Evidence map›Paper›PMID 36904415›Full record

ReviewPolymers2023

Electrospun Nanomaterials Based on Cellulose and Its Derivatives for Cell Cultures: Recent Developments and Challenges.

Kristina Peranidze, Tatiana V Safronova, Nataliya R Kildeeva

Full text readReview
In one paragraph

Review in Polymers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
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  10. 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.

Kristina PeranidzeDepartment of Materials Science, Lomonosov Moscow State University, Leninskie Gory 1, Building 73, 119991 Moscow, Russia.ORCID 0000-0002-1042-2392
Tatiana V SafronovaDepartment of Materials Science, Lomonosov Moscow State University, Leninskie Gory 1, Building 73, 119991 Moscow, Russia.ORCID 0000-0002-9799-5029
Nataliya R KildeevaDepartment of Chemistry and Technology of Polymer Materials and Nanocomposites, The Kosygin State University of Russia, Malaya Kaluzhskaya 1, 119071 Moscow, Russia.ORCID 0000-0002-7951-4703

Funding

Russian Foundation for Basic Research 20-03-00550 A
6 · The paper itself

Abstract

The development of electrospun nanofibers based on cellulose and its derivatives is an inalienable task of modern materials science branches related to biomedical engineering. The considerable compatibility with multiple cell lines and capability to form unaligned nanofibrous frameworks help reproduce the properties of natural extracellular matrix and ensure scaffold applications as cell carriers promoting substantial cell adhesion, growth, and proliferation. In this paper, we are focusing on the structural features of cellulose itself and electrospun cellulosic fibers, including fiber diameter, spacing, and alignment responsible for facilitated cell capture. The study emphasizes the role of the most frequently discussed cellulose derivatives (cellulose acetate, carboxymethylcellulose, hydroxypropyl cellulose, etc.) and composites in scaffolding and cell culturing. The key issues of the electrospinning technique in scaffold design and insufficient micromechanics assessment are discussed. Based on recent studies aiming at the fabrication of artificial 2D and 3D nanofiber matrices, the current research provides the applicability assessment of the scaffolds toward osteoblasts (hFOB line), fibroblastic (NIH/3T3, HDF, HFF-1, L929 lines), endothelial (HUVEC line), and several other cell types. Furthermore, a critical aspect of cell adhesion through the adsorption of proteins on the surfaces is touched upon.

Indexed as

cell culturecelluloseelectrospun nanofibersextracellular matrixscaffolds

Identifiers

PMID36904415
PMCPMC10007370

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Registered trials

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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.