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Infection with African swine fever virus (ASFV) causes an acute and highly lethal hemorrhagic disease that has been responsible for huge economic losses in China. To exactly detect the antigen of ASFV, we established a rapid, no-wash, one-step sandwich-type immunoassay based on the amplified luminescent proximity homogenous assay-linked immunosorbent assay (AlphaLISA) using two monoclonal antibodies (mAbs) M-5 and M-6 against ASFV p72. ASFV p72 in samples was captured by biotinylated mAb M-5 connected to the donor bead surface via streptavidin and "sandwiched" by mAb M-6 which was coated onto the acceptor bead. Efficacy and sensitivity trials revealed that the AlphaLISA could detect ≥0.78 ng/ml of purified p72 and with a linear range of 0.78–100 ng/ml. The AlphaLISA was specific for ASFV and did not cross-react with other common pathogenic porcine viruses. Compared with RealPCR ASFV DNA test and ASFV antigen detection kit, the sensitivity of the AlphaLISA evaluated in 60 porcine serum samples was 93% and 100%, respectively. The specificity was 100% and 91.7%, respectively. This study presents a good laboratory diagnostic tool for sensitive and efficient detection of ASFV in porcine serum. Key points: • MAbs M-5 and M-6 recognized various epitopes of ASFV p72. • The established ASFV p72 AlphaLISA showed well specificity, high sensitivity, and satisfied correlation coefficient. [ABSTRACT FROM AUTHOR]

• Prognostic signature of m6A-associated lncRNAs constructed in thyroid cancer. • Prognostic signature correlate with immune infiltration. • Prognostic signature correlates with response to immunotherapy. • LINC02471 and DOCK9-DT as new biomarkers in thyroid cancer. Thyroid cancer (THCA) is the most common endocrine malignancy worldwide and has been rising at the fastest rate in recent years. Long-stranded non-coding RNAs (lncRNAs) and N6-methyladenosine (m6A) have been associated with immunotherapy efficacy and cancer prognosis. However, how m6A-associated lncRNAs (mrlncRNAs) affect the prognosis of patients with thyroid cancer is unclear. Therefore, this study utilized The Cancer Genome Atlas (TCGA) database to provide thyroid cancer-related transcriptomic data and related clinical data. The R program was used to identify m6A-related lncRNAs, and a risk model consisting of two lncRNAs (LINC02471 and DOCK9-DT) was obtained using least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Kaplan-Meier survival analysis and transient subject operating characteristics (ROC) were used for analysis. The results showed a substantial association between immune cell infiltration and risk scores. Independent analyses confirmed that the expression of LINC02471 and DOCK9-DT was significantly higher in thyroid cancer tissues than in normal tissues, suggesting that they may be useful biomarkers for thyroid cancer. [ABSTRACT FROM AUTHOR]

The CNC machining of nephrite is increasingly used in the jade engraving industry. As the most important standard for quality evaluation, surface roughness is influenced by cutting parameters. In this paper, taking the Buddha head as the machining object, the influence of cutting parameters on the surface quality of was studied by SYIL S7 CNC milling machine. The grooving experiment was carried out at spindle speed of 24,000 rpm, then the CAXA manufacturing engineer and JDpiant software were comparatively applied in machining. Furtherly, the influence of the spindle speed on the roughness was investigated. The research results were summarized as follows: (1) No edge breakage appeared when feed speed lower than 300 mm/min with the maximum depth of cut of 0.1 mm. In this case, when the jade is machined with the spindle speed range of 16,000–24,000 rpm, the mean roughness R a was in the range of 1,496.111–891.842 nm. (2) JDpiant software is more suitable for CNC jade engraving than CAXA manufacturing engineer. (3) In roughing stage, only the high-speed grinding contdition is satisfied, the integrity of side profile could be guaranteed. The higher spindle speed was conducive to achieve the fine surface quality. (4) The tungsten steel cutter in finish machining stage shows better grinding ability than diamond cutter used in rough machining stage. In order to formulate an economic spindle speed, the finishing surface roughness should be considered in conjunction with the requirement of polishing. [ABSTRACT FROM AUTHOR]

