Evidence map›Paper›PMID 27330228›Full record

ArticleZeitschrift fuer angewandte mathematik und physik2016

Finite element modeling of finite deformable, biphasic biological tissues with transversely isotropic statistically distributed fibers: toward a practical solution.

John Z Wu, Walter Herzog, Salvatore Federico

Abstract read
In one paragraph

Article in Zeitschrift fuer angewandte mathematik und physik, 2016. 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
0.7field-weighted citation impact, top 29% of its field
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, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. AnFrontiers in bioengineering and biotechnology · 2021
    Article
  4. Review
  5. Finite element simulations of the head-brain responses to the top impacts of a construction helmet: Effects of the neck and body mass.Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine · 2017
    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

3 authors at 2 institutions in 2 countries.

John Z WuNational Institute for Occupational Safety and Health Morgantown, WV, USA jwu@cdc.gov.
Walter HerzogHuman Performance Laboratory, Faculty of Kinesiology The University of Calgary Calgary, AB, Canada.
Salvatore FedericoDepartment of Mechanical and Manufacturing Engineering The University of Calgary Calgary, AB, Canada salvatore.federico@ucalgary.ca.
University of Calgary · CANational Institute for Occupational Safety and Health · US

Funding

Intramural CDC HHS CC999999
6 · The paper itself

Abstract

The distribution of collagen fibers across articular cartilage layers is statistical in nature. Based on the concepts proposed in previous models, we developed a methodology to include the statistically distributed fibers across the cartilage thickness in the commercial FE software COMSOL which avoids extensive routine programming. The model includes many properties that are observed in real cartilage: finite hyperelastic deformation, depth-dependent collagen fiber concentration, depth- and deformation-dependent permeability, and statistically distributed collagen fiber orientation distribution across the cartilage thickness. Numerical tests were performed using confined and unconfined compressions. The model predictions on the depth-dependent strain distributions across the cartilage layer are consistent with the experimental data in the literature.

Indexed as

Articular cartilageBiphasic modelCollagen fibersFinite deformationFinite element model

Identifiers

PMID27330228
PMCPMC4908457
OpenAlexW2327065359

What OpenQuestion holds

Textmetadata
LicenceTDM
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.