Development of a Graphene Oxide-Incorporated Polydimethylsiloxane Membrane with Hexagonal Micropillars

Enhancing Nasopharyngeal Carcinoma Cell Separation with Selective Fibronectin Coating and Topographical Modification on Polydimethylsiloxane Scaffold Platforms

The extracellular matrix (ECM) serves as a complex scaffold with diverse physical dimensions and surface properties influencing NPC cell migration. Polydimethylsiloxane (PDMS), a widely used biocompatible material, is hydrophobic and undesirable for cell seeding. Thus, the establishment of a biomimetic model with varied topographies and surface properties is essential for effective NPC43 cell separation from NP460 cells. This study explored how ECM surface properties influence NP460 and NPC43 cell behaviors via plasma treatments and chemical modifications to alter the platform surface. In addition to the conventional oxygen/nitrogen (O2/N2) plasma treatment, O2 and argon plasma treatments were utilized to modify the platform surface, which increased the hydrophilicity of the PDMS platforms, resulting in enhanced cell adhesion. (3-aminopropyl)triethoxysilane and fibronectin (FN) were used to coat the PDMS platforms uniformly and selectively. The chemical coatings significantly affected cell motility and spreading, as cells exhibited faster migration, elongated cell shapes, and larger spreading areas on FN-coated surfaces. Furthermore, narrower top layer trenches with 5 µm width and a lower concentration of 10 µg/mL FN were coated selectively on the platforms to limit NP460 cell movements and enhance NPC43 cell separation efficiency. A significantly high separation efficiency of 99.4% was achieved on the two-layer scaffold platform with 20/5 µm wide ridge/trench (R/T) as the top layer and 40/10 µm wide R/T as the bottom layer, coupling with 10 µg/mL FN selectively coated on the sidewalls of the top and bottom layers. This work demonstrated an innovative application of selective FN coating to direct cell behavior, offering a new perspective to probe into the subtleties of NPC cell separation efficiency. Moreover, this cost-effective and compact microsystem sets a new benchmark for separating cancer cells.

Recognizing the Differentiation Degree of Human Induced Pluripotent Stem Cell-Derived Retinal Pigment Epithelium Cells Using Machine Learning and Deep Learning-Based Approaches

Induced pluripotent stem cells (iPSCs) can be differentiated into mesenchymal stem cells (iPSC-MSCs), retinal ganglion cells (iPSC-RGCs), and retinal pigmental epithelium cells (iPSC-RPEs) to meet the demand of regeneration medicine. Since the production of iPSCs and iPSC-derived cell lineages generally requires massive and time-consuming laboratory work, artificial intelligence (AI)-assisted approach that can facilitate the cell classification and recognize the cell differentiation degree is of critical demand. In this study, we propose the multi-slice tensor model, a modified convolutional neural network (CNN) designed to classify iPSC-derived cells and evaluate the differentiation efficiency of iPSC-RPEs. We removed the fully connected layers and projected the features using principle component analysis (PCA), and subsequently classified iPSC-RPEs according to various differentiation degree. With the assistance of the support vector machine (SVM), this model further showed capabilities to classify iPSCs, iPSC-MSCs, iPSC-RPEs, and iPSC-RGCs with an accuracy of 97.8%. In addition, the proposed model accurately recognized the differentiation of iPSC-RPEs and showed the potential to identify the candidate cells with ideal features and simultaneously exclude cells with immature/abnormal phenotypes. This rapid screening/classification system may facilitate the translation of iPSC-based technologies into clinical uses, such as cell transplantation therapy.

Preparation and Characterization of Functionalized Graphene Oxide Carrier for siRNA Delivery

A successful siRNA delivery system is dependent on the development of a good siRNA carrier. Graphene oxide (GO) has gained great attention as a promising nanocarrier in recent years. It has been reported that GO could be used to deliver a series of drugs including synthetic compounds, proteins, antibodies, and genes. Our previous research indicated that functionalized GO could deliver siRNA into tumor cells and induce a gene silencing effect, to follow up the research, in this research, GO-R8/cRGDfV(GRcR) was designed and prepared for VEGF-siRNA delivery as a novel carrier. The Zeta potential and particle size of the new designed GRcR carrier was measured at (29.46 ± 5.32) mV and (135.7 ± 3.3) nm respectively, and after transfection, the VEGF mRNA level and protein expression level were down-regulated by 48.22% (p < 0.01) and 38.3% (p < 0.01) in HeLa cells, respectively. The fluorescent images of the treated BALB/c nude mice revealed that GRcR/VEGF-siRNA could conduct targeted delivery of VEGF-siRNA into tumor tissues and showed a gene silencing effect as well as a tumor growth inhibitory effect (p < 0.01) in vivo. Further studies showed that GRcR/VEGF-siRNA could effectively inhibit angiogenesis by suppressing VEGF expression. Histology and immunohistochemistry studies demonstrated that GRcR/VEGF-siRNA could inhibit tumor tissue growth effectively and have anti-angiogenesis activity, which was the result of VEGF protein downregulation. Both in vitro and in vivo results demonstrated that GRcR/VEGF-siRNA could be used as an ideal nonviral tumor-targeting vector for VEGF-siRNA delivery in gene therapy.