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Purpose This paper aims to propose a novel model and calibration method to improve the absolute positioning accuracy of a robotic drilling system with secondary encoders and additional axis. Design/methodology/approach The enhanced rigid-flexible coupling model is developed by considering both kinematic parameters and link flexibility. The kinematic errors of the robot and the additional axis are considered with a model containing 27 parameters. The elastic deformation errors of the robot under self-weight of links and end-effector are estimated with a flexible link model. For calibration, an effective comprehensive calibration method is developed by further considering the coordinate systems parameters of the drilling system and using a two-step process constrained Levenberg–Marquardt identification method. Findings Experiments are performed on the robotic drilling system that contains a KUKA KR500 R2830 industrial robot and an additional lifting axis with a laser tracker. The results show that the maximum error and mean error are reduced to 0.311 and 0.136 mm, respectively, which verify the effectiveness of the model and the calibration method. Originality/value A novel enhanced rigid-flexible coupling model and a practical comprehensive calibration method are proposed and verified. The experiments results indicate that the absolute positioning accuracy of the system in a large workspace is greatly improved, which is conducive to the application of industrial robots in the field of aerospace assembly.

This article is concerned with set-membership global estimation for a networked system under unknown-but-bounded process and measurement noises. First, a group of local set-membership estimators is deployed to obtain the local ellipsoidal estimate of the true system state. Each estimator is capable of communicating with its neighbors within its communication range. Second, a global estimation approach is proposed which generates a trace-maximal ellipsoid within the intersection of all the local estimation sets with an aim to improve the difference of the local estimate at each time instant. Sufficient conditions for providing a global estimate under both complete and incomplete measurement transmissions are derived. Third, as an application, a modified distributed photovoltaic grid-connected generation system is provided to verify the effectiveness of the developed set-membership global estimation approach. Furthermore, an islanding fault detection scheme is derived based on the calculated global ellipsoidal estimate. Finally, simulation verification of the obtained theoretical results on the distributed generation system is presented.

This paper is concerned with the state estimation problem for an automatic guided vehicle (AGV). A novel set-membership filtering (SMF) scheme is presented to solve the state estimation problem in the trajectory tracking process of the AGV under the unknown-but-bounded (UBB) process and measurement noises. Different from some existing traditional filtering methods, such as Kalman filtering method and [Formula: see text] filtering method, the proposed SMF scheme is developed to provide state estimation sets rather than state estimation points for the system states to effectively deal with UBB noises and reduce the requirement of the sensor precision. Then, in order to obtain the state estimation ellipsoids containing the true states, a set-membership estimation algorithm is designed based on the AGV physical model and S-procedure technique. Finally, comparison examples are presented to illustrate the effectiveness of the proposed SMF scheme for an AGV state estimation problem in the present of the UBB noises.

This paper is concerned with the distributed ${H} _{\infty }$ -consensus filtering problem on attitude tracking over a radar filter network subject to switching topology and random packet dropouts occurring in the data transmission from both the Sun sensor and the filters. Since ground-based radars cannot directly measure the satellite attitude, a Sun sensor is deployed at the satellite side and its measurements are transmitted to radar filters through different network communication channels while suffering from random packet dropouts with different probabilities. In the radar filter network, each radar filter receives data not only from the Sun sensor but also from its local neighboring radar filters in accordance with a switching network topology. A delicate distributed ${H} _ {\infty}$ -consensus filtering algorithm, which incorporates the effects of switching network topology and random packet dropouts, is adopted to estimate attitude and attitude-rate. The algorithm guarantees ${H} _ {\infty }$ -consensus attenuation performance for the estimation deviations among radar filters, and the robustness against the switching network topology and packet dropouts for the radar filter network. The illustrative examples are given to verify the effectiveness of the proposed distributed ${H} _ {\infty}$ -consensus filtering algorithm.

