Evidence map›Paper›PMID 37849672›Full record

ReviewBME frontiers2023

Advances in In Vitro and In Vivo Bioreactor-Based Bone Generation for Craniofacial Tissue Engineering.

Emma Watson, Antonios G Mikos

Erratum issuedAbstract readReview
In one paragraph

Review in BME frontiers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Review
  2. Review
  3. Deficiency of the mCellular and molecular life sciences : CMLS · 2026
    Article
  4. Boosting ribosomal translationBioactive materials · 2026
    Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Mechanobiology in medicine · 2024
    Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Journal of tissue engineering
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Emma WatsonDepartment of Bioengineering, Rice University, Houston, TX 77030, USA.
Antonios G MikosDepartment of Bioengineering, Rice University, Houston, TX 77030, USA.

Funding

Training and Dissemination CoreP41EB023833 · NIBIB · UNIV OF MARYLAND, COLLEGE PARK · PI FISHER, JOHN P · 2017 to 2021
$6.2M
"A Two-Stage High-Fidelity, Anti-Infective Approach to Craniofacial Repair in Novel Ovine Model"F31DE027586 · NIDCR · RICE UNIVERSITY · PI WATSON, EMMA · 2017 to 2019
$134k
NIBIB NIH HHS P41 EB023833NIDCR NIH HHS F31 DE027586
6 · The paper itself

Abstract

Craniofacial reconstruction requires robust bone of specified geometry for the repair to be both functional and aesthetic. While native bone from elsewhere in the body can be harvested, shaped, and implanted within a defect, using either an in vitro or in vivo bioreactors eliminates donor site morbidity while increasing the customizability of the generated tissue. In vitro bioreactors utilize cells harvested from the patient, a scaffold, and a device to increase mass transfer of nutrients, oxygen, and waste, allowing for generation of larger viable tissues. In vivo bioreactors utilize the patient's own body as a source of cells and of nutrient transfer and involve the implantation of a scaffold with or without growth factors adjacent to vasculature, followed by the eventual transfer of vascularized, mineralized tissue to the defect site. Several different models of in vitro bioreactors exist, and several different implantation sites have been successfully utilized for in vivo tissue generation and defect repair in humans. In this review, we discuss the specifics of each bioreactor strategy, as well as the advantages and disadvantages of each and the future directions for the engineering of bony tissues for craniofacial defect repair.

Identifiers

PMID37849672
PMCPMC10521661

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.