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Abstract Background While xanthine oxidase inhibitors target uric acid production, renal urate underexcretion is the predominant subtypes in gout. This study was to compare treatment response to the XOI febuxostat in a gout cohort according to clinical subtypes of hyperuricemia. Methods A prospective cohort study was conducted to compare the efficacy and safety of febuxostat (initially 20 mg daily, escalating to 40 mg daily if not at target) in 644 gout patients with the three major clinical subtypes for 12 weeks. Hyperuricemia was defined as the renal overload subtype, the renal underexcretion subtype, or the combined subtype based on UUE > or ≤ 600 mg/d/1.73 m2 and FEUA

Abstract Background Low urine pH, which may be mediated by metabolic syndrome (MetS), is common in gout. Tart cherries are shown to improve MetS symptoms and possess anti-inflammatory properties. However, the efficacy of tart cherry supplements on urine pH has yet to be studied. Objectives This study aimed to investigate the efficacy and safety of tart cherry supplementary citrate (TaCCi) mixture on urine pH, serum urate (sUA), C-reactive protein (CRP), and gout flares in gout patients initiating urate-lowering therapy (ULT), in comparison to citrate mixture and sodium bicarbonate. Methods A prospective, randomized (1:1:1), open-label, parallel-controlled trial was conducted among 282 men with gout and fasting urine pH ≤ 6, who were initiating ULT with febuxostat (initially 20 mg daily, escalating to 40 mg daily if serum urate ≥ 360 μmol/L). Participants were randomized to groups taking either sodium bicarbonate, citrate mixture, or TaCCi mixture. All participants were followed every 4 weeks until week 12. Urine pH and sUA were co-primary outcomes, with various biochemical and clinical secondary endpoints. Results Urine pH increased to a similar extent in all three groups. SUA levels declined in all three groups as well, with no significant differences observed between the groups. At week 12, the TaCCi mixture group exhibited a greater reduction in the urine albumin/creatinine ratio (UACR) compared to the other two groups (p

Access to clean and safe drinking water is essential. This study aimed to evaluate the effect of a kind of small molecular natural mineral water, C-cell mineral water on hyperuricemia male mice metabolism condition. A 13-week drinking water intervention study was conducted in Uox-knockout mice (KO). The hepatic metabolite profiling and related genes expression were detected by UPLC-TOF-MS and transcriptomic, and the gut microbiota of KO mice was determined by metagenomics sequencing. Results showed that the body weight of mice fed with C-cell water was remarkably lower than that of control mice on D 77 and D 91. Hepatic metabolite profiling revealed a shift in the pathway of glycine, serine and threonine metabolism, pantothenate and CoA biosynthesis, and biosynthesis of cofactors in KO mice fed with C-cell mineral water. Increased energy metabolism levels were related to increased hepatic expression of genes responsible for coenzyme metabolism and lipid metabolism. Gut microbiota was characterized by increasing activity of beneficial bacteria Blautia, and reducing activity of pathobiont bacteria Parasutterella. These genera have been reported to be associated with obesity. Small molecular mineral-rich natural water ingestion regulates metabolism and gut microbiota, protecting against obesity induced by hyperuricemia through mediating a microbiota-liver axis.

Cadmium (Cd) exposure has been associated with the development of enterohepatic circulation disorders and hyperuricemia, but the possible contribution of chronic low-dose Cd exposure to disease progression is still need to be explored. A mouse model of wild-type mice (WT) and Uox-knockout mice (Uox-KO) to find out the toxic effects of chronic low-dose Cd exposure on liver purine metabolism by liquid chromatography-mass spectrometry (LC-MS) platform and associated intestinal flora. High throughput omics analysis including metabolomics and transcriptomics showed that Cd exposure can cause disruption of purine metabolism and energy metabolism. Cd changes several metabolites associated with purine metabolism (xanthine, hypoxanthine, adenosine, uridine, inosine) and related genes, which are associated with elevated urate levels. Microbiome analysis showed that Cd exposure altered the disturbance of homeostasis in the gut. Uox-KO mice were more susceptible to Cd than WT mice. Our findings extend the understanding of potential toxicological interactions between liver and gut microbiota and shed light on the progression of metabolic diseases caused by Cd exposure.