The complexity of an optimization problem is determined by its decision and objective spaces. Over the past few decades, a large number of works have focused on the performance improvement of metaheuristic algorithms via the objective space, whereas studies related to the decision space have attracted little attentions. Moreover, metaheuristic algorithms may not obtain satisfactory results within an entire feasible region, even if sufficient computational resources are available. Therefore, reducing the search space (i.e., finding a trust region) may be an effective method to ensure that the convergence is sufficiently close to the global optimal region. However, inappropriate subspace size may also weaken the performance of algorithms except for ones with a sufficiently small search space. To alleviate aforementioned problems, a variable search space (VSS) strategy based on a sequential trust region determination approach is proposed in this paper. In the VSS, the entire optimization process is divided into two stages: the first stage is to use an optimization approach for sequentially finding the trust domain of each variable and then determine the best-matched subspace; the second stage is to employ the optimization method for searching an optimal/near-optimal solution within the found trust region. The effectiveness of the VSS is evaluated using two widely used test suites, that is, IEEE CEC2014 and BBOB2012. Experimental results indicate that improving the algorithm performance is an important method for tackling problems, but locating a trust region is also beneficial for metaheuristic algorithms to improve the solution precision, especially for complex optimization problems.

Aim: The aim of this study is to investigate the mechanism and interaction of microRNA-181a (miR-181a), toll-like receptor 4 (TLR4) and nuclear factor-kappa B (NF-κB) in gastric hypersensitivity in diabetic rats. Methods: Diabetes was induced by a single intraperitoneal injection of streptozotocin (STZ; 65 mg/kg) in female SD rats. Gastric balloon distension technique was used to measure diabetic gastric hypersensitivity. Gastric-specific (T7-T10) dorsal root ganglion (DRG) neurons were acutely dissociated to measure excitability with patch-clamp techniques. Western blotting was employed to measure the expressions of TLR4, TRAF6 and NF-κB subunit p65 in T7-T10 DRGs. The expressions of microRNAs in T7-T10 DRGs were measured with quantitative real-time PCR and fluorescence in situ hybridization. Dual-luciferase reporter gene assay was used to detect the targeting regulation of microRNAs on TLR4. Results: (1) Diabetic rats were more sensitive to graded gastric balloon distention at 2 and 4 weeks. (2) The expression of TLR4 was significantly up-regulated in T7-T10 DRGs of diabetic rats. Intrathecal injection of CLI-095 (TLR4-selective inhibitor) attenuated diabetic gastric hypersensitivity, and markedly reversed the hyper-excitability of gastric-specific DRG neurons. (3) The expressions of miR-181a and miR-7a were significantly decreased in diabetic rats. MiR-181a could directly regulate the expression of TLR4, while miR-7a couldn’t. (4) Intrathecal injection of miR-181a agomir down-regulated the expression of TLR4, reduced the hyper-excitability of gastric-specific neurons, and alleviated gastric hypersensitivity. (5) p65 and TLR4 were co-expressed in Dil-labeled DRG neurons. (6) Inhibition of p65 attenuated diabetic gastric hypersensitivity and hyper-excitability of gastric-specific DRG neurons. (7) The expression of TRAF6 was significantly up-regulated in diabetic rats. CLI-095 treatment also reduced the expression of TRAF6 and p65. Conclusion: The reduction of microRNA-181a in T7-T10 DRGs might up-regulate TLR4 expression. TLR4 activated NF-κB through MyD88-dependent signaling pathway, increased excitability of gastric-specific DRG neurons, and contributed to diabetic gastric hypersensitivity.

This paper is concerned with the security problem for a networked control system subject to deception attacks. An adversary is present to corrupt both the sensor-to-controller channel and the controller-to-actuator channel with deception signals when sensor and control data are transmitted via the network medium. We model the malicious deception signals as unknown-but-bounded signals in such a way that no priori knowledge of the attack signals is required. First, a delicate set-membership performance index is proposed for meeting the system security requirement. Second, a novel set-membership estimation method is developed to obtain the desired ellipsoidal estimation set which guarantees the enclosing of true state of the system at every instant of time. Such an ellipsoidal estimation set is then used for deriving the sufficient conditions such that the resulting closed-loop system is set-membership input-to-state-stable and achieves the prescribed security requirement. Finally, a target tracking system is given to demonstrate the effectiveness of the proposed method.

