BackgroundAleutian mink disease, mink viral enteritis and canine distemper are known as the three most serious diseases that cause great economic loss in the mink industry. In clinical practice, aleutian mink disease ...
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BackgroundAleutian mink disease, mink viral enteritis and canine distemper are known as the three most serious diseases that cause great economic loss in the mink industry. In clinical practice, aleutian mink disease virus (AMDV), mink enteritis virus (MEV) and canine distemper virus (CDV) are common mixed infections, and they have similar clinical clinical signs, such as diarrhoea. Therefore, a rapid and accurate differential diagnosis method for use on mink ranches is essential for the control of these three pathogens. Here, we developed multiplex one-step real-time quantitative PCR (RT-qPCR) assays for the simultaneous detection and quantification of AMDV, MEV and CDV by using three primers and probes based on the conserved NS1, VP2 and N genes, *** results showed that the established method can not cross-react with other mink pathogens, with a detection sensitivity of 25 copies/mu L and a coefficient of variation less than 3.51%. Moreover, the interference experiment showed that the presence of AMDV, MEV and CDV templates at different concentrations would not interfere with the detection results. Furthermore, two hundred clinical samples of mink with diarrhoea were simultaneously analysed using multiplex RT-qPCR and single RT-qPCR, the Kappa values were all greater than 0.921, indicating that there was a high degree of coincidence between the two detection *** conclusion, multiplex RT-qPCR exhibited high specificity, sensitivity, and reproducibility, indicating that this method can be used as a reliable and specific tool for the differential detection and quantification of AMDV, MEV and CDV.
Regarding the traditional lane-changing decision theory around the vehicle's intention to change lanes, less consideration of the behavioral interactions between vehicles, and the personalized driving preferences ...
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Regarding the traditional lane-changing decision theory around the vehicle's intention to change lanes, less consideration of the behavioral interactions between vehicles, and the personalized driving preferences of different drivers, this paper proposes a dynamic game for a lane-changing decision-making method that considers human-like driving preferences. First, to match the multiperformance evaluation requirements in the lane-changing process of intelligent vehicles, a cost function including driving space, traffic efficiency, and driving comfort is constructed. Second, the analytic hierarchy process (AHP) and criteria importance through intercriteria correlation (CRITIC) methods are used to conduct subjective and objective analyses on the next generation simulation (NGSIM) traffic data set to obtain the weight coefficients of multiple performance indicators of human-like driving preferences. The effects of different driving behaviors on lane-changing intentions and performance indexes are also studied. Finally, fuzzy control theory and intelligent driver model (IDM) are used to predict the driving behavior of interacting vehicles in the target lane, and the master-slave dynamic game theory and the particle swarm optimization algorithm are used to realize the behavioral interaction between the main vehicle and surrounding vehicles and to make the optimal lane-changing decisions. The research results show that the dynamic game lane-changing decision-making method of intelligent vehicles as proposed in this paper, which considers human-like driving preferences, can effectively meet the personalized requirements of different driving behaviors on driving space and traffic efficiency in the process of lane changing and improve the safety of intelligent vehicle lane-changing driving.
Osteosarcoma tissues demonstrated elevated expression of proteins (FDX1 and DLAT) integral to cuproptosis in our preliminary study, indicating the potential effectiveness of anti-tumor strategies predicated on this pr...