Abstract In the field of intelligent manufacturing, robot grasping and sorting is important content. However, there are some disadvantages in the traditional single-view-based manipulator grasping methods by using a 2D camera, where the efficiency and the accuracy of grasping are both low when facing the scene of stacking and occlusion for the reason that there is information missing by single-view 2D camera-based methods while acquiring scene information, and the methods of grasping only can’t change the difficult-to-grasp scene which is stack and occluded. Regarding the issue above, a pushing-grasping collaborative method based on the deep Q-network in dual viewpoints is proposed in this paper. This method in this paper adopts an improved deep Q-network algorithm, with an RGB-D camera to obtain the information of objects’ RGB images and point clouds from two viewpoints, which solved the problem of lack of information missing. What’s more, it combines the pushing and grasping actions with the deep Q-network, which make it have the ability of active exploration, so that the trained manipulator can make the scenes less stacking and occlusion, and with the help of that, it can perform well in more complicated grasping scenes. In addition, we improved the reward function of the deep Q-network and propose the piecewise reward function to speed up the convergence of the deep Q-network. We trained different models and tried different methods in the V-REP simulation environment, and it drew a conclusion that the method proposed in this paper converges quickly and the success rate of grasping objects in unstructured scenes raises up to 83.5%. Besides, it shows the generalization ability and well performance when novel objects appear in the scenes that the manipulator has never grasped before.

Abstract Background Patients with gout frequently have low urinary pH, which is associated with the nephrolithiasis. However, the specific distribution of urinary pH and potential relationship of acidic urine pH to broader manifestations of kidney disease in gout are still poorly understood. Methods A 2016–2020 population-based cross-sectional study was conducted among 3565 gout patients in the dedicated gout clinic of the Affiliated Hospital of Qingdao University to investigate the association between low urinary pH and kidney disease. We studied patients that we defined to have “primary gout”, based on the absence of > stage 2 CKD. All subjects underwent 14 days of medication washout and 3-day standardized metabolic diet. We obtained general medical information, blood and urine biochemistries, and renal ultrasound examination on the day of the visit. The primary readouts were urine pH, eGFR, nephrolithiasis, renal cysts, microhematuria, and proteinuria. Patients were assigned into 5 subgroups (urine pH ≤5.0, 5.0 6.9), aligning with the clinical significance of urine pH. Results Overall, the median urine pH and eGFR of all patients was 5.63 (IQR 5.37~6.09), and 98.32 (IQR 86.03~110.6), with acidic urine in 46.5% of patients. The prevalence of nephrolithiasis, microhematuria, and proteinuria were 16.9%, 49.5%, and 6.9%, respectively. By univariate analysis, eGFR was significantly associated with age, sex, duration of gout, tophus, body mass index, systolic blood pressure, diastolic blood pressure, fasting blood glucose, total cholesterol, serum utare, hypertension, diabetes, and urine pH. On multivariable analysis, eGFR was associated with age, sex, diastolic blood pressure, serum uric acid, hypertension, diabetes, and urine pH. Acidic urine pH, especially urine pH < 5.0, was significantly associated with the prevalence of kidney disease, including > stage 1 CKD, nephrolithiasis, kidney cyst, and microhematuria. Patients with 6.2 ≤ urine pH ≤ 6.9 and SU ≤ 480 μmol/L had the highest eGFR with the lowest prevalence of nephrolithiasis, microhematuria, and proteinuria. Conclusions Approximately half of gout subjects had acidic urine pH. Urine pH < 5.0 was associated with significantly increased nephrolithiasis, renal cyst, microhematuria, and proteinuria. The results support prospective clinical investigation of urinary alkalinization in selected gout patients with acidic urine pH.

Long-range (LoRa) communication has attracted much attention recently due to its utility for many Internet of Things applications. However, one of the key problems of LoRa technology is that it is vulnerable to noise/interference due to the use of only up-chirp signals during modulation. In this paper, to solve this problem, unlike the conventional LoRa modulation scheme, we propose a modulation scheme for LoRa communication based on joint up- and down-chirps. A fast Fourier transform (FFT)-based demodulation scheme is devised to detect modulated symbols. To further improve the demodulation performance, a hybrid demodulation scheme, comprised of FFT- and correlation-based demodulation, is also proposed. The performance of the proposed scheme is evaluated through extensive simulation results. Compared to the conventional LoRa modulation scheme, we show that the proposed scheme exhibits over 3 dB performance gain at a bit error rate of 10−4.