This paper investigates the quantized set-membership filtering (SMF) problem for network-based automatic guided vehicle (AGV) systems in the presence of unknown-but-bounded (UBB) process and measurement noises. Considering the bandwidth constraints of the communication networks, the measurement outputs of the AGV are quantized before transmitting to the remote filter. Two independent quantizers are designed to quantize each variable in the two-dimensional output vector separately. Then, an SMF scheme is presented to solve the problem of the remote state estimation for the AGV with UBB noises and the quantization error. Next, a recursive convex optimization algorithm is provided to obtain the state estimation ellipsoid sets for the considered AGV. Simulation results demonstrate the effectiveness of the proposed method.

A novel set-membership control strategy is investigated for a class of discrete time-varying systems with unknown-but-bounded noises. Different from some existing set-membership estimation based control methods, the proposed control strategy is designed by using state estimation sets instead of some specific estimation points. The controlled performance requirement is modelled as a new set-membership performance constraint which ensures that the controlled output meets the requirement at any time instant. First, the set-membership filtering method is used for obtaining the ellipsoidal state estimation set. Second, a set-membership controller is constructed by utilising the state estimation which is arbitrarily chosen from the corresponding estimation set. Accordingly, sufficient conditions are derived such that the controlled system is asymptotically stable and satisfies the proposed performance constraint in the presence of unknown-but-bounded noises at each time instant. Then, a constructive computational algorithm is provided to describe the proposed control strategy. Finally, illustrative simulation examples are presented to demonstrate the effectiveness of the proposed method.

Extensive epidemiological evidence suggests that nonalcoholic fatty liver disease (NAFLD) is the primary chronic liver disease worldwide. However, some studies have showed conflicting results on the effects of probiotics and synbiotics supplementation. Therefore, we conducted a systematic review and meta-analysis to investigate the effectiveness of the supplementation in subjects with NAFLD. We searched systematically PubMed, Cochrane, and Embase databases up to April 2018 and checked manually the bibliography of the original articles. The quality of the studies was evaluated using the Cochrane Risk of Bias Tool. This study analyzed 15 randomized, controlled trials involving 782 patients with NAFLD. Probiotics and synbiotics supplementation could significantly improve liver steatosis, alanine aminotransferase, aspartate aminotransferase, triglyceride, total cholesterol, high-density lipoprotein, low-density lipoprotein, homeostasis model assessment-insulin resistance, liver stiffness and tumor necrosis factor-alpha (all P

This paper is concerned with the strong γc-γcl H∞ stabilization problem for networked control systems (NCSs) subject to denial of service (DoS) attacks, which are common attack behaviors that affect the packet transmission of measurement or control signals. The purpose of the problem under consideration is to design a stable dynamic output feedback (DOF) controller (strong stabilizing controller) with the prescribed H∞ performance norm bound γc to tolerate multiple packet dropouts caused by DoS attacks, such that, the closed-loop system is mean-square stable and captures the H∞ disturbance attenuation norm bound γcl. Based on the Lyapunov functional and the stochastic control approach, some sufficient conditions with the form of matrix inequalities for the existence of the desired stable DOF controller are established. Then, by an orthogonal complement space technique, the controller gain is parameterized. Next, an iterative linear matrix inequality (LMI) algorithm is developed to obtain the controller gain. Finally, the usefulness of the proposed method is indicated by a numerical simulation example.

