Evidence map›Paper›PMID 25728145›Full record

ArticleJournal of biomechanical engineering2015

Microstructural parameter-based modeling for transport properties of collagen matrices.

Seungman Park, Catherine Whittington, Sherry L Voytik-Harbin, Bumsoo Han

Abstract read
In one paragraph

Article in Journal of biomechanical engineering, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
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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

4 authors.

Seungman Park
Catherine Whittington
Sherry L Voytik-Harbin
Bumsoo Han

Funding

Collagen Cross-links Direct Matrix-Induced Vasculogenesis Via Tunable PathwaysR01HL109602 · NHLBI · PURDUE UNIVERSITY · PI VOYTIK-HARBIN, SHERRY L, YODER, MERVIN C. · 2011 to 2014
$1.5M
NHLBI NIH HHS HL109602NHLBI NIH HHS R01 HL109602
6 · The paper itself

Abstract

Recent advances in modulating collagen building blocks enable the design and control of the microstructure and functional properties of collagen matrices for tissue engineering and regenerative medicine. However, this is typically achieved by iterative experimentations and that process can be substantially shortened by computational predictions. Computational efforts to correlate the microstructure of fibrous and/or nonfibrous scaffolds to their functionality such as mechanical or transport properties have been reported, but the predictability is still significantly limited due to the intrinsic complexity of fibrous/nonfibrous networks. In this study, a new computational method is developed to predict two transport properties, permeability and diffusivity, based on a microstructural parameter, the specific number of interfibril branching points (or branching points). This method consists of the reconstruction of a three-dimensional (3D) fibrous matrix structure based on branching points and the computation of fluid velocity and solute displacement to predict permeability and diffusivity. The computational results are compared with experimental measurements of collagen gels. The computed permeability was slightly lower than the measured experimental values, but diffusivity agreed well. The results are further discussed by comparing them with empirical correlations in the literature for the implication for predictive engineering of collagen matrices for tissue engineering applications.

Indexed as

Models, AnatomicModels, ChemicalTissue ScaffoldsAnimalsCollagen Type IComputer SimulationDiffusionExtracellular MatrixPermeabilityProtein ConformationSwineCollagen Type I

Identifiers

PMID25728145
PMCPMC4403517

What OpenQuestion holds

Textmetadata
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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.