40 research outputs found

    Potential Application of the CRISPR/Cas9 System against Herpesvirus Infections.

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    The CRISPR/Cas9 system has been applied in the genome editing and disruption of latent infections for herpesviruses such as the herpes simplex virus, Epsteinā»Barr virus, cytomegalovirus, and Kaposi's sarcoma-associated herpesvirus. CRISPR/Cas9-directed mutagenesis can introduce similar types of mutations to the viral genome as can bacterial artificial chromosome recombination engineering, which maintains and reconstitutes the viral genome successfully. The cleavage mediated by CRISPR/Cas9 enables the manipulation of disease-associated viral strains with unprecedented efficiency and precision. Additionally, current therapies for herpesvirus productive and latent infections are limited in efficacy and cannot eradicate viruses. CRISPR/Cas9 is potentially adapted for antiviral treatment by specifically targeting viral genomes during latent infections. This review, which focuses on recently published progress, suggests that the CRISPR/Cas9 system is not only a useful tool for basic virology research, but also a promising strategy for the control and prevention of herpesvirus latent infections

    RNase P Ribozymes Inhibit the Replication of Human Cytomegalovirus by Targeting Essential Viral Capsid Proteins.

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    An engineered RNase P-based ribozyme variant, which was generated using the in vitro selection procedure, was used to target the overlapping mRNA region of two proteins essential for human cytomegalovirus (HCMV) replication: capsid assembly protein (AP) and protease (PR). In vitro studies showed that the generated variant, V718-A, cleaved the target AP mRNA sequence efficiently and its activity was about 60-fold higher than that of wild type ribozyme M1-A. Furthermore, we observed a reduction of 98%-99% in AP/PR expression and an inhibition of 50,000 fold in viral growth in cells with V718-A, while a 75% reduction in AP/PR expression and a 500-fold inhibition in viral growth was found in cells with M1-A. Examination of the antiviral effects of the generated ribozyme on the HCMV replication cycle suggested that viral DNA encapsidation was inhibited and as a consequence, viral capsid assembly was blocked when the expression of AP and PR was inhibited by the ribozyme. Thus, our study indicates that the generated ribozyme variant is highly effective in inhibiting HCMV gene expression and blocking viral replication, and suggests that engineered RNase P ribozyme can be potentially developed as a promising gene-targeting agent for anti-HCMV therapy

    Inhibition of Murine Cytomegalovirus Infection in Animals by RNase P-Associated External Guide Sequences.

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    External guide sequence (EGS) RNAs are associated with ribonuclease P (RNase P), a tRNA processing enzyme, and represent promising agents for gene-targeting applications as they can direct RNase-P-mediated cleavage of a target mRNA. Using murine cytomegalovirus (MCMV) as a model system, we examined the antiviral effects of an EGS variant, which was engineered using in vitro selection procedures. EGSs were used to target the shared mRNA region of MCMV capsid scaffolding protein (mCSP) and assemblin. In vitro, the EGS variant was 60 times more active in directing RNase P cleavage of the target mRNA than the EGS originating from a natural tRNA. In MCMV-infected cells, the variant reduced mCSP expression by 92% and inhibited viral growth by 8,000-fold. In MCMV-infected mice hydrodynamically transfected with EGS-expressing constructs, the EGS variant was more effective in reducing mCSP expression, decreasing viral production, and enhancing animal survival than the EGS originating from a natural tRNA. These results provide direct evidence that engineered EGS variants with higher targeting activity in vitro are also more effective in reducing gene expression in animals. Furthermore, our findings imply the possibility of engineering potent EGS variants for therapy of viral infections

    Research on the Impact of Carbon Trading Policy on the Structural Upgrading of Marine Industry

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    To promote greenhouse gas emission reduction, China has proposed a dual carbon target to achieve carbon peaking by 2030 and carbon neutrality by 2060. Since 2013, China has opened an increasing number of carbon emission trading pilot projects, and at this stage, Chinaā€™s carbon emission trading policy has been gradually promoted to the whole country; therefore, how can marine economy be affected under the promotion of carbon trading policy? This paper uses the difference in differences method to study the data of marine industry structure of Chinese coastal provinces from 2010 to 2018. The study finds that carbon trading policies promote the upgrading of the marine industry structure, and further verifies that the impact of carbon trading policies on the upgrading of the marine industry structure is spatially heterogeneous. In other words, the carbon trading policy also has a significant promoting effect on the provinces within 160 km of the pilot provinces, but the effect will be weaker than that of the pilot provinces; at 160ā€“320 km from the pilot provinces, the carbon trading policy has no significant promoting effect on the provinces within this range; at 320ā€“960 km from the pilot provinces, the effect of the carbon trading policy on the provinces within this range becomes negative and significant, showing a suppressive effect. The experimental findings of this paper will provide a reference for China to achieve its carbon neutrality goal and realize a strong ocean state

    Noise Removal and Feature Extraction in Airborne Radar Sounding Data of Ice Sheets

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    The airborne ice-penetrating radar (IPR) is an effective method used for ice sheet exploration and is widely applied for detecting the internal structures of ice sheets and for understanding the mechanism of ice flow and the characteristics of the bottom of ice sheets. However, because of the ambient influence and the limitations of the instruments, IPR data are frequently overlaid with noise and interference, which further impedes the extraction of layer features and the interpretation of the physical characteristics of the ice sheet. In this paper, we first applied conventional filtering methods to remove the feature noise and interference in IPR data. Furthermore, machine learning methods were introduced in IPR data processing for noise removal and feature extraction. Inspired by a comparison of the filtering methods and machine learning methods, we propose a fusion method combining both filtering methods and machine-learning-based methods to optimize the feature extraction in IPR data. Field data tests indicated that, under different conditions of IPR data, the application of different methods and strategies can improve the layer feature extraction

    Noise Removal and Feature Extraction in Airborne Radar Sounding Data of Ice Sheets

    No full text
    The airborne ice-penetrating radar (IPR) is an effective method used for ice sheet exploration and is widely applied for detecting the internal structures of ice sheets and for understanding the mechanism of ice flow and the characteristics of the bottom of ice sheets. However, because of the ambient influence and the limitations of the instruments, IPR data are frequently overlaid with noise and interference, which further impedes the extraction of layer features and the interpretation of the physical characteristics of the ice sheet. In this paper, we first applied conventional filtering methods to remove the feature noise and interference in IPR data. Furthermore, machine learning methods were introduced in IPR data processing for noise removal and feature extraction. Inspired by a comparison of the filtering methods and machine learning methods, we propose a fusion method combining both filtering methods and machine-learning-based methods to optimize the feature extraction in IPR data. Field data tests indicated that, under different conditions of IPR data, the application of different methods and strategies can improve the layer feature extraction
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