Background and Objective: Hepatocellular carcinoma (HCC) is a highly aggressive malignant tumor of the digestive system worldwide. Chronic hepatitis B virus (HBV) infection and aflatoxin exposure are predominant causes of HCC in China, whereas hepatitis C virus (HCV) infection and alcohol intake are likely the main risk factors in other countries. It is an unmet need to recognize the underlying molecular mechanisms of HCC in China.Methods: In this study, microarray datasets (GSE84005, GSE84402, GSE101685, and GSE115018) derived from Gene Expression Omnibus (GEO) database were analyzed to obtain the common differentially expressed genes (DEGs) by R software. Moreover, the gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by using Database for Annotation, Visualization and Integrated Discovery (DAVID). Furthermore, the protein-protein interaction (PPI) network was constructed, and hub genes were identified by the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape, respectively. The hub genes were verified using Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and Kaplan-Meier Plotter online databases were performed on the TCGA HCC dataset. Moreover, the Human Protein Atlas (HPA) database was used to verify candidate genes’ protein expression levels.Results: A total of 293 common DEGs were screened, including 103 up-regulated genes and 190 down-regulated genes. Moreover, GO analysis implied that common DEGs were mainly involved in the oxidation-reduction process, cytosol, and protein binding. KEGG pathway enrichment analysis presented that common DEGs were mainly enriched in metabolic pathways, complement and coagulation cascades, cell cycle, p53 signaling pathway, and tryptophan metabolism. In the PPI network, three subnetworks with high scores were detected using the Molecular Complex Detection (MCODE) plugin. The top 10 hub genes identified were CDK1, CCNB1, AURKA, CCNA2, KIF11, BUB1B, TOP2A, TPX2, HMMR and CDC45. The other public databases confirmed that high expression of the aforementioned genes related to poor overall survival among patients with HCC.Conclusion: This study primarily identified candidate genes and pathways involved in the underlying mechanisms of Chinese HCC, which is supposed to provide new targets for the diagnosis and treatment of HCC in China.

With the prosperity of artificial intelligence, research on machine learning becomes a hot issue globally. Generative Adversarial Networks expose the huge security risks of machine learning. After the creation, GAN has achieved good performance in image generation, automatic image coloring, and data enhancement. With the improvement of the ability to generate samples against the deep learning network, generating malicious samples against the target learning model to achieve the deceptive discriminator becomes an effective and harmful attacking method. At present, some efficient attack methods have been proposed for different types of learning networks and different types of sample data. This paper mainly discusses the vulnerability of deep learning networks and several attack methods based on adversarial samples.

In these years, with the development of search engines, it is more convenient for people to get information via the Internet. However, despite the benefit, search engines bring new challenges to network security. More and more hackers search for vulnerable websites and computers with the help of search engines and make large-scale attacks. This is quite a challenge to traditional cybersecurity concepts. Honeypot is a technology that is widely used in capturing and analyzing hackers' behaviors. By building virtual objectives with vulnerabilities, honeypots attract hackers and analyze the interaction process with hackers. But traditional honeypot can't attract hackers well and just wait for attackers. We design and implement a new Web honeypot detection system based on search engines, which can not only attract hackers but also can renew the content automotive to synchronize with the new attack technologies. This new kind of honeypot makes up for the shortcomings of traditional honeypots and has great advantages in finding zero-day attacks.

