Evidence map›Paper›PMID 36132017›Full record

ArticleNanoscale advances2020

Neurite guidance and neuro-caging on steps and grooves in 2.5 dimensions.

Cornelius Fendler, Jann Harberts, Lars Rafeldt, Gabriele Loers, Robert Zierold, Robert H Blick

Open access · goldAbstract read
In one paragraph

Article in Nanoscale advances, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 33% 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

4 citing papers in PubMed, 13 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. 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

6 authors at 2 institutions in 4 countries.

Cornelius FendlerCenter for Hybrid Nanostructures (CHyN), Universität Hamburg 22761 Hamburg Germany rzierold@physik.uni-hamburg.de.
Jann HarbertsCenter for Hybrid Nanostructures (CHyN), Universität Hamburg 22761 Hamburg Germany rzierold@physik.uni-hamburg.de.ORCID https://orcid.org/0000-0003-3044-6823
Lars RafeldtCenter for Hybrid Nanostructures (CHyN), Universität Hamburg 22761 Hamburg Germany rzierold@physik.uni-hamburg.de.
Gabriele LoersCenter for Molecular Neurobiology Hamburg (ZMNH), University Medical Center Hamburg-Eppendorf (UKE) Hamburg 20251 Germany.
Robert ZieroldCenter for Hybrid Nanostructures (CHyN), Universität Hamburg 22761 Hamburg Germany rzierold@physik.uni-hamburg.de.ORCID https://orcid.org/0000-0003-0292-0970
Robert H BlickCenter for Hybrid Nanostructures (CHyN), Universität Hamburg 22761 Hamburg Germany rzierold@physik.uni-hamburg.de.
Universität Hamburg · DEUniversity of Wisconsin–Madison · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Directed guidance of neurites is a pre-requisite for tailor-made designs of interfaces between cells and semiconducting components. Grayscale lithography, reactive ion etching, and ultraviolet nanoimprint lithography are potent semiconductor industry-compatible techniques for a cost- and time-effective fabrication of modulated surfaces. In this work, neurite outgrowth of murine cerebellar neurons on 2.5D pathways produced with these methods is studied. Structures of micron-sized steps and grooves serve as cell culture platforms. The effects of contact guidance through topography and chemical guidance through selective poly-d-lysine coating on these platforms are analyzed. As a consequence, the herein presented fabrication approach can be utilized to cultivate and to study low-density neuronal networks in 2.5D configuration with a high degree of order.

Identifiers

PMID36132017
PMCPMC9417336
OpenAlexW3042313054

What OpenQuestion holds

Textmetadata
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.