Intelligent devices, which significantly improve the quality of life and work efficiency, are now widely integrated into people’s daily lives and work. A precise understanding and analysis of human motion is essential for achieving harmonious coexistence and efficient interaction between intelligent devices and humans. However, existing human motion prediction methods often fail to fully exploit the dynamic spatial correlations and temporal dependencies inherent in motion sequence data, which leads to unsatisfactory prediction results. To address this issue, we proposed a novel human motion prediction method that utilizes dual-attention and multi-granularity temporal convolutional networks (DA-MgTCNs). Firstly, we designed a unique dual-attention (DA) model that combines joint attention and channel attention to extract spatial features from both joint and 3D coordinate dimensions. Next, we designed a multi-granularity temporal convolutional networks (MgTCNs) model with varying receptive fields to flexibly capture complex temporal dependencies. Finally, the experimental results from two benchmark datasets, Human3.6M and CMU-Mocap, demonstrated that our proposed method significantly outperformed other methods in both short-term and long-term prediction, thereby verifying the effectiveness of our algorithm.

Abstract Background The Reporting Items for Practice Guidelines in Healthcare (RIGHT) checklist was used to assess the reporting quality of 2009–2019 clinical practice guidelines (CPGs) regarding gout and hyperuricemia, aimed to improve the reporting quality of future guidelines. Methods We searched PubMed, the Chinese Biomedical Literature database, the Wanfang Database, and the China National Knowledge Infrastructure from January 2009 to June 2019 for guidelines regarding gout and hyperuricemia. We also searched the websites of guideline development organizations (the Guidelines International Network, the National Institute for Health and Clinical Excellence, the American College of Rheumatology, and the European League Against Rheumatism (EULAR)). Furthermore, supplementary guidelines reported in included articles were systematically searched, as well as Google Scholar. Results Seventeen guidelines were included, of which one was in Chinese and 16 were in English. The mean reporting rate of the 35 items specified was 14.9 (42.5%); only five CPGs (29.4%) had a reporting rate >50%. Of the 35 items, three were very frequently reported. The reporting proportion of the seven domains (basic information, background, evidence, recommendations, review and quality assurance, funding and declaration and management of interests, and other information) were 64.7%, 36.8%, 50.6%, 42.9%, 8.82%, 33.8%, and 31.4%, respectively. Conclusion The reporting quality of the present guidelines for gout and hyperuricemia is relatively poor. We suggest that the RIGHT reporting checklist should be used by CPG developers to ensure higher reporting quality of future guidelines.

Unmanned aerial vehicles (UAV) equipped with a manipulator offer an additional flexibility and smart way to grasp the desired objects from inaccessible locations where the access of ground vehicles (GV) are not possible. In this research, we design an adaptive control based regulation, pole-placement and tracking (RST) control scheme for controlling the nonlinear behavior of an under-actuated quad rotor aerial vehicle. The overall performance of the system dealt by MIT rules. The aerial vehicle is equipped with a camera and a gripper that helps us to locate the wanted object from inaccessible location. The model of quad rotor UAV has six degrees of freedom (6-DOF) and the equipped gripper is about (2-DOF). For a successful flight operation UAV requires a reliable controller to stabilize the aerodynamic effects, disturbances that produced by the gripper. Due to aforementioned issue, design an adaptive RST controller, to control the dynamic behavior of the highly nonlinear complex system. Moreover, the effectiveness of the designed controller proven by applying computer-based simulation and it will verify experimentally. Lastly, it observes that the designed controller shows better robustness and good steady state performance to accomplish the given task.

