ArticleInternational journal of molecular sciences2023
The Impact of Biomaterial Surface Properties on Engineering Neural Tissue for Spinal Cord Regeneration.
Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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.
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Who cites it
10 citing papers in PubMed, 20 citations in OpenAlex.
- Interferon regulatory factor 4-releasing 3D-printed scaffolds enhance spinal cord repair by modulating macrophage polarization.Neural regeneration research · 2026Article
- Polylactide/Polycaprolactone Nanofiber Scaffold Enhances Primary Cortical Neuron Growth.Polymers · 2026Article
- Effects of Surface Treatments on Innovative Additively Manufactured Scaffolds: Implications for Biocompatibility in Bone Tissue Engineering.Life (Basel, Switzerland) · 2025Article
- CRISPR and Artificial Intelligence in Neuroregeneration: Closed-Loop Strategies for Precision Medicine, Spinal Cord Repair, and Adaptive Neuro-Oncology.International journal of molecular sciences · 2025Review
- Building the framework for bioprinted human heart tissue: recent developments and future prospects.Regenerative medicine · 2025Review
- Biomaterials and Tissue Engineering in Neurosurgery: Current Innovations and Future Directions.Biotech (Basel (Switzerland)) · 2025Review
- Innovative Strategies in 3D Bioprinting for Spinal Cord Injury Repair.International journal of molecular sciences · 2024Review
- Size-Optimized Layered Double Hydroxide Nanoparticles Promote Neural Progenitor Cells Differentiation of Embryonic Stem Cells Through the Regulation of MInternational journal of nanomedicine · 2024Article
- A Bioinspired Astrocyte-Derived Coating Promotes the In Vitro Proliferation of Human Neural Stem Cells While Maintaining Their Stemness.Biomimetics (Basel, Switzerland) · 2023Article
- Nanopatterned bioresorbable elastomeric scaffolds to promote neural, glial, and endothelial differentiation using human embryonic and induced pluripotent stem cells.Journal of tissue engineeringArticle
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 2 countries.
Funding
Abstract
Tissue engineering for spinal cord injury (SCI) remains a complex and challenging task. Biomaterial scaffolds have been suggested as a potential solution for supporting cell survival and differentiation at the injury site. However, different biomaterials display multiple properties that significantly impact neural tissue at a cellular level. Here, we evaluated the behavior of different cell lines seeded on chitosan (CHI), poly (ε-caprolactone) (PCL), and poly (L-lactic acid) (PLLA) scaffolds. We demonstrated that the surface properties of a material play a crucial role in cell morphology and differentiation. While the direct contact of a polymer with the cells did not cause cytotoxicity or inhibit the spread of neural progenitor cells derived from neurospheres (NPCdn), neonatal rat spinal cord cells (SCC) and NPCdn only attached and matured on PCL and PLLA surfaces. Scanning electron microscopy and computational analysis suggested that cells attached to the material's surface emerged into distinct morphological populations. Flow cytometry revealed a higher differentiation of neural progenitor cells derived from human induced pluripotent stem cells (hiPSC-NPC) into glial cells on all biomaterials. Immunofluorescence assays demonstrated that PCL and PLLA guided neuronal differentiation and network development in SCC. Our data emphasize the importance of selecting appropriate biomaterials for tissue engineering in SCI treatment.
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What OpenQuestion holds
Registered trials
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.