The Pseudogene BMEA_B0173 Deficiency in Brucella melitensis Contributes to M-epitope Formation and Potentiates Virulence in a Mice Infection Model.

It is widely acknowledged that pseudogenes play important roles in bacterial diversification and evolution and participate in gene regulation and RNA interference (RNAi). However, the function of most pseudogenes in Brucella spp remains poorly understood, warranting further studies.To comprehensively analyze the function of the pseudogenes BMEA_B0173 in Brucella melitensis strain 63/9, a BMEA_B0173 in-frame deleted mutant strain was constructed. Then, the phenotypes of the mutant strain, such as growth characteristics and bacterial virulence, were assessed in mice infection models. Finally, iTRAQ analysis was performed to investigate the gene expression profile affected by the pseudogenes BMEA_B0173. In this study, we found that BMEA_B0173 deletion exhibited increased agglutination with M monospecific sera. In a mouse model of chronic infection, the BMEA_B0173 deletion strain displayed increased colonization in the spleen compared to the wild-type pathogen. The iTRAQ assay revealed that 252 proteins were differentially expressed between the BMEA_B0173 deletion and the wild-type strains. In addition, deletion of BMEA_B0173 significantly increased the expression of proteins involved in the denitrification pathway, iron metabolism, and several transcriptional regulators, which might cause increased virulence of the mutant strain. In conclusion, this study preliminary uncovered the function of the pseudogene BMEA_B0173 in Brucella melitensis 63/9 and provided novel insights for studying the pathogenesis of Brucella strains.

Research on Simultaneous localization and mapping Algorithm based on Lidar and IMU.

In recent years, the research of autonomous driving and mobile robot technology is a hot research direction. The ability of simultaneous positioning and mapping is an important prerequisite for unmanned systems. Lidar is widely used as the main sensor in SLAM (Simultaneous Localization and Mapping) technology because of its high precision and all-weather operation. The combination of Lidar and IMU (Inertial Measurement Unit) is an effective method to improve overall accuracy. In this paper, multi-line Lidar is used as the main data acquisition sensor, and the data provided by IMU is integrated to study robot positioning and environment modeling. On the one hand, this paper proposes an optimization method of tight coupling of lidar and IMU using factor mapping to optimize the mapping effect. Use the sliding window to limit the number of frames optimized in the factor graph. The edge method is used to ensure that the optimization accuracy is not reduced. The results show that the point plane matching mapping method based on factor graph optimization has a better mapping effect and smaller error. After using sliding window optimization, the speed is improved, which is an important basis for the realization of unmanned systems. On the other hand, on the basis of improving the method of optimizing the mapping using factor mapping, the scanning context loopback detection method is integrated to improve the mapping accuracy. Experiments show that the mapping accuracy is improved and the matching speed between two frames is reduced under loopback mapping. However, it does not affect real-time positioning and mapping, and can meet the requirements of real-time positioning and mapping in practical applications.

Study on the Modeling and Compensation Method of Pose Error Analysis for the Fracture Reduction Robot.

BACKGROUND: In the process of fracture reduction, there are some errors between the actual trajectory and the ideal trajectory due to mechanism errors, which would affect the smooth operation of fracture reduction. To this end, based on self-developed parallel mechanism fracture reduction robot (FRR), a novel method to reduce the pose errors of FRR is proposed. METHODS: Firstly, this paper analyzed the pose errors, and built the model of the robot pose errors. Secondly, mechanism errors of FRR were converted into drive bar parameter's errors, and the influence of each drive bar parameter on the robot pose error were analyzed. Thirdly, combining with Cauchy opposition-based learning and differential evolution algorithm (DE), an improved whale optimization algorithm (CRLWOA-DE) is proposed to compensate the end-effector's pose errors, which could improve the speed and accuracy of fracture reduction, respectively. RESULTS: The iterative accuracy of CRLWOA-DE is improved by 50.74%, and the optimization speed is improved by 22.62% compared with the whale optimization algorithm (WOA). Meanwhile, compared with particle swarm optimization (PSO) and ant colony optimization (ACO), CRLWOA-DE is proved to be more accurate. Furthermore, SimMechanics in the software of MATLAB was used to reconstruct the fracture reduction robot, and it was verified that the actual motion trajectory of the CRLWOA-DE optimized kinematic stage showed a significant reduction in error in both the x-axis and z-axis directions compared to the desired motion trajectory. CONCLUSIONS: This study revealed that the error compensation in FRR reset process had been realized, and the CRLWOA-DE method could be used for reducing the pose error of the fracture reduction robot, which has some significance for the bone fracture and deformity correction.

