A well plate-based GelMA photo-crosslinking system with tunable hydrogel mechanical properties to regulate the PTH-mediated osteogenic fate.

Versatile and efficient regulation of the mechanical properties of the extracellular matrix is crucial not only for understanding the dynamic changes in biological systems, but also for obtaining precise and effective cellular responses in drug testing. In this study, we developed a well plate-based hydrogel photo-crosslinking system to effectively control the mechanical properties of hydrogels and perform high-throughput assays. We improved cell biocompatibility by using gelatin methacryloyl (GelMA) with a visible light photo-crosslinking method. Multiple cell-laden GelMA hydrogels were simultaneously and uniformly created using multi-arrayed 520 nm light-emitting diodes in a well plate format. The elastic modulus of the hydrogels can be widely adjusted (0.5-30 kPa) using a photo-crosslinking system capable of independently controlling the light intensity or exposure time for multiple samples. We demonstrate the feasibility of our system by observing enhanced bone differentiation of human mesenchymal stem cells (hMSCs) cultured on stiffer hydrogels. Additionally, we observed that the osteogenic fate of hMSCs, affected by the different mechanical properties of the gel, was regulated by parathyroid hormone (PTH). Notably, in response to PTH, hMSCs in a high-stiffness microenvironment upregulate osteogenic differentiation while exhibiting increased proliferation in a low-stiffness microenvironment. Overall, the developed system enables the generation of multiple cell-laden three-dimensional cell culture models with diverse mechanical properties and holds significant potential for expansion into drug testing.

A long-term storable gel-laden chip composite built in a multi-well plate enablingin situcell encapsulation for high-throughput liver model.

Hydrogels are widely used as scaffold materials for constructingin vitrothree-dimensional microphysiological systems. However, their high sensitivity to various external cues hinders the development of hydrogel-laden, microscale, and high-throughput chips. Here, we have developed a long-term storable gel-laden chip composite built in a multi-well plate, which enablesin situcell encapsulation and facilitates high-throughput analysis. Through optimized chemical crosslinking and freeze-drying method (C/FD), we have achieved a high-quality of gel-laden chip composite with excellent transparency, uniform porosity, and appropriate swelling and mechanical characteristics. Besides collagen, decellularized extracellular matrix with tissue-specific biochemical compound has been applied as chip composite. As a ready-to-use platform,in situcell encapsulation within the gel has been achieved through capillary force generated during gel reswelling. The liver-mimetic chip composite, comprising HepG2 cells or primary hepatocytes, has demonstrated favorable hepatic functionality and high sensitivity in drug testing. The developed fabrication process with improved stability of gels and storability allows chip composites to be stored at a wide range of temperatures for up to 28 d without any deformation, demonstrating off-the-shelf products. Consequently, this provides an exceptionally simple and long-term storable platform that can be utilized for an efficient tissue-specific modeling and various biomedical applications.

Bone-on-a-Chip: Biomimetic Models Based on Microfluidic Technologies for Biomedical Applications.

With the increasing importance of preclinical evaluation of newly developed drugs or treatments, in vitro organ or disease models are necessary. Although various organ-specific on-chip (organ-on-a-chip, or OOC) systems have been developed as emerging in vitro models, bone-on-a-chip (BOC) systems that recapitulate the bone microenvironment have been less developed or reviewed compared with other OOCs. The bone is one of the most dynamic organs and undergoes continuous remodeling throughout its lifetime. The aging population is growing worldwide, and healthcare costs are rising rapidly. Since in vitro BOC models that recapitulate native bone niches and pathological features can be important for studying the underlying mechanism of orthopedic diseases and predicting drug responses in preclinical trials instead of in animals, the development of biomimetic BOCs with high efficiency and fidelity will be accelerated further. Here, we review recently engineered BOCs developed using various microfluidic technologies and investigate their use to model the bone microenvironment. We have also explored various biomimetic strategies based on biological, geometrical, and biomechanical cues for biomedical applications of BOCs. Finally, we addressed the limitations and challenging issues of current BOCs that should be overcome to obtain more acceptable BOCs in the biomedical and pharmaceutical industries.

A high-throughput biomimetic bone-on-a-chip platform with artificial intelligence-assisted image analysis for osteoporosis drug testing.