Drug-induced liver injury (DILI) is difficult in diagnose, criteria used now are mostly based on history review. We tried to evaluate the value of these criteria and histopathology features in DILI to perform a method diagnosing DILI more definitely.We enrolled 458 consecutive hospitalized DILI patients from January 1, 2012 to December 31, 2018, using Roussel-Uclaf Causality Assessment Method (RUCAM), MariaVictorino scale (MV), and Digestive Disease Week-Japan criterion (DDW-J) combined with refined pathological scoring system respectively to perform the evaluation.A total of 458 DILI patients were enrolled, the area under receiver operating characteristics (AUROC) of the 3 clinical diagnostic criteria were 0.730 (95% confidence interval [CI]: 0.667-0.793), 0.793 (95% CI: 0.740-0.847), and 0.764 (95% CI: 0.702-0.826) respectively. Three hundred two DILI patients' liver biopsies were included: steatosis in 204 cases (67.5%), cholestasis in 151 cases (50%), cell apoptosis in 139 cases (46%), eosinophil granulocyte infiltration in 131 cases (43.4%), central and/or portal phlebitis in 103 cases (34.1%), iron deposition in 90 cases (29.8%), and pigmented macrophages in 92 cases (30.5%). The AUROC of refined pathological scale combined with 3 criteria were 0.843 (95% CI: 0.747-0.914), 0.907 (95% CI: 0.822-0.960), and 0.881 (95% CI: 0.790-0.942) respectively. In hepatocellular type, the AUROCs were 0.894 (95% CI: 0.787-0.959), 0.960 (95% CI: 0.857-0.994), and 0.940 (95% CI: 0.847-0.985); in cholestatic type, the AUROCs were 0.750 (95% CI: 0.466-0.931), 0.500 (95% CI: 0.239-0.761), and 0.500 (95% CI: 0.239-0.761); in mixed type, the AUROCs were 0.786 (95% CI: 0.524-0.943), 0.869 (95% CI: 0.619-0.981), and 0.762 (95% CI: 0.498 to -0.930).Combined with pathological scale can significantly improve the accuracy of clinical diagnostic criteria, no matter in alone or combined condition, MV might be more accurate in diagnosing DILI from suspected patients.

Each type of problems, such as unimodal/multimodal, linear/non-linear, convex/non-convex, and symmetrical/asymmetrical, has its own characteristics. Although various differential evolution (DE) variants have been proposed, several studies indicate that a DE variant may only exhibit high solution efficiency in solving a specific type of problems, but may perform poorly in others. Therefore, an important decision is made to automatically select a suitable DE variant among several chosen algorithms for solving a particular type of problems during the evolutionary process. To achieve this objective, an auto-selection mechanism (ASM) is introduced in this study. In the ASM, rankings attained using Friedman's test are adopted to assess the performances of DE variants. A learning strategy is employed to update the choice probabilities of DE variants, and an additional selection probability is used to alleviate the greedy selection issue. Three sets of benchmark test functions proposed in BBOB2012, IEEE CEC2005, and IEEE CEC2014 are used to evaluate the effectiveness of the ASM. The performance of the proposed algorithm is also compared with that of nine state-of-the-art DE variants and four non-DE algorithms. Statistical analysis results demonstrate that the ASM is an efficient and effective method that can take full advantages of multiple algorithms. Furthermore, the ASM is utilized to estimate the parameters of a heavy oil thermal cracking model. Experimental results indicate that the proposed algorithm outperforms the other compared algorithms in this case.

This paper is concerned with the simultaneous stability of the multi-mode large-scale systems composed of the interaction subsystems. A novel distributed control network consisting of multiple network-based controllers with the partial information exchange is adopted to simultaneously stabilize the large-scale systems in multiple operation modes. In the distributed control network (DCN), a partial state information exchange approach is developed to save the real-time communication and computation resources. To compensate for the effects of dynamic couplings between interaction subsystems, the designed controllers use both the local states and the neighbors’ partial information with packet dropouts for local feedback design. Then, a series of Lyapunov functions are constructed to derive a matrix-inequality-based sufficient condition for the existence of the desired controllers. Based on an orthogonal complement technique, the gains of the controllers in DCN are parameterized. The iterative algorithm for the solution of simultaneous stabilization problem is also developed. Finally, a numerical example is performed to show the relevant feature of the proposed method.

