Amorphous poly(DL-lactide-co-RS-beta-malic acid) (PDLLMAc) was synthesized by hydrogenolysis of poly(DL-lactide-co-RS-beta-malolactonate) (PDLLMA), which was obtained from the ring-opening polymerization of DL-lactide (DLLA) and RS-beta-benzyl malolactonate (MA) using stannous octoate as the catalyst. The amount of malolactonate (MA) in the feeding dose was varied from 0 to 8.0 mol %. The copolymers were characterized by 1H NMR, FTIR, GPC, and DSC. The tensile properties and water uptake of the copolymers were measured. The protective benzyl groups in PDLLMA were completely removed in hydrogenolysis to produce PDLLMAc. The molecular weight (M(n)) of the copolymers decreased with increasing MA content. However, with low feed MA content of 0.6 and 1.0%, high molecular weight PDLLMAc with M(n) of 63 and 35 kDa, respectively, were obtained; these copolymers exhibited good tensile yield stress and modulus of 17-23 MPa and 1.1-1.4 GPa, which are comparable to PDLLA homopolymer. The corresponding protected PDLLMA have tensile yield stress/modulus of 2.0-2.4 MPa and 11-42 MPa. The malic acid comonomer in PDLLMAc significantly improves the tensile strength and modulus compared to the protected PDLLMA. Further, the functionalizable PDLLMAc (with 0.6 mol % feed MA) was grafted with bioactive RGD peptide. The culture of primary umbilical artery smooth muscle cells was investigated. Methylthiazoletetrazolium results showed that both the RGD- and COOH-functionalized (0.6 mol %) PDLLMAc copolymers were significantly more biocompatible than the control PDLLA and could potentially be employed as tissue engineering scaffolds.
Generalized signcryption (GSC) can adaptively work as an encryption scheme, a signature scheme or a signcryption scheme with only one algorithm. It is more suitable for the storage constrained setting. In this paper, motivated by Paterson-Schuldt's scheme, based on bilinear pairing, we first proposed an identity based generalized signcryption (IDGSC) scheme in the standard model. To the best of our knowledge, it is the first scheme that is proven secure in the standard model.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.