Development of sterile platform for quantification of extracellular analytes via single walled carbon nanotubes

Progress has been made studying cell-cell signaling communication processes. However, due to limitations of current sensors on time and spatial resolution, the role of many extracellular analytes is still unknown. A single walled carbon nanotube (SWNT) platform was previously developed based on the avidin-biotin immobilization of SWNT to a glass substrate. The SWNT platform provides real time feedback about analyte concentration and has a high concentration of evenly distributed sensors, both of which are essential for the study of extracellular analytes. Unfortunately, this initial SWNT platform is synthesized through unsterile conditions and cannot be sterilized post-production due to the delicate nature of the sensors, making it unsuitable for in vitro work. Herein the multiple-step process for SWNT immobilization is modified and the platform's biocompatibility is assessed in terms of sterility, cytotoxicity, cell proliferation, and cell morphology through comparison with non-sensors controls. The results demonstrate the SWNT platform's sterility and lack of toxicity over 72 h. The proliferation rate and morphology profiles for cells growing on the SWNT platform are similar to those grown on tissue culture substrates. This novel nano-sensor platform preserves cell health and cell functionality over time, offering opportunities to study extracellular analytes gradients in cellular communication.

Weighted Gene Coexpression Network Analysis Reveals the Dynamic Transcriptome Regulation and Prognostic Biomarkers of Hepatocellular Carcinoma

This study was aimed at revealing the dynamic regulation of mRNAs, long noncoding RNAs (lncRNAs), and microRNAs (miRNAs) in hepatocellular carcinoma (HCC) and to identify HCC biomarkers capable of predicting prognosis. Differentially expressed mRNAs (DEmRNAs), lncRNAs, and miRNAs were acquired by comparing expression profiles of HCC with normal samples, using an expression data set from The Cancer Genome Atlas. Altered biological functions and pathways in HCC were analyzed by subjecting DEmRNAs to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis. Gene modules significantly associated with disease status were identified by weighted gene coexpression network analysis. An lncRNA-mRNA and an miRNA-mRNA coexpression network were constructed for genes in disease-related modules, followed by the identification of prognostic biomarkers using Kaplan-Meier survival analysis. Differential expression and association with the prognosis of 4 miRNAs were verified in independent data sets. A total of 1220 differentially expressed genes were identified between HCC and normal samples. Differentially expressed mRNAs were significantly enriched in functions and pathways related to “plasma membrane structure,” “sensory perception,” “metabolism,” and “cell proliferation.” Two disease-associated gene modules were identified. Among genes in lncRNA-mRNA and miRNA-mRNA coexpression networks, 9 DEmRNAs and 7 DEmiRNAs were identified to be potential prognostic biomarkers. MIMAT0000102, MIMAT0003882, and MIMAT0004677 were successfully validated in independent data sets. Our results may advance our understanding of molecular mechanisms underlying HCC. The biomarkers may contribute to diagnosis in future clinical practice.