The search efficiency of differential evolution (DE) algorithm is greatly impacted by its control parameters. Although many adaptation/self-adaptation techniques can automatically find suitable control parameters for the DE, most techniques are based on population information which may be misleading in solving complex optimization problems. Therefore, a self-adaptive DE (i.e., JADE) using two-phase parameter control scheme (TPC-JADE) is proposed to enhance the performance of DE in the current study. In the TPC-JADE, an adaptation technique is utilized to generate the control parameters in the early population evolution, and a well-known empirical guideline is used to update the control parameters in the later evolution stages. The TPC-JADE is compared with four state-of-the-art DE variants on two famous test suites (i.e., IEEE CEC2005 and IEEE CEC2015). Results indicate that the overall performance of the TPC-JADE is better than that of the other compared algorithms. In addition, the proposed algorithm is utilized to obtain optimal nutrient and inducer feeding for the Lee-Ramirez bioreactor. Experimental results show that the TPC-JADE can perform well on an actual dynamic optimization problem.

Yuezhi Zhao is famous for her theory of communication criticism. In the western-dominated international academic circles, she is the first critical scholar of communication in mainland China. In her first Chinese monograph, “Communication and Society: Political Economy and Culture Analysis”, put forward “look east, go south”: open up a new perspective of communication research in the post-crisis era. While deeply worried about the influence of depoliticization and neoliberalism on Chinese society, she also hoped that China would be different from the development mode of western capitalism with patriotism, and put forward the insight that “another world is possible”.

At present, the related research on the causes of “left-behind children” is very seldom. Most of literatures are simply summarized as two points: farmers need to survive, and it is the choice of the subject; the second is the inevitable process of China’s economic and social development and the objective necessity. In this paper, Bourdieu’s Practical Theory, such as Field, capital and habitus three elements, is analyzed and the behavior of workers is explained. It is considered that the phenomenon of left-behind children appearing in large scale in China is not only a problem of economic development, but also a special habitus of “working”, which is not simply the individual choice behavior of the parents of left-behind children.

Drilling and riveting are commonly used in aircraft panel assembly process. Due to the fixture positioning error and the deformation of workpiece, the real position and orientation of the workpiece as well as its 3D geometry at the drilling position varies from the nominal CAD model, which would cause an unfavorable impact on assembly quality. Therefore, surface normal measurement and adjustment at the drilling position is of great importance. In this paper, a fast and effective non-contact measurement method for normal vector and height of moderately curved surfaces is accomplished by four laser displacement sensors, and a dedicated NC machine tool is also developed for normal adjustment. Firstly, a novel sensor calibration method based on laser tracker is introduced, which can acquire the sensors’ position and orientation in Tool Coordinate System (TCS) at the same time. The normal vector at hole position is calculated by cross product of any two non-parallel vectors constructed by the four laser projection points on the panel surface. Secondly, the kinematic model of the machine tool is established to calculate the adjustment of each axis of the machine tool with the Homogeneous Transformation Matrix (HTM). Besides, an innovative method to identify the distance of two rotary centers based on two laser interferometers is proposed. Finally, a series of experiments are conducted to validate the feasibility of the proposed method. The results show that the angle deviation can be reduced to less than 0.5° after adjustment, while the accuracy of the surface height is ±0.04 mm.

Press working causes structural deformation of the machine tool, especially the machine tool with large-span gantry or double columns used for the large-sized workpiece. The structural deformation makes the press tool out of accurate positioning, which leads to dimension deviation of the pressed workpiece. Even more, for thin-walled panel riveting, the structural deformation of the riveting machine will cause local deformations of the panel at rivet joints; this accumulated deformation will make the panel out of tolerance. An online deformation measurement and compensation method is developed for adaptive riveting with high accuracy and efficiency in this paper. During the process of servo driving riveting combined with force measurement, the force–displacement data points can be online obtained, and the recognized feature data points by a robust algorithm can represent the critical points during rivet deformation. Combined with the analytical springback of the rivet joint, the deformation of the machine tool can be accurately solved and compensated to the displacement of press tool for high­precision riveting. Simultaneously, with this innovative measurement method, the online quantity inspection for rivet joints can be realized synchronously. Also, a contrast experiment is conducted to validate the effectiveness of the online adaptive deformation compensation based on force–displacement data analysis. The results demonstrate the feasibility of the proposed method in riveting error compensation and riveting quantity inspection.

