Evidence map›Paper›PMID 34729595›Full record

ArticleJournal of biomechanical engineering2022

Multiscale Computational Model Predicts Mouse Skin Kinematics Under Tensile Loading.

Nathan J Witt, Alan E Woessner, Kyle P Quinn, Edward A Sander

Abstract read
In one paragraph

Article in Journal of biomechanical engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 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

4 authors.

Nathan J WittRoy J. Carver Department of Biomedical Engineering, College of Engineering, University of Iowa, Iowa City, IA 52242.
Alan E WoessnerDepartment of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701.
Kyle P QuinnDepartment of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701.
Edward A SanderRoy J. Carver Department of Biomedical Engineering, College of Engineering, University of Iowa, 5629 Seamans Center, Iowa City, IA 52242; Department of Orthopedics and Rehabilitation, Carver College of Medicine, University of Iowa, Iowa City, IA 52242.

Funding

In vivo label-free characterization of aged skin to predict delayed wound healingR01AG056560 · NIA · UNIVERSITY OF ARKANSAS AT FAYETTEVILLE · PI QUINN, KYLE PATRICK · 2017 to 2021
$1.7M
NIA NIH HHS R01 AG056560
6 · The paper itself

Abstract

Skin is a complex tissue whose biomechanical properties are generally understood in terms of an incompressible material whose microstructure undergoes affine deformations. A growing number of experiments, however, have demonstrated that skin has a high Poisson's ratio, substantially decreases in volume during uniaxial tensile loading, and demonstrates collagen fiber kinematics that are not affine with local deformation. In order to better understand the mechanical basis for these properties, we constructed multiscale mechanical models (MSM) of mouse skin based on microstructural multiphoton microscopy imaging of the dermal microstructure acquired during mechanical testing. Three models that spanned the cases of highly aligned, moderately aligned, and nearly random fiber networks were examined and compared to the data acquired from uniaxially stretched skin. Our results demonstrate that MSMs consisting of networks of matched fiber organization can predict the biomechanical behavior of mouse skin, including the large decrease in tissue volume and nonaffine fiber kinematics observed under uniaxial tension.

Indexed as

Biomechanical PhenomenaCollagenExtracellular MatrixSkin Physiological PhenomenaAnimalsComputer SimulationMiceStress, MechanicalTensile StrengthCollagenbiomechanicscollagendermisfiber networksmultiphoton microscopynonaffine

Identifiers

PMID34729595
PMCPMC8719047

What OpenQuestion holds

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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.