Imaging moiety-directed co-assembly for biodegradation control with synchronous four-modal biotracking

• Published in: Biomaterials 2022-08, Vol.287, p.121665-121665, Article 121665
• Main Authors: Liu, Qingsong, Fu, Ye, Wu, Bin, Tang, Jingyu, Wang, Yaoben, Wu, Yanping, Zhang, Man, Shen, Shen, Shen, Yang, Gao, Caiyun, Ding, Jiandong, Zhu, Liangliang
• Format: Article
• Language: English
• Subjects: Biodegradation; Bioinformation correlation; Biomedical polymer; Directed co-assembly; Multi-mode imaging
• ISSN: 0142-9612; 1878-5905
• DOI: 10.1016/j.biomaterials.2022.121665

The complexity of existing methods for biodegradation control limits the multi-functionality of biomedical materials. It is urgent to develop simple and straightforward strategies to control the biodegradation rate with precise tracking of various parameters in real-time. Here, we show an imaging moiety-directed co-assembly strategy, in which different imaging moieties bearing non-covalent interaction sites are covalently introduced into the poly (D,l-lactic acid) (PDLLA) chain as end groups, followed by alternate non-covalent interactions with polymer chains upon compression molding. This strategy takes advantage of a variety of bonding types (including CH–π, CH–F, etc.) to firmly integrate the PDLLA chains and strongly control the biodegradation rate, making the amorphous prototype degraded much slower than higher-molecular-weight counterparts, and the local inflammatory response is insignificant. On this basis, a synchronous four-modal (X-ray computed tomography + fluorescence + photoacoustics + ultrasound) imaging was achieved on the single entity in vivo, even within a millimeter-scale thick-skin tissue. These imaging signals can precisely correlate the multi parameter variation trend of material mass, volume and molecular weight, signifying that co-assembly can be utilized to develop advanced theranostic systems. We developed an imaging moiety-directed co-assembly strategy to control the biodegradation rate and achieve the synchronization of real-time four-modal imaging in vivo. These imaging signals can precisely correlate the multi-parameter variation trend of material mass, volume and molecular weight, which provided comprehensive biomedical information accessing both qualitatively and quantitatively. [Display omitted]