Evidence map›Paper›PMID 26771746›Full record

ArticlePloS one2016

Geometry Design Optimization of Functionally Graded Scaffolds for Bone Tissue Engineering: A Mechanobiological Approach.

Antonio Boccaccio, Antonio Emmanuele Uva, Michele Fiorentino, Giorgio Mori, Giuseppe Monno

Abstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing 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

37 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Mechanobiological optimization of scaffolds for bone tissue engineering.Biomechanics and modeling in mechanobiology · 2024
    Article
  5. Recent advances in artificial intelligent strategies for tissue engineering and regenerative medicine.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2024
    Review
  6. Article
  7. Review
  8. Review
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Challenges in computational fluid dynamics applications for bone tissue engineering.Proceedings. Mathematical, physical, and engineering sciences · 2022
    Review
  18. Article
  19. Osteo-mucosal engineered construct: In situ adhesion of hard-soft tissues.Materials science & engineering. C, Materials for biological applications · 2021
    Article
  20. Review
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

5 authors.

Antonio BoccaccioDipartimento di Meccanica, Matematica e Management, Politecnico di Bari, 70126, Bari, Italy.
Antonio Emmanuele UvaDipartimento di Meccanica, Matematica e Management, Politecnico di Bari, 70126, Bari, Italy.
Michele FiorentinoDipartimento di Meccanica, Matematica e Management, Politecnico di Bari, 70126, Bari, Italy.
Giorgio MoriDipartimento di Medicina Clinica e Sperimentale, Università di Foggia, 71122, Foggia, Italy.
Giuseppe MonnoDipartimento di Meccanica, Matematica e Management, Politecnico di Bari, 70126, Bari, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Functionally Graded Scaffolds (FGSs) are porous biomaterials where porosity changes in space with a specific gradient. In spite of their wide use in bone tissue engineering, possible models that relate the scaffold gradient to the mechanical and biological requirements for the regeneration of the bony tissue are currently missing. In this study we attempt to bridge the gap by developing a mechanobiology-based optimization algorithm aimed to determine the optimal graded porosity distribution in FGSs. The algorithm combines the parametric finite element model of a FGS, a computational mechano-regulation model and a numerical optimization routine. For assigned boundary and loading conditions, the algorithm builds iteratively different scaffold geometry configurations with different porosity distributions until the best microstructure geometry is reached, i.e. the geometry that allows the amount of bone formation to be maximized. We tested different porosity distribution laws, loading conditions and scaffold Young's modulus values. For each combination of these variables, the explicit equation of the porosity distribution law-i.e the law that describes the pore dimensions in function of the spatial coordinates-was determined that allows the highest amounts of bone to be generated. The results show that the loading conditions affect significantly the optimal porosity distribution. For a pure compression loading, it was found that the pore dimensions are almost constant throughout the entire scaffold and using a FGS allows the formation of amounts of bone slightly larger than those obtainable with a homogeneous porosity scaffold. For a pure shear loading, instead, FGSs allow to significantly increase the bone formation compared to a homogeneous porosity scaffolds. Although experimental data is still necessary to properly relate the mechanical/biological environment to the scaffold microstructure, this model represents an important step towards optimizing geometry of functionally graded scaffolds based on mechanobiological criteria.

Indexed as

Bone and BonesAlgorithmsBiocompatible MaterialsHumansModels, TheoreticalPorosityTissue EngineeringTissue ScaffoldsBiocompatible Materials

Identifiers

PMID26771746
PMCPMC4714836

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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.