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Osteosarcoma tissues demonstrated elevated expression of proteins (FDX1 and DLAT) integral to cuproptosis in our preliminary study, indicating the potential effectiveness of anti-tumor strategies predicated on this process. Nevertheless, the overexpression of copper export proteins and the challenge of copper ion penetration may contribute to insufficient local copper ion concentration for inducing cuproptosis. Herein, we engineered a biomimetic copper-elesclomol-polyphenol network for the efficient delivery of copper ions and the copper ionophore elesclomol. Simultaneously, we integrated catalase (CAT) to alleviate tumor hypoxia, thereby inducing a greater reliance of tumor cells on aerobic respiration and enhancing cuproptosis sensitivity. In vitro analyses revealed that the nanocomplex exhibited potent cytotoxicity and displayed hallmark characteristics of cuproptosis. In vivo trials further validated targeted tumor accumulation, resulting in the suppression of tumor growth and lung metastasis. An augmentation in the proportion of activated immune cells in both tumor and draining lymph nodes was observed. The improvement of immunosuppressive microenvironment facilitated a synergistic antitumor effect with cuproptosis. The therapeutic efficacy was further evidenced in two osteosarcoma models, highlighting the potential as a safe and effective strategy against osteosarcoma and lung metastasis. Statement of significance: Osteosarcoma tissues exhibit a marked increase in the expression of proteins FDX1 and DLAT, which are crucial for cuproptosis. Moreover, cells that depend on mitochondrial respiration are more susceptible to cuproptosis. Here we developed a biomimetic copper-based nanocomplex to trigger cuproptosis against osteosarcoma and lung metastases. The nanocomplex demonstrated excellent biocompatibility and tumor targeting. Catalase incorporating facilitated oxygen generation within tumor microenvironment and alleviated hypoxia, thereby inducing a greater re
Currently, the epidemic situation of classical swine fever (CSF) is sporadic, and cases of atypical swine fever are on the rise in China. Therefore, it is necessary to accurately eliminate suspected cases by using hig...
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Currently, the epidemic situation of classical swine fever (CSF) is sporadic, and cases of atypical swine fever are on the rise in China. Therefore, it is necessary to accurately eliminate suspected cases by using highly sensitive and specific diagnostic techniques. Monoclonal and polyclonal antibodies are mostly used for the development of traditional enzyme-linked immunosorbent assays (ELISAs), but the use of certain conventional antibodies may be limited by their low yield, the difficulty of their isolation, and their high cost. Heavy-chain antibodies derived from camelids with naturally missing light chains can overcome these deficiencies and are an excellent alternative to conventional antibodies. In this study, a nanobody (Nb)-AviTag fusion protein was constructed, and the feasibility of its use as a high-sensitivity probe in a blocking ELISA (bELISA) for classical swine fever virus (CSFV) was investigated. The CSFV E2 recombinant protein expressed by the CHO expression system exhibited good reactogenicity and immunogenicity and induced the production of high CSFV antibody levels in rabbits. Three different clones of Nbs were successfully isolated using a phage display system in alpaca, and an Nb1-AviTag fusion protein was successfully expressed using an Escherichia coli expression system. The purified Nb1-AviTag fusion protein was then biotinylated in vitro to obtain Nb1-biotin. A novel bELISA was developed for the detection of CSFV antibodies in clinical serum using Nb1-biotin as a probe. The cutoff value of bELISA was 32.18%, the sensitivity of bELISA was higher than that of the bELISA kit with IDEXX antibody, and the coincidence rate was 94.7%. A rapid, low-cost, highly sensitive and highly specific CSFV E2 antibody-based bELISA method was successfully established and can be used for the serological evaluation of CSFV E2 subunit vaccines and the ELISA-based diagnosis of CSFV *** Currently, the epidemic situation of classical swine fever (C
Learning and job deterioration co-exist in many realistic scheduling situations. This paper introduces a general scheduling model with the effects of learning and deterioration simultaneously which is a significant ge...
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Learning and job deterioration co-exist in many realistic scheduling situations. This paper introduces a general scheduling model with the effects of learning and deterioration simultaneously which is a significant generalization of some existing models in the literature. By the effects of learning and deterioration, we mean that job processing times are defined by functions of their start times and positions in the sequence. This paper shows that the single-machine scheduling problems to minimize the makespan, sum of the kth power of completion times, total lateness and sum of earliness penalties (with a common due date) are polynomially solvable under the proposed model. It further shows that the problems to minimize the total weighted completion time, discounted total weighted completion time, maximum lateness, maximum tardiness, total tardiness and total weighted earliness penalties (with a common due date) are polynomially solvable under certain conditions. (C) 2010 Elsevier Ltd. All rights reserved.
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