Direct 3D Bioprinting of Tough and Antifatigue Cell-Laden Constructs Enabled by a Self-Healing Hydrogel Bioink.

Three-dimensional (3D) extrusion bioprinting has emerged as one of the most promising biofabrication technologies for preparing biomimetic tissue-like constructs. The successful construction of cell-laden constructs majorly relies on the development of proper bioinks with excellent printability and cytocompatibility. Bioinks based on gelatin methacryloyl (GelMA) have been widely explored due to the excellent biocompatibility and biodegradability and the presence of the arginine-glycine-aspartic acid (RGD) sequences for cell adhesion. However, such bioinks usually require low-temperature or ionic cross-linking systems to solidify the extruded hydrogel structures, which results in complex processes and limitations to certain applications. Moreover, many current hydrogel-based bioinks, even after chemical cross-linking, hardly possess the required strength to resist the mechanical loads during the implantation procedure. Herein, we report a self-healing hydrogel bioink based on GelMA and oxidized dextran (OD) for the direct printing of tough and fatigue-resistant cell-laden constructs at room temperature without any template or cross-linking agents. Enabled by dynamic Schiff base chemistry, the mixed GelMA/OD solution showed the characteristics of a dynamic hydrogel with shear-thinning and self-supporting behavior, which allows bridging the 5 mm gap and efficient direct bioprinting of complex constructs with high shape fidelity. After photo-cross-linking, the resulting tissue constructs exhibited excellent low cell damage, high cell viability, and enhanced mechanical strength. Moreover, the GelMA/OD construct could resist up to 95% compressive deformation without any breakage and was able to maintain 80% of the original Young's modulus during long-term loading (50 cycles). It is believed that our GelMA/OD bioink would expand the potential of GelMA-based bioinks in applications such as tissue engineering and pharmaceutical screening.

Transcriptome combined with single cell to explore hypoxia-related biomarkers in osteoarthritis.

Osteoarthritis (OA) is a prevalent degenerative condition among the elderly on a global scale. Research has demonstrated that hypoxia can promote chondrocyte apoptosis and autophagy leading to OA. Hence, it was vital to screen the hypoxia related biomarkers in OA. We introduced transcriptome data to screen out differentially expressed genes (DEGs) in GSE114007 and GSE57218 (OA samples vs control samples). We performed differential expression analysis in key annotated cell to obtain differentially expressed marker genes at the single-cell level (GSE169454). Venn diagram was executed to identify hypoxia related differentially expressed genes (HR-DEGs) associated with OA. Further, feature genes were obtained through the application of least absolute shrinkage and selection operator (LASSO) regression and the Random Forest (RF) algorithm. Receiver operating characteristic (ROC) and expression level analysis were used to identify hypoxia related biomarkers in OA. We further performed immune infiltration and gene set enrichment analysis (GSEA) based on hypoxia related biomarkers. Finally, we analyzed the expression of biomarkers in single-cell level. We identified 2351 DEGs associated with OA. At the single-cell level, 242 differentially expressed marker genes were obtained. 12 HR-DEGs were retained venn diagram. Subsequently, three hypoxia related biomarkers (ADM, DDIT3 and MAFF) were identified. Moreover, we got 15 significantly different immune cells. Finally, we found a lower expression of ADM, DDIT3 and MAFF in OA group compared to the control group in ECs. Overall, we obtained three hypoxia related biomarkers (ADM, DDIT3 and MAFF) associated with OA, which established a theoretical basis for addressing OA.