Trifolirhizin relieves renal injury in a diabetic nephropathy model by inducing autophagy and inhibiting oxidative stress through the regulation of PI3K/AKT/mTOR pathway

Purpose: To evaluate the effects of trifolirhizin on diabetic nephropathy (DN), and the mechanism of action. Methods: Male db/db mice (8 weeks, n = 24) and age-matched control mice (n = 6) were obtained. The mice were further divided into four groups and administered increasing doses of trifolirhizin (0, 12.5, 25 and 50 mg/kg). Histological analysis of renal tissues were performed by H & E staining. Blood urea nitrogen (BUN) and creatinine were determined using enzyme-linked immunosorbent assay (ELISA). Immunoblot and TUNEL assay were performed to investigate the effect of trifolirhizin on autophagy and apoptosis, while ELISA and dihydroethidium (DHE) staining were conducted to evaluate reactive oxygen species (ROS), malondialdehyde (MDA) and superoxide dismutase (SOD) levels. The effect of trifolirhizin on PI3K/AKT/mTOR pathway was determined using Immunoblot assays. Results: Trifolirhizin alleviated renal injury in diabetic mice, and also activate autophagy and inhibited apoptosis in the renal tissues in diabetic mice (p < 0.001). In addition, trifolirhizin inhibited the oxidative stress response in the renal tissue in diabetic mice (p < 0.001). Trifolirhizin further inhibited PI3K/AKT/mTOR pathway and therefore relieved renal injury in the diabetic nephropathy model (p < 0.001). Conclusion: Trifolirhizin alleviates renal injury in diabetic mice, activates autophagy, and inhibits apoptosis in renal tissue of diabetic mice. Therefore, trifolirhizin is a promising a promising drug for the treatment of DN

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Dynamics modeling of a mobile manipulator for wheel slip avoidance

For a mobile manipulator consisting of a 4-wheel skid-steering mobile robot with a 7-DOF manipulator, in order to avoid wheel slip caused by unstructured road conditions, the concept of active control is introduced in this paper. By properly changing the configuration of the 7-DOF arm, the vertical forces of the wheels on the road are adjusted. The wheels which are close to slipping should have a larger force applied so as to be able to avoid the slip. In this paper, an estimate model is built to monitor the slipping condition of the wheels. Additionally, the relationship between the arm's configuration and the vertical force applied on the wheels is also modeled. Finally, those models are verified by experiments on a mobile manipulator. © 2011 IEEE.Link_to_subscribed_fulltex

Online identification of quality of teleoperator (QoT) for performance improvement of telerobotic operations

In teleoperation studies, most researchers have been researching on the stability and telepresence. Few of them have studied the influence of the operational status of the teleoperator on the telerobotic systems. As a matter of fact, improper and incorrect operations of the teleoperator may decrease the teleoperation efficiency and even result in some serious safety problems even if the stability and telepresence are both guaranteed. Thus, this paper investigates a method to online identify the quality of the teleoperator and then integrate it into the planning and control of the telerobotic system. The method can help improve the performance of the system including efficiency and safety. It is also implemented on a mobile manipulator and the experimental results illustrate the effectiveness of the designed method. © 2012 IEEE.Link_to_subscribed_fulltex

Image based approach to obstacle avoidance in mobile manipulators

Due to many advantages, the mobile manipulators have been used in many areas. However, it is challenging to operate such system in teleoperation because of the too many controllable degrees for the teleoperator. Additionally, because of the unstructured working environment, it is necessary for the mobile manipulator to posses the ability of solving this problem in real time. The existing methods cannot meet these requirements, so this paper proposes a method based on images for a teleoperated mobile manipulator to take advantage of the redundancy to avoid the obstacles. With this method, the teleoperator can concentrate on the end-effector operation regardless of obstacle avoidance of the the arm links. The feasibility and effectiveness of the proposed method are well demonstrated by simulations. © 2011 IEEE.Link_to_subscribed_fulltex

Telerobotic systems adaptive to the quality of its operators

Telerobotic systems plays important role in hazardous environment applications. In the past, the design of controllers for telerobotic systems and the performance of the operators have been treated as separated issues. In the controller design, most of researches focus on the stability or transparency of the telerobotic systems. For the aspect of operators, researches have been concentrated on evaluation of the performance of the operators. However, the efficiency and safety of a telerobotic system directly depend on the real-time integration and interactions of the controllers and operators. This paper proposes a concept named Quality of Teleoperator (QoT) to represent the confidence and quality of the decisions and commands generated by a teleoperator. The value of QoT is generated by a set of quantities describing the mental statuses of the teleoperator, which can be measured in real-time based on the operator's electroencephalography (EEG) signals. The controller of the telerobotic system will adjust its parameters based on the QoT in real-time to adapt the confidence and quality of the operator in order to achieve an optimal system performance. Based on QoT, an adaptation scheme for the control system is designed to enhance the efficiency and safety of the telerobotic system. In the paper, the analysis and design methods for QoT based controllers will be discussed. The theoretical analysis and experimental results have demonstrated the effectiveness of the proposed methods.Link_to_subscribed_fulltex

Controlling telerobotic operations adaptive to quality of teleoperator and task dexterity

Telerobotic systems have been researched for decades due to their extensive applications in many civilian and military areas. Most research mainly focused on either the stability or telepresence of the telerobotic systems. Few studies have investigated the effects of the confidence of the teleoperator on the performance of the teleoperation. The confidence of the teleoperator is of significant importance to the efficiency and safety of the telerobotic systems. This paper proposes a concept named quality of teleoperator (QoT) to represent the confidence of the decisions and commands generated by the teleoperator. The value of QoT is computed based on a set of mental states of the teleoperator. Based on the QoT, a control adjustment mechanism is designed to enhance the efficiency and safety of the telerobotic systems. Experiments were implemented on a manipulator to demonstrate the effectiveness of the proposed method. © 2011 IEEE.Link_to_subscribed_fulltex

Link Prediction Based on Feature Mapping and Bi-Directional Convolution

A considerable amount of research on link prediction has recently been driven by missing relationships between knowledge graph entities and the problem of the incompleteness of knowledge graphs. Some recent studies have shown that convolutional neural networks based on knowledge embeddings are highly expressive and have good performance in link prediction. However, we found that the convolutional neural network (CNN)-based models do not handle the link between relations and entities well. For this reason, this paper proposes a link prediction model (LPM) based on feature mapping and bi-directional convolution. For the modeling of the task, an encoding layer–mapping layer–decoding layer structure is used. Among these layers, the encoding layer adopts a graph attention network to encode multi-hop triad information and obtains richer encoding of entities and relationships. The mapping layer can realize the mapping transformation between entities and relations and project the entity encoding in the space of relation encoding to capture the subtle connection between entities and relations. The decoding layer adopts bidirectional convolution to merge and decode the triples in a sequential inverse order, which makes the decoding layer model more advantageous in prediction. In addition, the decoding layer also adopts the r-drop training method to effectively reduce the distribution error generated by training between models and enhance the robustness of the model. Our experiments demonstrated the effectiveness of mapping relations, bidirectional convolution, and r-drop, and the accuracy of the proposed model showed significant improvements for each evaluation metric on two datasets, WN18RR and FB15k-237