2018
DOI: 10.1177/0885328218808917
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Design and fabrication of conductive nanofibrous scaffolds for neural tissue engineering: Process modeling via response surface methodology

Abstract: Peripheral nervous system in contrary to central one has the potential for regeneration, but its regrowth requires proper environmental conditions and supporting growth factors. The aim of this study is to design and fabricate a conductive polyaniline/graphene nanoparticles incorporated gelatin nanofibrous scaffolds suitable for peripheral nervous system regeneration. The scaffolds were fabricated with electrospinning and the fabrication process was designed with Design-Expert software via response surface met… Show more

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Cited by 22 publications
(15 citation statements)
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“…15 Soleimani et al also observed that the duration of degradation was increased by adding PAG to the gelatin scaffold. 31 As shown in Figure 2D, by increasing the percentage of PAG in the hybrid scaffold, the degradability of samples has been decreased. However, the scaffold degradation rate in the absence of PAG was relatively fast.…”
Section: Biodegradability Of Scaffoldmentioning
confidence: 87%
“…15 Soleimani et al also observed that the duration of degradation was increased by adding PAG to the gelatin scaffold. 31 As shown in Figure 2D, by increasing the percentage of PAG in the hybrid scaffold, the degradability of samples has been decreased. However, the scaffold degradation rate in the absence of PAG was relatively fast.…”
Section: Biodegradability Of Scaffoldmentioning
confidence: 87%
“…This technology offers several advantages which enable the growth of eukaryotic cells on nanofibrous textiles. Surface morphology is an important factor for the adhesion and spreading of cells, offering numerous adhesion points for cells to grow [5,6,7].…”
Section: Introductionmentioning
confidence: 99%
“…The negligible difference between R-squared and predicted R-squared values could be used as proof that this model could predict new results. 58–60 Moreover, the P-values of the model and all involved parameters were less than 0.05, indicating that the selected parameters had a significant impact on the model.…”
Section: Resultsmentioning
confidence: 99%