Evidence map›Paper›PMID 37101751›Full record

ArticleFrontiers in bioengineering and biotechnology2023

Poro-viscoelastic material parameter identification of brain tissue-mimicking hydrogels.

Manuel P Kainz, Alexander Greiner, Jan Hinrichsen, Dagmar Kolb, Ester Comellas, Paul Steinmann, Silvia Budday, Michele Terzano, Gerhard A Holzapfel

Abstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Tuning porosity of macroporous hydrogels enables rapid rates of stress relaxation and promotes cell expansion and migration.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
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.

Manuel P KainzInstitute of Biomechanics, Graz University of Technology, Graz, Austria.
Alexander GreinerDepartment Mechanical Engineering, Institute of Applied Mechanics, Friedrich Alexander-University Erlangen-Nürnberg, Erlangen, Germany.
Jan HinrichsenDepartment Mechanical Engineering, Institute of Applied Mechanics, Friedrich Alexander-University Erlangen-Nürnberg, Erlangen, Germany.
Dagmar KolbCenter for Medical Research, Gottfried Schatz Research Center, Core Facility Ultrastructure Analysis, Medical University of Graz, Graz, Austria.
Ester ComellasDepartment of Physics, Serra Húnter Fellow, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain.
Paul SteinmannDepartment Mechanical Engineering, Institute of Applied Mechanics, Friedrich Alexander-University Erlangen-Nürnberg, Erlangen, Germany.
Silvia BuddayDepartment Mechanical Engineering, Institute of Applied Mechanics, Friedrich Alexander-University Erlangen-Nürnberg, Erlangen, Germany.
Michele TerzanoInstitute of Biomechanics, Graz University of Technology, Graz, Austria.
Gerhard A HolzapfelInstitute of Biomechanics, Graz University of Technology, Graz, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding and characterizing the mechanical and structural properties of brain tissue is essential for developing and calibrating reliable material models. Based on the Theory of Porous Media, a novel nonlinear poro-viscoelastic computational model was recently proposed to describe the mechanical response of the tissue under different loading conditions. The model contains parameters related to the time-dependent behavior arising from both the viscoelastic relaxation of the solid matrix and its interaction with the fluid phase. This study focuses on the characterization of these parameters through indentation experiments on a tailor-made polyvinyl alcohol-based hydrogel mimicking brain tissue. The material behavior is adjusted to

Indexed as

biomechanical testingbrain tissuehydrogelindentationparameter identificationpolyvinyl alcoholporoelasticityviscoelasticity

Identifiers

PMID37101751
PMCPMC10123293

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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.