Many features of extracellular matrices, e.g., self-healing, adhesiveness, viscoelasticity, and conductivity, are associated with the intricate networks composed of many different covalent and non-covalent chemical bonds. Whereas a reductionism approach would have the limitation to fully recapitulate various biological properties with simple chemical structures, mimicking such sophisticated networks by incorporating many different functional groups in a macromolecular system is synthetically challenging. Herein, we propose a strategy of convergent synthesis of complex polymer networks to produce biomimetic electroconductive liquid metal hydrogels. Four precursors could be individually synthesized in one to two reaction steps and characterized, then assembled to form hydrogel adhesives. The convergent synthesis allows us to combine materials of different natures to generate matrices with high adhesive strength, enhanced electroconductivity, good cytocompatibility in vitro and high biocompatibility in vivo. The reversible networks exhibit self-healing and shear-thinning properties, thus allowing for 3D printing and minimally invasive injection for in vivo experiments.

Conductive hydrogels (CHs) are emerging as a promising and well-utilized platform for 3D cell culture and tissue engineering to incorporate electron signals as biorelevant physical cues. In conventional covalently crosslinked conductive hydrogels, the network dynamics (e.g., stress relaxation, shear shining, and self-healing) required for complex cellular functions and many biomedical utilities (e.g., injection) cannot be easily realized. In contrast, dynamic conductive hydrogels (DCHs) are fabricated by dynamic and reversible crosslinks. By allowing for the breaking and reforming of the reversible linkages, DCHs can provide dynamic environments for cellular functions while maintaining matrix integrity. These dynamic materials can mimic some properties of native tissues, making them well-suited for several biotechnological and medical applications. An overview of the design, synthesis, and engineering of DCHs is presented in this review, focusing on the different dynamic crosslinking mechanisms of DCHs and their biomedical applications.

The split-and-pool method has been widely used to synthesize chemical libraries of a large size for early drug discovery, albeit without the possibility of meaningful quality control. In contrast, a self-assembled DNA-encoded chemical library (DEL) allows us to construct an m x n-member library by mixing an m-member and an n-member pre-purified sub-library. Herein, we report a trio-pharmacophore DEL (T-DEL) of m x l x n members through assembling three pre-purified and validated sub-libraries. The middle sub-library is synthesized using DNA-templated synthesis with different reaction mechanisms and designed as a linkage connecting the fragments displayed on the flanking two sub-libraries. Despite assembling three fragments, the resulting compounds do not exceed the up-to-date standard of molecular weight regarding drug-likeness. We demonstrate the utility of T-DEL in linker optimization for known binding fragments against trypsin and carbonic anhydrase II and by de novo selections against matrix metalloprotease-2 and −9.

Stem cell bioengineering and therapy require different model systems and materials in different stages of development. If a chemically defined biomatrix system can fulfill most tasks, it can minimize the discrepancy among various setups. By screening biomaterials synthesized through a coacervation‐mediated self‐assembling mechanism, a biomatrix system optimal for 2D human mesenchymal stromal cell (hMSC) culture and osteogenesis is identified. Its utility for hMSC bioengineering is further demonstrated in coating porous bioactive glass scaffolds and nanoparticle synthesis for esiRNA delivery to knock down the SOX‐9 gene with high delivery efficiency. The self‐assembled injectable system is further utilized for 3D cell culture, segregated co‐culture of hMSC with human umbilical vein endothelial cells (HUVEC) as an angiogenesis model, and 3D bioprinting. Most interestingly, the coating of bioactive glass with the self‐assembled biomatrix not only supports the proliferation and osteogenesis of hMSC in the 3D scaffold but also induces the amorphous bioactive glass (BG) scaffold surface to form new apatite crystals resembling bone‐shaped plate structures. Thus, the self‐assembled biomatrix system can be utilized in various dimensions, scales, and geometries for many different bioengineering applications.

Information processing functions are essential for organisms to perceive and react to their complex environment, and for humans to analyze and rationalize them. While our brain is extraordinary at processing complex information, winner-take-all, as a type of biased competition is one of the simplest models of lateral inhibition and competition among biological neurons. It has been implemented as DNA-based neural networks, for example, to mimic pattern recognition. However, the utility of DNA-based computation in information processing for real biotechnological applications remains to be demonstrated. In this paper, a biased competition method for nonlinear manipulation and analysis of mixtures of DNA sequences was developed. Unlike conventional biological experiments, selected species were not directly subjected to analysis. Instead, parallel computation among a myriad of different DNA sequences was carried out to reduce the information entropy. The method could be used for various oligonucleotide-encoded libraries, as we have demonstrated its application in decoding and data analysis for selection experiments with DNA-encoded chemical libraries against protein targets.