Evidence map›Paper›PMID 28851984›Full record

ArticleScientific reports2017

Nano-topography Enhances Communication in Neural Cells Networks.

V Onesto, L Cancedda, M L Coluccio, M Nanni, M Pesce, N Malara, M Cesarelli, E Di Fabrizio, F Amato, F Gentile

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
2.7field-weighted citation impact, top 9% 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

29 citing papers in PubMed, 64 citations in OpenAlex.

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  18. Nanotechnology Facilitated Cultured Neuronal Network and Its Applications.International journal of molecular sciences · 2021
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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

10 authors at 3 institutions in 2 countries.

V OnestoDepartment of Experimental and Clinical Medicine, University of Magna Graecia, 88100, Catanzaro, Italy.
L CanceddaIstituto Italiano di Tecnologia, Via Morego 30, 16163, Genova, Italy.ORCID 0000-0003-0566-057X
M L ColuccioDepartment of Experimental and Clinical Medicine, University of Magna Graecia, 88100, Catanzaro, Italy.
M NanniIstituto Italiano di Tecnologia, Via Morego 30, 16163, Genova, Italy.
M PesceIstituto Italiano di Tecnologia, Via Morego 30, 16163, Genova, Italy.
N MalaraDepartment of Experimental and Clinical Medicine, University of Magna Graecia, 88100, Catanzaro, Italy.
M CesarelliDepartment of Electrical Engineering and Information Technology, University of Naples, 80125, Naples, Italy.
E Di FabrizioDepartment of Experimental and Clinical Medicine, University of Magna Graecia, 88100, Catanzaro, Italy.
F AmatoDepartment of Experimental and Clinical Medicine, University of Magna Graecia, 88100, Catanzaro, Italy.ORCID 0000-0002-9053-3139
F GentileDepartment of Electrical Engineering and Information Technology, University of Naples, 80125, Naples, Italy. francesco.gentile2@unina.it.
Magna Graecia University · ITItalian Institute of Technology · ITUniversity of Naples Federico II · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neural cells are the smallest building blocks of the central and peripheral nervous systems. Information in neural networks and cell-substrate interactions have been heretofore studied separately. Understanding whether surface nano-topography can direct nerve cells assembly into computational efficient networks may provide new tools and criteria for tissue engineering and regenerative medicine. In this work, we used information theory approaches and functional multi calcium imaging (fMCI) techniques to examine how information flows in neural networks cultured on surfaces with controlled topography. We found that substrate roughness S

Indexed as

Cell CommunicationNeural Networks, ComputerAnimalsCalciumCells, CulturedFemaleMiceMicroscopy, Atomic ForceMicroscopy, FluorescenceMolecular ImagingNerve NetNeuronsPregnancyCalcium

Identifiers

PMID28851984
PMCPMC5575309
OpenAlexW2748428834

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.