Evidence map›Paper›PMID 37071298›Full record

ArticleApplied biochemistry and biotechnology2023

Carboxymethyl Chitosan-Functionalized Polyaniline/Polyacrylonitrile Nano-Fibers for Neural Differentiation of Mesenchymal Stem Cells.

Sahar Arbab Solimani, Shiva Irani, Marjan Mohamadali, Hadi Bakhshi

Abstract read
In one paragraph

Article in Applied biochemistry and biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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.

Sahar Arbab SolimaniDepartment of Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Shiva IraniDepartment of Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran. s.irani@srbiau.ac.ir.
Marjan MohamadaliDepartment of Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Hadi BakhshiDepartment of Life Science and Bioprocesses, Fraunhofer Institute for Applied Polymer Research IAP, Geiselbergstraße 68, 14476, Potsdam-Golm, Germany. hadi.bakhshi@iap.fraunhofer.de.ORCID http://orcid.org/0000-0002-1272-8942

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electroconductive scaffolds based on polyaniline (PANi)/polyacrylonitrile (PAN) were fabricated and surface-functionalized by carboxymethyl chitosan (CMC) as efficient scaffolds for nerve tissue regeneration. The results of scanning electron microscopy (SEM), Fourier-transform infrared (FTIR) spectroscopy, and water contact angle measurement approved the successful fabrication of CMC-functionalized PANi/PAN-based scaffolds. Human adipose-derived mesenchymal stem cells (hADMSCs) were cultured on the scaffolds for 10 d in the presence or absence of β-carotene (βC, 20 µM) as a natural neural differentiation agent. The MTT and SEM results confirmed the attachment and proliferation of hADMSCs on the scaffolds. The expression of MAP2 at the mRNA and protein levels showed the synergic neurogenic induction effect of CMC-functionalization and βC for hADMSCs on the scaffolds. The CMC-functionalized nanofibrous PANi/PAN-based scaffolds are potential candidates for nerve tissue engineering.

Indexed as

ChitosanMesenchymal Stem CellsNanofibersAcrylic ResinsAniline CompoundsCell ProliferationHumansSpectroscopy, Fourier Transform InfraredTissue EngineeringTissue ScaffoldsAcrylic ResinsAniline CompoundsChitosanpolyacrylonitrilepolyanilineCarboxymethyl chitosanNeural differentiationPolyacrylonitrilePolyanilineSurface-functionalization

Identifiers

PMID37071298
PMCPMC10754755

What OpenQuestion holds

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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.