Recently, unmanned aerial vehicles (UAV) are widely used in many fields due to the low cost and high flexibility. One of the most popular applications of UAV is vehicle detection in aerial images which plays an important role in traffic surveillance and urban planning. Although, many deep learning based detectors have achieved state-of-the-art (SOTA) performance in natural images, the significant variation in object scales caused by the altitude change of the UAV platform brings great challenges to these detectors for precise localization of vehicles in aerial images. To improve the detection performance for vehicles with different scales, we propose a novel detection algorithm which consists of three stages. In the first stage, to reduce the distortion of vehicles during image resizing and keep more information of aerial images, we utilize an image cropping strategy to divide the image into two patches. In the second stage, we combine the original image and two patches into a batch and detect vehicles with a Convolutional Neural Network (CNN). For feature representation in our detector, we propose Scale-specific Prediction to strengthen the multi-scale features of vehicles with context information. In the final stage, to fuse detections and suppress false alarms, we propose an Outlier-Aware Non-Maximum Suppression. Extensive experiments are conducted to demonstrate the superiority of the proposed algorithm by comparison with other SOTA solutions.

IntroductionAchieving a goal of serum urate levels in patients with gout is an important way to prevent gout and its complications while it remains difficult with a low targeting rate worldwidely. Currently, hyperuricemia classification has not been widely applied to the management of gout owing to insufficient clinical evidences. This study aimed to evaluate the effectiveness of achieving target urate based on hyperuricemia classification in Chinese patients with gout.MethodsIn this prospective study, patients with gout receiving urate lowering therapy with benzbromarone were assigned to two groups, a renal underexcretion and an unclassified type. The primary endpoint was the proportion of patients achieving the serum urate target (

ObjectiveTo clarify the relationship between serum urate (SU) decrease and visceral fat area (VFA) reduction in patients with gout.MethodsWe retrospectively analyzed 237 male gout patients who had two sets of body composition and metabolic measurements within 6 months. Subjects included had all been treated with urate-lowering therapy (ULT) (febuxostat 20–80 mg/day or benzbromarone 25–50 mg/day, validated by the medical record). All patients were from the specialty gout clinic of The Affiliated Hospital of Qingdao University. The multiple linear regression model evaluated the relationship between change in SU [ΔSU, (baseline SU) – (final visit SU)] and change in VFA [ΔVFA, (baseline VFA) – (final visit VFA)].ResultsULT resulted in a mean (standard deviation) decrease in SU level (464.22 ± 110.21 μmol/L at baseline, 360.93 ± 91.66 μmol/L at the final visit, p

Abstract Background Serum uric acid (SUA), hyperuricemia (HUA) and gout are complex traits with relatively high heritability. This study aims to identify whether a candidate gene, SLC28A2, exerts susceptibility for SUA fluctuation and incidence of HUA and gout in the Han Chinese population. Results Three sample sets of 1376 gout patients, 1290 long-term HUA subjects (no gout attack) and 1349 normouricemic controls were recruited for this study. Eight polymorphisms in the SLC28A2 gene were genotyped using the ligase detection reaction-polymerase chain reaction (LDR-PCR) technology. Rs16941238 showed the most significant associations with SUA level (minor allele “A”, BETA = − 13.84 μmol/L, P = 0.0041, Pperm = 0.0042) and HUA (OR = 0.7734, P = 0.0033, Pperm = 0.0020), but not with gout (OR = 0.8801, P = 0.1315, Pperm = 0.1491). Rs2271437 was significantly associated with gout (minor allele “G”, OR = 1.387, P = 0.0277, Pperm = 0.0288), and was further confirmed in the meta-analysis with the previously published gout GWAS dataset (OR = 1.3221, P = 0.0089). Each variant basically conferred consistent OR direction on gout and HUA, compared with the normouricemic control. Conclusions Our findings support the associations of the SLC28A2 gene with the SUA level, the HUA phenotype and gout in Han Chinese.

The hydrophobic epicuticle wax on fresh leaves of tea tree (Camellia sinensis (L.) 0. Kuntze) leads to the loss of pesticide droplets, reducing efficacy. In this study, four adjuvants were selected to improve the diffusion and adhesion of bifenthrin droplets on the surface of tea leaves at different growth stages. The coupling effect of bifenthrin and adjuvants on the time-dependent and concentration-dependent wettability of droplets was investigated, and the difference in the wettability between bud and leaf was explained by observing the surface morphology. It was found that adjuvants effectively reduced the contact angle of droplets and accelerated the diffusion speed, and the above phenomenon became obvious with the increase in the adjuvant concentration. The wetting promotion of young leaves was more significant due to the reduced epicuticle wax and the greater roughness compared with fresh buds. The surface tension of the pesticide mixture was negatively correlated with the cosine of contact angle after adding the four adjuvants regardless of the growth stage of tea leaves. The contact angle of 0.2% Silwet L-77 decreased to 0° within 10 s, but the extreme wettability led to the decrease in adhesion with the increase in concentration. However, the wettability and adhesion on the surface of tea leaves were simultaneously suitable with more than 0.1% nonionic surfactant. The minimum concentration of the optimal adjuvant proposed in this study can provide an experimental basis and guide more efficient plant protection in tea gardens.

