Evidence map›Paper›PMID 31581436›Full record

ReviewMaterials (Basel, Switzerland)2019

Layer-By-Layer: The Case for 3D Bioprinting Neurons to Create Patient-Specific Epilepsy Models.

Natasha Antill-O'Brien, Justin Bourke, Cathal D O'Connell

Abstract readReview
In one paragraph

Review in Materials (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. 3D Printing for Neural Repair: Bridging the Gap in Regenerative Medicine.Advanced materials (Deerfield Beach, Fla.) · 2025
    Article
  2. Review
  3. Review
  4. Review
  5. Article
  6. Anticonvulsant Activity ofMolecules (Basel, Switzerland) · 2022
    Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Brain-on-a-Chip: Dream or Reality?Frontiers in neuroscience · 2022
    Article
  12. Article
  13. Article
  14. Article
  15. EngineeringAPL bioengineering · 2021
    Article
  16. Article
  17. Biocompatibility of α-AlJournal of functional biomaterials · 2020
    Article
  18. Review
  19. 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.

Natasha Antill-O'BrienBioFab3D, Aikenhead Centre for Medical Discovery, St Vincent's Hospital Melbourne, Fitzroy, VIC 3065, Australia. nbobrien@student.unimelb.edu.au.
Justin BourkeBioFab3D, Aikenhead Centre for Medical Discovery, St Vincent's Hospital Melbourne, Fitzroy, VIC 3065, Australia. justin.bourke@unimelb.edu.au.
Cathal D O'ConnellBioFab3D, Aikenhead Centre for Medical Discovery, St Vincent's Hospital Melbourne, Fitzroy, VIC 3065, Australia. cathal.oconnell@svha.org.au.ORCID 0000-0002-1690-9505

Funding

St Vincent's Hospital Melbourne Research Endowment Fund 88306
6 · The paper itself

Abstract

The ability to create three-dimensional (3D) models of brain tissue from patient-derived cells, would open new possibilities in studying the neuropathology of disorders such as epilepsy and schizophrenia. While organoid culture has provided impressive examples of patient-specific models, the generation of organised 3D structures remains a challenge. 3D bioprinting is a rapidly developing technology where living cells, encapsulated in suitable bioink matrices, are printed to form 3D structures. 3D bioprinting may provide the capability to organise neuronal populations in 3D, through layer-by-layer deposition, and thereby recapitulate the complexity of neural tissue. However, printing neuron cells raises particular challenges since the biomaterial environment must be of appropriate softness to allow for the neurite extension, properties which are anathema to building self-supporting 3D structures. Here, we review the topic of 3D bioprinting of neurons, including critical discussions of hardware and bio-ink formulation requirements.

Indexed as

3D printing3D scaffoldsbioinkbioprintingbrainneural networkorganoidspatient specific disease modellingthree-dimensional (3D) models

Identifiers

PMID31581436
PMCPMC6804258

What OpenQuestion holds

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LicenceCC BY
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.