Impedance Iterative Learning Backstepping Control for Output-Constrained Multisection Continuum Arms Based on PMA.

BACKGROUND: Pneumatic muscle actuator (PMA) actuated multisection continuum arms are widely applied in various fields with high flexibility and bionic properties. Nonetheless, their kinematic modeling and control strategy proves to be extremely challenging tasks. METHODS: The relationship expression between the deformation parameters and the length of PMA with the geometric method is obtained under the assumption of piecewise constant curvature. Then, the kinematic model is established based on the improved D-H method. Considering the limitation of PMA telescopic length, an impedance iterative learning backstepping control strategy is investigated. For one thing, the impedance control is utilized to ensure that the ideal static balance force is maintained constant in the Cartesian space. For another, the iterative learning backstepping control is applied to guarantee that the desired trajectory of each PMA can be accurately tracked with the output-constrained requirement. Moreover, iterative learning control (ILC) is implemented to dynamically estimate the unknown model parameters and the precondition of zero initial error in ILC is released by the trajectory reconstruction. To further ensure the constraint requirement of the PMA tracking error, a log-type barrier Lyapunov function is employed in the backstepping control, whose convergence is demonstrated by the composite energy function. RESULTS: The tracking error of PMA converges to 0.004 m and does not exceed the time-varying constraint function through cosimulation. CONCLUSION: From the cosimulation results, the superiority and validity of the proposed theory are verified.

Hardness Prediction of Grind-Hardening Layer Based on Integrated Approach of Finite Element and Cellular Automata.

As an emerging composite processing technology, the grind-hardening process implements efficient removal on workpiece materials and surface strengthening by the effective utilization of grinding heat. The strengthening effect of grind-hardening on a workpiece surface is principally achieved by a hardened layer, which is chiefly composed of martensite. As a primary parameter to evaluate the strengthening effect, the hardness of the hardened layer mostly depends on the surface microstructure of the workpiece. On this basis, this paper integrated the finite element (FE) and cellular automata (CA) approach to explore the distribution and variation of the grinding temperature of the workpiece surface in a grind-hardening process. Moreover, the simulation of the transformation process of "initial microstructure-austenite-martensite" for the workpiece helps determine the martensite fraction and then predict the hardness of the hardened layer with different grinding parameters. Finally, the effectiveness of the hardness prediction is confirmed by the grind-hardening experiment. Both the theoretical analysis and experiment results show that the variation in the grinding temperature will cause the formation to a certain depth of a hardened layer on the workpiece surface in the grind-hardening process. Actually, the martensite fraction determines the hardness of the hardened layer. As the grinding depth and feeding speed increase, the martensite fraction grows, which results in an increase in its hardness value.

Targeting nasopharyngeal carcinoma by artesunate through inhibiting Akt/mTOR and inducing oxidative stress.

Drug repurposing has become an alternative therapeutic strategy for cancer treatment given the known pharmacokinetics and toxicity. The inhibitory effects of artesunate have been reported in various cancers. In this work, we investigated the effects of artesunate in nasopharyngeal carcinoma (NPC). We demonstrate that artesunate significantly inhibits proliferation via arresting NPC cells at G2/M phase. It also induces apoptosis through caspase-dependent and mitochondria-independent pathways in multiple NPC cell lines. The combination of artesunate and cisplatin is synergistic in targeting NPC cells in in vitro cellular culture system and in vivo xenograft tumor models. Artesunate inhibits phosphorylation of essential molecules involved in Akt/mTOR pathway in NPC cells, such as Akt, mTOR, and 4EBP1, and its inhibitory effects are partially abolished by overexpression of constitutively active Akt. In addition, artesunate also induces mitochondrial dysfunction and oxidative stress via inhibiting mitochondrial respiration, increasing levels of mitochondrial superoxide and cellular reactive oxygen species (ROS), leading to decreased ATP levels. Two ROS scavengers partially abolish the inhibitory effects of artesunate in NPC cells. These data suggest that both inhibition of Akt/mTOR pathway and induction of ROS are required for the action of artesunate in NPC cells. Our work demonstrates that artesunate is a potential candidate for NPC treatment. Our work also highlights the critical roles of Akt/mTOR pathway and mitochondrial function in NPC cells.

Photo-regulation of DNA function by azobenzene-tethered oligonucleotides.

Multiple azobenzene moieties were tethered to DNA on D-threoninol linker, and formation and dissociation of DNA duplex could be reversibly photo-regulated either by irradiating UV or visible light. With this photo-responsive DNA, RNase H reaction was also successfully photo-regulated.