Currently, simultaneous localization and mapping (SLAM) is one of the main research topics in the robotics field. Visual-inertia SLAM, which consists of a camera and an inertial measurement unit (IMU), can significantly improve robustness and enable scale weak-visibility, whereas monocular visual SLAM is scale-invisible. For ground mobile robots, the introduction of a wheel speed sensor can solve the scale weak-visibility problem and improve robustness under abnormal conditions. In this paper, a multi-sensor fusion SLAM algorithm using monocular vision, inertia, and wheel speed measurements is proposed. The sensor measurements are combined in a tightly coupled manner, and a nonlinear optimization method is used to maximize the posterior probability to solve the optimal state estimation. Loop detection and back-end optimization are added to help reduce or even eliminate the cumulative error of the estimated poses, thus ensuring global consistency of the trajectory and map. The outstanding contribution of this paper is that the wheel odometer pre-integration algorithm, which combines the chassis speed and IMU angular speed, can avoid the repeated integration caused by linearization point changes during iterative optimization; state initialization based on the wheel odometer and IMU enables a quick and reliable calculation of the initial state values required by the state estimator in both stationary and moving states. Comparative experiments were conducted in room-scale scenes, building scale scenes, and visual loss scenarios. The results showed that the proposed algorithm is highly accurate—2.2 m of cumulative error after moving 812 m (0.28%, loopback optimization disabled)—robust, and has an effective localization capability even in the event of sensor loss, including visual loss. The accuracy and robustness of the proposed method are superior to those of monocular visual inertia SLAM and traditional wheel odometers.

Abstract Gout is a chronic disease resulting from elevated serum urate (SU). Previous genome-wide association studies (GWAS) have identified dozens of susceptibility loci for SU/gout, but few have been conducted for Chinese descent. Here, we try to extensively investigate whether these loci contribute to gout risk in Han Chinese. A total of 2255 variants in linkage disequilibrium (LD) with GWAS identified SU/gout associated variants were analyzed in a Han Chinese cohort of 1255 gout patients and 1848 controls. Cumulative genetic risk score analysis was performed to assess the cumulative effect of multiple “risk” variants on gout incidence. 23 variants (41%) of LD pruned variants set (n = 56) showed nominal association with gout in our sample (p

Abstract Background To identify potential causative mutations in SLC2A9 and SLC22A12 that lead to hypouricemia or hyperuricemia (HUA). Methods Targeted resequencing of whole exon regions of SLC2A9 and SLC22A12 was performed in three cohorts of 31 hypouricemia, 288 HUA and 280 normal controls. Results A total of 84 high‐quality variants were identified in these three cohorts. Eighteen variants were nonsynonymous or in splicing region, and then included in the following association analysis. For common variants, no significant effects on hypouricemia or HUA were identified. For rare variants, six single nucleotide variations (SNVs) p.T21I and p.G13D in SLC2A9, p.W50fs, p.Q382L, p.V547L and p.E458K in SLC22A12, occurred in totally six hypouricemia subjects and were absent in HUA and normal controls. Allelic and genotypic frequency distributions of the six SNVs differed significantly between the hypouricemia and normal controls even after multiple testing correction, and p.G13D in SLC2A9 and p.V547L in SLC22A12 were newly reported. All these mutations had no significant effects on HUA susceptibility, while the gene‐based analyses substantiated the significant results on hypouricemia. Conclusion Our study first presents a comprehensive mutation spectrum of hypouricemia in a large Chinese cohort.

