Evidence map›Paper›PMID 31936240›Full record

ReviewPolymers2020

Piezoelectric Scaffolds as Smart Materials for Neural Tissue Engineering.

Angelika Zaszczynska, Paweł Sajkiewicz, Arkadiusz Gradys

Open access · goldAbstract readReview
In one paragraph

Review in Polymers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed
8.4field-weighted citation impact, top 1% 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

49 citing papers in PubMed, 150 citations in OpenAlex.

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  6. Stimuli-responsive hybrid materials for 4DMaterials today. Bio · 2025
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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

3 authors at 1 institution in 1 country.

Angelika ZaszczynskaInstitute of Fundamental Technological Research, Polish Academy of Sciences, Pawinskiego 5b St., 02-106 Warsaw, Poland.ORCID 0000-0003-3571-1438
Paweł SajkiewiczInstitute of Fundamental Technological Research, Polish Academy of Sciences, Pawinskiego 5b St., 02-106 Warsaw, Poland.ORCID 0000-0003-4092-9853
Arkadiusz GradysInstitute of Fundamental Technological Research, Polish Academy of Sciences, Pawinskiego 5b St., 02-106 Warsaw, Poland.
Institute of Fundamental Technological Research · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Injury to the central or peripheral nervous systems leads to the loss of cognitive and/or sensorimotor capabilities, which still lacks an effective treatment. Tissue engineering in the post-injury brain represents a promising option for cellular replacement and rescue, providing a cell scaffold for either transplanted or resident cells. Tissue engineering relies on scaffolds for supporting cell differentiation and growth with recent emphasis on stimuli responsive scaffolds, sometimes called smart scaffolds. One of the representatives of this material group is piezoelectric scaffolds, being able to generate electrical charges under mechanical stimulation, which creates a real prospect for using such scaffolds in non-invasive therapy of neural tissue. This paper summarizes the recent knowledge on piezoelectric materials used for tissue engineering, especially neural tissue engineering. The most used materials for tissue engineering strategies are reported together with the main achievements, challenges, and future needs for research and actual therapies. This review provides thus a compilation of the most relevant results and strategies and serves as a starting point for novel research pathways in the most relevant and challenging open questions.

Indexed as

neural tissue engineeringpiezoelectric scaffoldspolymerssmart materials

Identifiers

PMID31936240
PMCPMC7022784
OpenAlexW2999470894

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.