The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Strong Electroactive Biodegradable Shape Memory Polymer Networks Based on Star-Shaped Polylactide and Aniline Trimer for Bone Tissue Engineering
Abstract
Preparation of functional shape memory polymer (SMP) for tissue engineering remains a challenge. Here the synthesis of strong electroactive shape memory polymer (ESMP) networks based on star-shaped polylactide (PLA) and aniline trimer (AT) is reported. Six-armed PLAs with various chain lengths were chemically cross-linked to synthesize SMP. After addition of an electroactive AT segment into the SMP, ESMP was obtained. The polymers were characterized by (1)H NMR, GPC, FT-IR, CV, DSC, DMA, tensile test, and degradation test. The SMP and ESMP exhibited strong mechanical properties (modulus higher than GPa) and excellent shape memory performance: short recovery time (several seconds), high recovery ratio (over 94%), and high fixity ratio (almost 100%). Moreover, cyclic voltammetry test confirmed the electroactivity of the ESMP. The ESMP significantly enhanced the proliferation of C2C12 cells compared to SMP and linear PLA (control). In addition, the ESMP greatly improved the osteogenic differentiation of C2C12 myoblast cells compared to PH10 and PLA in terms of ALP enzyme activity, immunofluorescence staining, and relative gene expression by quantitative real-time polymerase chain reaction (qRT-PCR). These intelligent SMPs and electroactive SMP with strong mechanical properties, tunable degradability, good electroactivity, biocompatibility, and enhanced osteogenic differentiation of C2C12 cells show great potential for bone regeneration.
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Cites
Biodegradable, Elastic Shape-Memory Polymers for Potential Biomedical Applications
Lendlein, A., & Langer, R. (2002) · Science · doi:10.1126/science.1066102 · Cited by 2,146
Tunable polymer multi-shape memory effect
Xie, T. (2010) · Nature · doi:10.1038/nature08863 · Cited by 1,380
Synthetic biodegradable functional polymers for tissue engineering: a brief review
Guo, B., & Ma, P. X. (2014) · Science China Chemistry · doi:10.1007/s11426-014-5086-y · Cited by 592
Self-citationRapidly Self-Expandable Polymeric Stents with a Shape-Memory Property
Chen, M.-C., Tsai, H.-W., Chang, Y., Lai, W.-Y., Mi, F.-L., Liu, C.-T., Wong, H.-S., & Sung, H.-W. (2007) · Biomacromolecules · doi:10.1021/bm7004615 · Cited by 160
Synthesis and characterization of PCL–PLLA polyurethane with shape memory behavior
Peponi, L., Navarro-Baena, I., Sonseca, A., Gimenez, E., Marcos-Fernandez, A., & Kenny, J. M. (2013) · European Polymer Journal · doi:10.1016/j.eurpolymj.2012.11.001 · Cited by 149
Lendlein, A., Zotzmann, J., Feng, Y., Alteheld, A., & Kelch, S. (2009) · Biomacromolecules · doi:10.1021/bm900038e · Cited by 115
Design of multistimuli-responsive shape-memory polymer materials by reactive extrusion
Pilate, F., Mincheva, R., De Winter, J., Gerbaux, P., Wu, L., Todd, R., Raquez, J.-M., & Dubois, P. (2014) · Chemistry of Materials · doi:10.1021/cm5020543 · Cited by 78
Amirian, M., Nabipour Chakoli, A., Sui, J., & Cai, W. (2012) · Journal of Polymer Research · doi:10.1007/s10965-011-9777-1 · Cited by 32
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Conducting Polymers for Tissue Engineering
Guo, B., & Ma, P. X. (2018) · Biomacromolecules · doi:10.1021/acs.biomac.8b00276 · Cited by 835
Self-citationFunctional and Biomimetic Materials for Engineering of the Three-Dimensional Cell Microenvironment
Huang, G., Li, F., Zhao, X., Ma, Y., Li, Y., Lin, M., Jin, G., Lu, T. J., Genin, G. M., & Xu, F. (2017) · Chemical Reviews · doi:10.1021/acs.chemrev.7b00094 · Cited by 825
Dong, R., Zhao, X., Guo, B., & Ma, P. X. (2016) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.6b04911 · Cited by 538
Self-citationDeng, Z., Hu, T., Lei, Q., He, J., Ma, P. X., & Guo, B. (2019) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.8b20178 · Cited by 486
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Metadata
- Authors
- Xie, M., Wang, L., Ge, J., Guo, B., & Ma, P. X.
- Venue
- ACS Applied Materials & Interfaces
- Publisher
- American Chemical Society (ACS)
- Published
- 2015-03-17
- Volume
- 7
- Issue
- 12
- Pages
- 6772-6781
- ISSN
- 1944-8244 (ISSN-L)
- 1944-8252
- OpenAlex
- W2330316978
- Cited by
- 201
- References
- 8
- FWCI
- 16.50
- Type
- journal article
- Language
- en
- Open access
- closed
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