A novel approach to inverse spectral theory for Schr&oumldinger Equation operators on a half-line was first introduced by Barry Simon and actively studied in recent literatures. The remarkable discovery is a new object A-function and intergo-differential Equation (called A-Equation) it satisfies. Inverse problem of reconstructing potential is then directly connected to finding solutions of A-Equation. In this work, we present a large class of exact solutions to A-Equation and reveal the connection to a class of arbitrarily large systems of nonlinear ordinary differential Equations. This non-linear system turns out to be C-integrable in the sense of F. Calogero. Integration scheme is proposed and the approach is illustrated in several examples.

The estrogen levels in the pre and post menstrual phases interact with brain-derived neurotrophic factor in a complex manner, which influences the overall state of the body. To study the role of oestradiol and brain-derived neurotrophic factor in modulating obesity related type 2 diabetes and the interactions between two factors, we enrolled 15 diabetic premenopausal women and 15 diabetic postmenopausal women respectively, the same number of healthy pre and postmenopausal women were recruited as two control groups. The fasting blood glucose, insulin, lipids, estrogen, and brain-derived neurotrophic factor levels were measured through clinical tests. Additionally, we set up obese female mouse model to mimic human trial stated above, to verify the relationship between estrogen and brain-derived neurotrophic factor. Our findings revealed that there is a moderately positive correlation between brain-derived neurotrophic factor and oestradiol in females, and decreased brain-derived neurotrophic factor may worsen impaired insulin function. The results further confirmed that high fat diet-fed mice which exhibited impaired glucose tolerance, showed lower levels of oestradiol and decreased expression of brain-derived neurotrophic factor mRNA in the ventromedial hypothalamus. The level of brain-derived neurotrophic factor reduced on condition that the level of oestradiol is sufficiently low, such as women in postmenopausal period, which aggravates diabetes through feeding-related pathways. Increasing the level of brain-derived neurotrophic factor may help to alleviate the progression of the disease in postmenopausal women with diabetes.

Background Drug-induced liver injury(DILI) is difficult in diagnose, criteria used now are mostly based on history review. We tried to evaluate the value of these criteria and histopathology features in DILI to perform a method diagnosing DILI more definitely.Methods We enrolled 458 consecutive hospitalized DILI patients from 1st January 2012 to 31st December 2018, using Roussel-Uclaf Causality Assessment Method(RUCAM), Maria&Victorino scale (M&V) and Digestive Disease Week-Japan criterion(DDW-J) to perform the evaluation. A refined pathological scale was calculated and combined with those criteria using logistic regression analysis. Area under receiver operating characteristics(AUROC) were used to estimate diagnostic accuracy.Results The AUROC of the three clinical diagnostic criteria were 0.730 (95%CI:0.667-0.793), 0.793(95%CI:0.740-0.847) and 0.764(95%CI:0.702-0.826) respectively. The AUROC of the refined pathological scale combined with the three criteria were 0.843(95%CI:0.747-0.914), 0.907(95%CI:0.822-0.960) and 0.881(95%CI:0.790-0.942) respectively. In hepatocellular type, the AUROCs were 0.894(95%CI:0.787-0.959), 0.960(95%CI:0.857-0.994) and 0.940(95%CI:0.847-0.985); In cholestatic type, the AUROCs were 0.750(95%CI:0.466-0.931), 0.500(95%CI:0.239-0.761) and 0.500(95%CI:0.239-0.761); In mixed type, the AUROCs were 0.786(95%CI: 0.524-0.943), 0.869(95%CI:0.619-0.981) and 0.762(95%CI: 0.498 -0.930).Conclusion Combined with pathological scale can significantly improve the accuracy of clinical diagnostic criteria, no matter in alone or combined condition, M&V might be more accurate in diagnosing DILI from suspected patients.