Characterization of CircRNA-Associated CeRNA Networks in Folate Deficiency-Induced Neural Tube Defects.

Objective: Circular RNAs (circRNAs) participate in several important pathological processes and have been used in the diagnosis and treatment of various diseases. This study aimed to investigate the role of circRNAs in neural tube defects (NTDs). Method: We characterized circRNA-associated competitive endogenous RNA (ceRNA) networks in brain tissue of low folate -induced NTDs mouse at embryonic day 13.5 by high-throughput sequencing. The expression levels of Circzfp644, miR-20-5p and Gas7 were detected by RT-PCR. Gas7 and Circzfp644 functions were determined by miRNA-mimics and inhibitors in mouse teratocarcinoma cells (F9 cells), and luciferase gene reporter assay was assessed in the F9 cells. In addition, the expression levels of Circzfp644, miR-20-5p and Gas7 were determined by Nanostring in human NTDs tissues. Results: We detected 57 circRNA transcripts, 16 miRNAs, and 148 mRNAs that were significantly dysregulated in NTDs brain tissues compared with their expression levels in control (normal) tissues. Circzfp644 shared miRNA response elements with the growth arrest specific 7 ( Gas7) gene and competitively bound with miR-20-5p to increase the expression of Gas7. Downregulation of Circzfp644 and Gas7 and upregulation of miR-20-5p were found in human NTD tissue. Conclusion: This study provides new perspectives on the role of circRNAs in nervous system development and the pathogenesis of NTDs.

Down-regulation of long noncoding RNA LINC00472 alleviates sepsis-induced acute hepatic injury by regulating miR-373-3p/TRIM8 axis.

BACKGROUND: The long noncoding RNAs (lncRNAs) have been confirmed to be involved in sepsis-induced organ injury. Here, we first investigated the functional role and the underlying mechanism of lncRNA LINC00472 in sepsis-induced acute hepatic injury (AHI). METHODS: Human liver THLE-3 cells were treated with lipopolysaccharide (LPS) to mimic sepsis-induced AHI in vitro; intraperitoneal injection of LPS in rats were used as an in vivo model of AHI induced by sepsis. The expressions of LINC00472, miR-373-3p, and TRIM8 mRNA were detected by qRT-PCR. The effects of LINC00472 and miR-373-3p on the viability of THLE-3 cells were assessed by CCK-8 assay. Dual-luciferase reporter and RNA immunoprecipitation (RIP) assays were performed to determine the binding relationship between LINC00472 and miR-373-3p as well as between miR-373-3p and TRIM8. The expressions of apoptosis-related proteins and TRIM8 were detected by Western blot; the levels of ALT, AST, TNF-α, IL-6, and IL-10 in the serum of rats were measured using ELSA assay. RESULTS: LINC00472 and TRIM8 were significantly upregulated in liver tissues and THLE-3 cells in sepsis-induced AHI models, while miR-373-3p was downregulated. Silencing of LINC00472 promoted cell viability and suppressed cell apoptosis in LPS-treated THLE-3 cells, whereas upregulation of LINC00472 had the opposite effect. Moreover, LINC00472 served as a sponge for miR-373-3p and negatively regulated its expression. miR-373-3p mimics could promote THLE-3 cell viability and suppress cell apoptosis. Additionally, TRIM8 was a direct target of miR-373-3p, which was downregulated in LINC00472-silenced cells and upregulated by the miR-373-3p inhibitor. Further, the co-transfection of miR-373-3p inhibitor reversed the effects of LINC00472 knockdown on cell viability and apoptosis. Downregulation of LINC00472 in rats restored the levels of ALT, AST, IL-6, IL-10, and TNF-α. CONCLUSION: Downregulation of LINC00472 ameliorates sepsis-induced AHI by regulating the miR-373-3p/TRIM8 axis.

[Algae identification research based on fluorescence spectral imaging technology combined with cluster analysis and principal component analysis].

In order to explore rapid real-time algae detection methods, in the present study experiments were carried out to use fluorescence spectral imaging technology combined with a pattern recognition method for identification research of different types of algae. The fluorescence effect of algae samples is obvious during the detection. The fluorescence spectral imaging system was adopted to collect spectral images of 40 algal samples. Through image denoising, binarization processing and making sure the effective pixels, the spectral curves of each sample were drawn according to the spectral cube. The spectra in the 400-720 nm wavelength range were obtained. Then, two pattern recognition methods, i.e., hierarchical cluster analysis and principal component analysis, were used to process the spectral data. The hierarchical cluster analysis results showed that the Euclidean distance method and average weighted method were used to calculate the cluster distance between samples, and the samples could be correctly classified at a level of the distance L=2.452 or above, with an accuracy of 100%. The principal component analysis results showed that first-order derivative, second-order derivative, multiplicative scatter correction, standard normal variate and other pretreatments were carried out on raw spectral data, then principal component analysis was conducted, among which the identification effect after the second-order derivative pretreatment was shown to be the most effective, and eight types of algae samples were independently distributed in the principal component eigenspace. It was thus shown that it was feasible to use fluorescence spectral imaging technology combined with cluster analysis and principal component analysis for algae identification. The method had the characteristics of being easy to operate, fast and nondestructive.