We report a simple, economical and green one-pot hydrothermal strategy to synthesize the bio-derived nitrogen-doped carbon sheets (ONCSs) embedded with zirconia nanoparticles (ZrO 2 NPs) with orange juice as carbon source and solvent. The ONCSs-ZrO 2 NPs composite was further applied in the decoration of glassy carbon electrode (GCE) for electrochemical sensing of methyl parathion. The orange juice-derived ONCSs with graphene-like micromorphology showed good electrical conductivity, large specific surface area, and nitrogen functional groups. They could accelerate the electron transport, provide sufficient electrolyte-electrode interface, and improve the surface wettability, thus forming a suitable microenvironment for the redox reaction of MP. The embedded ZrO 2 NPs in graphene-like ONCSs possessed a strong affinity toward the phosphorus groups on MP molecules, which could promote the preconcentration of MP in the interface of the fabricated sensor and electrolyte. Benefitting from the synergistic effect of ONCSs and ZrO 2 NPs/GCE, the ONCSs-ZrO 2 NPs/GCE sensor exhibited excellent peak current response towards MP with a linear detection range of 0.01–15 μg mL−1 and a low detection limit of 0.115 ng mL−1. Furthermore, the ONCSs-ZrO 2 NPs/GCE sensor presented good capability to investigate the MP levels in romaine and kiwifruit juices with satisfactory recoveries. This work provides a novel and green one-step approach in the development of carbon-based composite materials for high-performance MP electrochemical sensors. [ABSTRACT FROM AUTHOR]

A Ni–P–(sol)Al2O3 coating was prepared on the surface of Q235 steel by direct-current electrodeposition. This method was combined with sol-gel and electrodeposition technique, instead of the traditional nanopowder dispersion, to prepare highly dispersible oxide nanoparticle-reinforced composites. The effects of temperature, pH value, and current density and Al2O3 sol on the hardness of composite coating were investigated. The coating surface morphology and structure were characterized by scanning electron microscopy and energy dispersive spectroscopy, respectively. The corrosion resistance of coatings in the presence of intermediate layers was evaluated by electrochemical measurement in 3.5% NaCl solution by open-circuit potential measurement at room temperature. The hardness and wear resistance of the coating were measured by a microindentation instrument and friction wear machine, respectively. The results showed that Al2O3 sol can effectively improve Ni–P alloy coating structure and refine grain. When the bath temperature was 55°C, the pH value was 4.5, the amount of sol was 80 mL/L, the current density was 1 A/dm2, and the hardness of the nanosol coating was 569 HV. Compared with Ni–P, the friction coefficient increases slightly, but the wear rate was only 1.768 × 10 − 6 g · m − 1 . The corrosion resistance was also better than that of Ni–P coating. [ABSTRACT FROM AUTHOR]

Summary: This article handles the probability‐guaranteed state estimation problem for a class of nonlinear memristive neural networks (MNNs) by using an event‐triggered mechanism. Both time‐varying delays and incomplete measurements are considered in the MNNs dynamics. To mitigate the impact of limited communication bandwidth, a communication protocol is proposed that incorporates an encoding–decoding technique in addition to an event‐triggered scheme. The aim is to devise a state estimator that can estimate the states of MNNs, ensuring that the state estimation error falls within the required ellipsoidal area with a desired chance. We obtain sufficient conditions for the feasibility of the addressed problem, where the requested gains can be found iteratively by solving certain convex optimization problems. On the basis of the proposed framework, some issues are further presented to determine locally optimal estimator parameters according to different specifications. Finally, we utilize an illustrative numerical example to show the validity of our provided theoretical results. [ABSTRACT FROM AUTHOR]