Evidence map›Paper›PMID 36070858›Full record

ReviewChemical reviews2022

Microfluidics for Neuronal Cell and Circuit Engineering.

Rouhollah Habibey, Jesús Eduardo Rojo Arias, Johannes Striebel, Volker Busskamp

Abstract readReview
In one paragraph

Review in Chemical reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Article
  2. Review
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  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Review
  10. Review
  11. Review
  12. Article
  13. 3DMaterials today. Bio · 2025
    Article
  14. Review
  15. Review
  16. Article
  17. Research Progress on Neural Cell Culture Systems.Current neuropharmacology · 2025
    Review
  18. Article
  19. Microfluidic Nanoparticle Separation for Precision Medicine.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  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

4 authors.

Rouhollah HabibeyDepartment of Ophthalmology, Universitäts-Augenklinik Bonn, University of Bonn, Ernst-Abbe-Straße 2, D-53127 Bonn, Germany.
Jesús Eduardo Rojo AriasWellcome─MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge CB2 0AW, United Kingdom.
Johannes StriebelDepartment of Ophthalmology, Universitäts-Augenklinik Bonn, University of Bonn, Ernst-Abbe-Straße 2, D-53127 Bonn, Germany.
Volker BusskampDepartment of Ophthalmology, Universitäts-Augenklinik Bonn, University of Bonn, Ernst-Abbe-Straße 2, D-53127 Bonn, Germany.ORCID 0000-0001-7517-8944

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The widespread adoption of microfluidic devices among the neuroscience and neurobiology communities has enabled addressing a broad range of questions at the molecular, cellular, circuit, and system levels. Here, we review biomedical engineering approaches that harness the power of microfluidics for bottom-up generation of neuronal cell types and for the assembly and analysis of neural circuits. Microfluidics-based approaches are instrumental to generate the knowledge necessary for the derivation of diverse neuronal cell types from human pluripotent stem cells, as they enable the isolation and subsequent examination of individual neurons of interest. Moreover, microfluidic devices allow to engineer neural circuits with specific orientations and directionality by providing control over neuronal cell polarity and permitting the isolation of axons in individual microchannels. Similarly, the use of microfluidic chips enables the construction not only of 2D but also of 3D brain, retinal, and peripheral nervous system model circuits. Such brain-on-a-chip and organoid-on-a-chip technologies are promising platforms for studying these organs as they closely recapitulate some aspects of in vivo biological processes. Microfluidic 3D neuronal models, together with 2D in vitro systems, are widely used in many applications ranging from drug development and toxicology studies to neurological disease modeling and personalized medicine. Altogether, microfluidics provide researchers with powerful systems that complement and partially replace animal models.

Indexed as

MicrofluidicsTissue EngineeringAnimalsBrainHumansLab-On-A-Chip DevicesNeurons

Identifiers

PMID36070858
PMCPMC9523714

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.