Arm mounted unmanned aerial vehicles provide more feasible and attractive solution to manipulate objects in remote areas where access to arm mounted ground vehicles is not possible. In this research, an under-actuated quadrotor unmanned aerial vehicle model equipped with gripper is utilized to grab objects from inaccessible locations. A dual control structure is proposed for controlling and stabilization of the moving unmanned aerial vehicle along with the motions of the gripper. The control structure consists of model reference adaptive control augmented with an optimal baseline controller. Although model reference adaptive control deals with the uncertainties as well as attitude controlling of unmanned aerial vehicle, baseline controller is utilized to control the gripper, remove unwanted constant errors and disturbances during arm movement. The proposed control structure is applied in 6-degree-of-freedom nonlinear model of a quadrotor unmanned aerial vehicle equipped with gripper having (2 degrees of freedom) robotic limb; it is applicable for the simulations to desired path of unmanned aerial vehicle and to grasp object. Moreover, the efficiency of the presented control structure is compared with optimal baseline controller. It is observed that the proposed control algorithm has good transient behavior, better robustness in the presence of continuous uncertainties and gripper movement involved in the model of unmanned aerial vehicle.

This article proposes a new navigation method for mobile robots based on an extended bag of words (BoW) model for general object recognition in indoor environments. The scale-invariant feature transform (SIFT)-detection algorithm with the graphic processing unit (GPU) acceleration technology is used to describe feature vectors in this model. First, in order to add some redundant image information, statistical information of the spatial relationships of all the feature points in an image, i.e. relative distances and angles, is used to extend the feature vectors in the original BoW model. Then, the support vector machine (SVM) classifier is used to classify objects. Also, in order to navigate conveniently in unknown and dynamic indoor environments, a type of human–robot interaction method based on a hand-drawn semantic map is considered. The experimental results show that this new navigation technology for indoor mobile robots is very robust and highly effective.

In many applications involving epistemic uncertainties usually modeled by belief functions, it is often necessary to approximate general (non-Bayesian) basic belief assignments (BBAs) to subjective probabilities (called Bayesian BBAs). This necessity occurs if one needs to embed the fusion result in a system based on the probabilistic framework and Bayesian inference (e.g. tracking systems), or if one needs to make a decision in the decision making problems. In this paper, we present a new fast combination method, called modified rigid coarsening (MRC), to obtain the final Bayesian BBAs based on hierarchical decomposition (coarsening) of the frame of discernment. Regarding this method, focal elements with probabilities are coarsened efficiently to reduce computational complexity in the process of combination by using disagreement vector and a simple dichotomous approach. In order to prove the practicality of our approach, this new approach is applied to combine users' soft preferences in recommender systems (RSs). Additionally, in order to make a comprehensive performance comparison, the proportional conflict redistribution rule #6 (PCR6) is regarded as a baseline in a range of experiments. According to the results of experiments, MRC is more effective in accuracy of recommendations compared to original Rigid Coarsening (RC) method and comparable in computational time.

The use of renewable energy has increased dramatically over the past couple of decades. Wind farms, consisting of wind turbines, play a vital role in the generation of renewable energy. For monitoring and maintenance purposes, a wind turbine has a variety of sensors to measure the state of the turbine. Sensor measurements are transmitted to a control center, which is located away from the wind farm, for monitoring and maintenance purposes. It is therefore desirable to ensure reliable wireless communication between the wind turbines and the control center while integrating the observations from different sensors. In this paper, we propose an IoT based communication framework for the purpose of reliable communication between wind turbines and control center. The communication framework is based on repeat-accumulate coded communication to enhance reliability. A fusion algorithm is proposed to exploit the observations from multiple sensors while taking into consideration the unpredictable nature of the wireless channel. The numerical results show that the proposed scheme can closely predict the state of a wind turbine. We also show that the proposed scheme significantly outperforms traditional estimation schemes.

Epidemiological studies have identified hyperuricemia as an independent risk factor for cardiovascular disease. However, the mechanism whereby hyperuricemia causes atherosclerosis remains unclear. The objective of the study was to establish a new rat model of hyperuricemia-induced atherosclerosis. Wistar-Kyoto rats were randomly allocated to either a normal diet (ND), high-fat diet (HFD), or high-adenine diet (HAD), followed by sacrifice 4, 8, or 12 weeks later. Serum uric acid and lipid levels were analyzed, pathologic changes in the aorta were observed by hematoxylin and eosin staining, and mRNA expression was evaluated by quantitative real-time polymerase chain reaction. Serum uric acid and TC were significantly increased in the HAD group at 4 weeks compared with the ND group, but there was no significant difference in serum uric acid between the ND and HFD groups. Aorta calcification occurred earlier and was more severe in the HAD group, compared with the HFD group. Proliferating cell nuclear antigen, monocyte chemotactic factor-1, intercellular adhesion molecule-1, and vascular cell adhesion molecule-1 mRNA levels were increased in the HFD and HAD groups compared with the ND group. This new animal model will be a useful tool for investigating the mechanisms responsible for hyperuricemia-induced atherosclerosis.

