Rapid and facile detection of largemouth bass ranavirus with CRISPR/Cas13a.

Largemouth bass ranavirus (LMBV) is an epidemic disease that seriously jeopardizes the culture of largemouth bass（Micropterus salmoides）, and it has a very high incidence in largemouth bass. Once an outbreak occurs, it may directly lead to the failure of the culture, resulting in substantial economic losses, but there is no effective vaccine or special effective drug yet. Consequently, it is important to establish an accurate, sensitive, convenient and specific detection approach for preventing LMBV infection. The recombinant enzyme-assisted amplification (RAA) technology was used in combination with clustered regularly interspaced short palindromic repeats (CRISPR), and associated protein 13a (CRISPR/Cas13a) to detect LMBV. We designed RAA primers and CRISPR RNA (crRNA) that targeted the conserved region in the LMBV main capsid protein (MCP) gene, amplified sample nucleic acids using the RAA technology, performed CRISPR/Cas13a fluorescence detection and evaluated the sensitivity and specificity of the established method with qPCR as a control method. This technique was able to determine the results by collecting fluorescence signals, visualizing fluorescence by UV excitation and combining with lateral flow strips (LFS). The sensitivity and specificity of the established method were consistent with the qPCR method. Besides, it was performed at a constant temperature of 37 °C and the sensitivity of the reaction system was 3.1 × 101 copies/µL, with no cross-reactivity with other common aquatic pathogens. Further, the positive detection rate of the proposed method in 32 clinical samples was consistent with that of qPCR. In conclusion, our established RAA-CRISPR/Cas13 method for detecting LMBV is sensitive, simple and specific, which is applicable in the rapid on-site detection and epidemiological monitoring of LMBV.

Identification and application of an endophytic fungus Arcopilus aureus from Panax notoginseng against crop fungal disease.

Endophytic fungi are important microbial resources for developing novel antibacterial and antifungal drugs to prevent and control crop diseases. Panax notoginseng has been used as a Chinese medicinal herb for a long time, as it has various bioactivities. However, information on endophytic fungi isolated from Panax notoginseng is rare. In this study, an endophytic fungus known as SQGX-6, which was later identified as the golden hair fungus Arcopilus aureus, was isolated from Panax notoginseng. SQGX-6 was extracted using ethyl acetate, and the active components of the fungus were identified using ultra-performance liquid chromatography-mass spectrometry (UHPLC-MS). The antifungal and antioxidant activities of the extract were determined and evaluated in vitro and in vivo. SQGX-6 and its extract inhibited the growth of Corn stalk rot (Fusarium graminearum), Corn southern leaf blight (Helminthosporium maydis), and Tomato gray mold (Botrytis cinerea) in vitro. The free radical scavenging rates for 2,2-Diphenyl-1-pyridinyl hydrazide (DPPH) radical scavenging activity, 3-Ethylbenzothiazoline-6-Sulfonic Acid Radical scavenging (ABTS) activity were also downregulated by the SQGX-6 extract. In vivo, the SQGX-6 extract inhibited the mycelial growth rates of the three aforementioned fungi and downregulated malondialdehyde (MDA) content and upregulated peroxidase (POD) and phenylalanine ammonia-lyase (PAL) content in fruits, leading to significant reduction in damage to cherry tomatoes caused by Botrytis cinerea. UHPLC-MS was performed to identify various active substances, including Alkaloids, Azoles, Benzofurans, Coumarins, Flavonoids, Organic acids, Phenols, and plant growth regulators contained in the extract. These results suggested that the endophytic fungus SQGX-6 of Panax notoginseng and its extract have excellent antifungal and antioxidant activities, and thus, it is an important microbial resource for the developing novel drugs against plant fungal infections.

Rapid detection of grass carp reovirus type 1 using RPA-based test strips combined with CRISPR Cas13a system.