Although numerous organ-on-a-chips have been developed, bone-on-a-chip platforms have rarely been reported because of the high complexity of the bone microenvironment. With an increase in the elderly population, a high-risk group for bone-related diseases such as osteoporosis, it is essential to develop a precise bone-mimicking model for efficient drug screening and accurate evaluation in preclinical studies. Here, we developed a high-throughput biomimetic bone-on-a-chip platform combined with an artificial intelligence (AI)-based image analysis system. To recapitulate the key aspects of natural bone microenvironment, mouse osteocytes (IDG-SW3) and osteoblasts (MC3T3-E1) were cocultured within the osteoblast-derived decellularized extracellular matrix (OB-dECM) built in a well plate-based three-dimensional gel unit. This platform spatiotemporally and configurationally mimics the characteristics of the structural bone unit, known as the osteon. Combinations of native and bioactive ingredients obtained from the OB-dECM and coculture of two types of bone cells synergistically enhanced osteogenic functions such as osteocyte differentiation and osteoblast maturation. This platform provides a uniform and transparent imaging window that facilitates the observation of cell-cell interactions and features high-throughput bone units in a well plate that is compatible with a high-content screening system, enabling fast and easy drug tests. The drug efficacy of anti-SOST antibody, which is a newly developed osteoporosis drug for bone formation, was tested via ß-catenin translocation analysis, and the performance of the platform was evaluated using AI-based deep learning analysis. This platform could be a cutting-edge translational tool for bone-related diseases and an efficient alternative to bone models for the development of promising drugs.

Prediction of anticancer drug resistance using a 3D microfluidic bladder cancer model combined with convolutional neural network-based image analysis.

Bladder cancer is the most common urological malignancy worldwide, and its high recurrence rate leads to poor survival outcomes. The effect of anticancer drug treatment varies significantly depending on individual patients and the extent of drug resistance. In this study, we developed a validation system based on an organ-on-a-chip integrated with artificial intelligence technologies to predict resistance to anticancer drugs in bladder cancer. As a proof-of-concept, we utilized the gemcitabine-resistant bladder cancer cell line T24 with four distinct levels of drug resistance (parental, early, intermediate, and late). These cells were co-cultured with endothelial cells in a 3D microfluidic chip. A dataset comprising 2,674 cell images from the chips was analyzed using a convolutional neural network (CNN) to distinguish the extent of drug resistance among the four cell groups. The CNN achieved 95.2% accuracy upon employing data augmentation and a step decay learning rate with an initial value of 0.001. The average diagnostic sensitivity and specificity were 90.5% and 96.8%, respectively, and all area under the curve (AUC) values were over 0.988. Our proposed method demonstrated excellent performance in accurately identifying the extent of drug resistance, which can assist in the prediction of drug responses and in determining the appropriate treatment for bladder cancer patients.

Inhibition of tumor progression and M2 microglial polarization by extracellular vesicle-mediated microRNA-124 in a 3D microfluidic glioblastoma microenvironment.

Background: Glioblastoma (GBM) is one of the most aggressive types of brain cancer. GBM progression is closely associated with microglia activation; therefore, understanding the regulation of the crosstalk between human GBM and microglia may help develop effective therapeutic strategies. Elucidation of efficient delivery of microRNA (miRNA) via extracellular vesicles (EVs) and their intracellular communications is required for therapeutic applications in GBM treatment. Methods: We used human GBM cells (U373MG) and human microglia. MiRNA-124 was loaded into HEK293T-derived EVs (miR-124 EVs). Various anti-tumor effects (proliferation, metastasis, chemosensitivity, M1/M2 microglial polarization, and cytokine profile) were investigated in U373MG and microglia. Anti-tumor effect of miR-124 EVs was also investigated in five different patient-derived GBM cell lines (SNU-201, SNU-466, SNU-489, SNU-626, and SNU-1105). A three-dimensional (3D) microfluidic device was used to investigate the interactive microenvironment of the tumor and microglia. Results: MiR-124 EVs showed highly efficient anti-tumor effects both in GBM cells and microglia. The mRNA expression levels of tumor progression and M2 microglial polarization markers were decreased in response to miR-124 EVs. The events were closely related to signal transducer and activator of transcription (STAT) 3 signaling in both GBM and microglia. In 3D microfluidic experiments, both U373MG and microglia migrated to a lesser extent and showed less-elongated morphology in the presence of miR-124 EVs compared to the control. Analyses of changes in cytokine levels in the microfluidic GBM-microglia environment showed that the treatment with miR-124 EVs led to tumor suppression and anti-cancer immunity, thereby recruiting natural killer (NK) cells into the tumor. Conclusions: In this study, we demonstrated that EV-mediated miR-124 delivery exerted synergistic anti-tumor effects by suppressing the growth of human GBM cells and inhibiting M2 microglial polarization. These findings provide new insights toward a better understanding of the GBM microenvironment and provide substantial evidence for the development of potential therapeutic strategies using miRNA-loaded EVs.