Interleukin (IL)-17 is a proinflammatory cytokine mainly secreted by activated T helper 17 cells and involved in inflammatory immune responses. This study aimed to investigate the association between IL-17 variants as well as serum IL-17 levels with gout in male Chinese Han individuals. A total of 1,101 male gout patients and 1,239 ethic-matched controls were enrolled. Genetic distributions of three variants (rs2275913 in IL-17A, rs763780 in IL-17F, and rs4819554 in IL-17RA) were detected by real-time polymerase chain reaction using the Taqman probe method. The plasma concentrations of IL-17A and IL-17F were measured in 228 gout patients and 198 controls that came from above samples by an enzyme-linked immunosorbent assay. No significant differences were observed in the genetic distribution of these polymorphisms between cases and controls (rs2275913: χ2 = 0.15, p = 0.928 by genotype, χ2 = 0.14, p = 0.711 by allele; rs763780: χ2 = 2.24, p = 0.326 by genotype, χ2 = 0.26, p = 0.609 by allele; rs4819554: χ2 = 1.79, p = 0.409 by genotype, χ2 = 1.46, p = 0.227 by allele). Levels of serum IL-17A and IL-17F were significantly decreased in gout patients (both p0.05). Although the genetic variants in IL-17 we studied in this research do not appear to be involved in the development of gout in male Chinese Han individuals, the IL-17 cytokine family may participate in gouty inflammation in an undefined way, which requires further validation.

This paper presents a chirp based ultrasonic positioning system (UPS) using orthogonal chirp waveforms. In the proposed method, multiple transmitters can simultaneously transmit chirp signals, as a result, it can efficiently utilize the entire available frequency spectrum. The fundamental idea behind the proposed multiple access scheme is to utilize the oversampling methodology of orthogonal frequency-division multiplexing (OFDM) modulation and orthogonality of the discrete frequency components of a chirp waveform. In addition, the proposed orthogonal chirp waveforms also have all the advantages of a classical chirp waveform. Firstly, the performance of the waveforms is investigated through correlation analysis and then, in an indoor environment, evaluated through simulations and experiments for ultrasonic (US) positioning. For an operational range of approximately 1000 mm, the positioning root-mean-square-errors (RMSEs) &90% error were 4.54 mm and 6.68 mm respectively.

A new visual navigation method for a mobile robot is proposed in this paper. Its originality lies in integrating a sketched map with a semantic map together for the robot's navigation and in using unified tags to help recognize landmarks. In this sketched semantic map, the outline and semantic information of key referenced objects are used to represent themselves and a rough route for the robot's navigation is also sketched. Over the course of robot navigation along the route, and in order to easily recognize the referenced objects from the complex background, a kind of unified label is designed and pasted on the potential referenced objects in advance. A recognition method based on the Pseudo-Zernike Moment and the Normalized Moment of Inertia is used to compute the matching degree between the real-time image of the referenced object and its similar outline in a database. In addition, the odometer information is also fused so as to roughly localize the robot. Finally, through a series of experiments, the advantage and efficiency of the new navigation method with real-time dynamic obstacle avoidance are testified with the help of the imprecise real map and route.

Our previous studies showed that recombinant high-density lipoprotein (rHDL) rHDL74 exhibited higher anti-inflammatory capabilities compared to wild-type rHDL (rHDLwt), while rHDL228 showed hyper-proinflammation. In this paper, we further investigated the potential mechanisms involved in their different inflammatory functions using two models: endotoxemic mice and the RAW264.7 inflammation model. Our results showed that 24 h after the injection of lipopolysaccharide (LPS), mice treated with rHDL74 had a significant decrease in plasma CRP (P