Introduction: Due to the existence of grass carp reovirus (GCRV), grass carp hemorrhagic disease occurs frequently, and its high pathogenicity and infectivity are great challenges to the aquaculture industry. As a highly pathogenic pathogen, the outbreak of hemorrhagic disease often causes tremendous economic losses. Therefore, it is important to rapidly and accurately detect GCRV on site to control timely. Methods: In this study, recombinant enzyme amplification (RPA) combined with clustered regularly interspaced short palindromic repeats (CRISPR)/Cas13a system was employed to establish a method to detect the vp7 gene of grass carp reovirus type 1. This method can be adopted for judging the results by collecting fluorescence signal, ultraviolet excitation visual fluorescence and test strip. Results: Combined with the RPA amplification experiment, the detection limit of the RPA-CRISPR method can reach 7.2 × 101 copies/µL of vp7 gene per reaction, and the detection process can be completed within 1 h. In addition, this method had no cross-reaction with the other 11 common aquatic pathogens. Then, the performance of the RPA-CRISPR/Cas13a detection method was evaluated by comparing it with the real-time fluorescence quantitative PCR detection method of clinical samples. The results of RPA-CRISPR/Cas13a detection were shown to be in consistence with the results obtained from the real-time fluorescence quantitative PCR detection. The coincidence rate of this method with 26 GCRV clinical samples was 92.31%. Discussion: In summary, this method has high sensitivity, specificity and on-site practicability for detecting GCRV type 1, and has great application potential in on-site GCRV monitoring.

Fractional-order numerical modeling to study chloride ion transport in concrete with fly ash or slag additions.

To better study the chloride ion migration in concrete with fly ash or ground granulated blast furnace slag under low fatigue load, a Caputo time fractional-order chloride diffusion model is developed in this paper. The model, grounded in Fick's second law with a fractional-order derivative, employs an implicit numerical method for discretization, resulting in a fractional-order numerical scheme. The stability and convergence of the scheme are rigorously proven within the paper. The model's unknown parameters are estimated using genetic algorithm with a grid method. To validate the model's effectiveness, its numerical solution is juxtaposed with experimental results from chloride erosion studies. Furthermore, the fitting efficacy of the Caputo time fractional-order numerical scheme is compared with that of the classical Fick's second law numerical scheme and analytical solution. The research findings demonstrate that the fractional-order numerical scheme can more accurately simulate the chloride concentration in concrete containing fly ash or slag. Additionally, the model shows promise in predicting the service life of fly ash or slag concrete.

Multi-term time fractional diffusion equations and novel parameter estimation techniques for chloride ions sub-diffusion in reinforced concrete.

In this paper, searching for a better chloride ions sub-diffusion system, a multi-term time-fractional derivative diffusion model is proposed for the description of the time-dependent chloride ions penetration in reinforced concrete structures exposed to chloride environments. We prove the stability and convergence of the model. We use the modified grid approximation method (MGAM) to estimate the fractional orders and chloride ions diffusion coefficients in the reinforced concrete for the multi-term time fractional diffusion system. And then to verify the efficiency and accuracy of the proposed methods in dealing with the fractional inverse problem, two numerical examples with real data are investigated. Meanwhile, we use two methods of fixed chloride ions diffusion coefficient and variable diffusion coefficient with diffusion depth to simulate chloride ions sub-diffusion system. The result shows that with the new fractional orders and parameters, our multi-term fractional order chloride ions sub-diffusion system is capable of providing numerical results that agree better with the real data than other models. On the other hand, it is also noticed from the numerical solution of the chloride ions sub-diffusion system that setting the variable diffusion coefficient with diffusion depth is more reasonable. And it is also found that chloride ions diffusion coefficients in reinforced concrete should be decreased with diffusion depth which is completely consistent with the theory. In addition, the model can be used to predict the chloride profiles with a time-dependent property. This article is part of the theme issue 'Advanced materials modelling via fractional calculus: challenges and perspectives'.