIH HHS UL1 TR001108NCATS NIH HHS UL1TR001108NIH HHS S10 OD023595
6 · The paper itself

Abstract

Natural tissues are incorporated with vasculature, which is further integrated with a cardiovascular system responsible for driving perfusion of nutrient-rich oxygenated blood through the vasculature to support cell metabolism within most cell-dense tissues. Since scaffold-free biofabricated tissues being developed into clinical implants, research models, and pharmaceutical testing platforms should similarly exhibit perfused tissue-like structures, we generated a generalizable biofabrication method resulting in self-supporting perfused (SSuPer) tissue constructs incorporated with perfusible microchannels and integrated with the modular FABRICA perfusion bioreactor. As proof of concept, we perfused an MLO-A5 osteoblast-based SSuPer tissue in the FABRICA. Although our resulting SSuPer tissue replicated vascularization and perfusion observed in situ, supported its own weight, and stained positively for mineral using Von Kossa staining, our in vitro results indicated that computational fluid dynamics (CFD) should be used to drive future construct design and flow application before further tissue biofabrication and perfusion. We built a CFD model of the SSuPer tissue integrated in the FABRICA and analyzed flow characteristics (net force, pressure distribution, shear stress, and oxygen distribution) through five SSuPer tissue microchannel patterns in two flow directions and at increasing flow rates. Important flow parameters include flow direction, fully developed flow, and tissue microchannel diameters matched and aligned with bioreactor flow channels. We observed that the SSuPer tissue platform is capable of providing direct perfusion to tissue constructs and proper culture conditions (oxygenation, with controllable shear and flow rates), indicating that our approach can be used to biofabricate tissue representing primary tissues and that we can model the system in silico.

Indexed as

BioreactorsHydrodynamicsModels, BiologicalAnimalsBioprintingCell LineComputer SimulationEquipment DesignMiceOsteoblastsPerfusion3D-bioprintingbiofabricationbioreactorcomputational fluid dynamicsperfusionscaffold-free

Identifiers

PMID31788785
PMCPMC7015804

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.