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Abstract Inflammatory bowel disease (IBD) is a chronic disease that includes Crohn’s disease (CD) and ulcerative colitis (UC). Although genome-wide association studies (GWASs) have identified many relevant genetic risk loci, the impact of these loci on protein abundance and their potential utility as clinical therapeutic targets remain uncertain. Therefore, this study aimed to investigate the pathogenesis of IBD and identify effective therapeutic targets through a comprehensive and integrated analysis. We systematically integrated GWAS data related to IBD, UC and CD (N = 25,305) by the study of de Lange KM with the human blood proteome (N = 7213) by the Atherosclerosis Risk in Communities (ARIC) study. Proteome-wide association study (PWAS), mendelian randomisation (MR) and Bayesian colocalisation analysis were used to identify proteins contributing to the risk of IBD. Integrative analysis revealed that genetic variations in IBD, UC and CD affected the abundance of five (ERAP2, RIPK2, TALDO1, CADM2 and RHOC), three (VSIR, HGFAC and CADM2) and two (MST1 and FLRT3) cis-regulated plasma proteins, respectively (P

Abstract Background The interferon‐γ (IFN‐γ) signaling pathway is activated in systemic lupus erythematosus (SLE). This study aimed to assess the causal association between IFN‐γ, IFN‐γ receptor 1 (IFN‐γR1), and IFN‐γR2 and SLE using a bidirectional Mendelian randomization (MR) design. Methods Genetic instruments for exposure to IFN‐γ, IFN‐γR1, and IFN‐γR2 were derived from a large genome‐wide association study (GWAS) that included a sample size of 3301 participants. Instrumental variables for SLE were selected from another independent GWAS analysis comprising 5201 cases and 6099 controls with European ancestry. Bidirectional two‐sample MR was performed using inverse variance weighting, MR‐Egger regression, and weighted median methods. A series of sensitivity analyses were conducted to assess the robustness of the results. Results The inverse variance weighting showed that IFN‐γ had a positive causal association with the risk of SLE (odd ratio [OR] = 1.24, 95% confidence interval [CI]: 1.03–1.47, p = 0.018). IFN‐γR2 levels were not associated with SLE risk after adjustment for multiple comparisons (OR = 0.85, 95% CI: 0.73–0.99, p = 0.034). No genetic association was also detected between IFN‐γR1 and SLE (OR = 0.97, 95% CI: 0.79–1.19, p = 0.768). Evidence from bidirectional MR did not support reverse causality. The weighted median regression also showed directionally similar estimates. Conclusion Higher levels of IFN‐γ are significantly associated with an increased risk of SLE, providing insights into the pathogenesis of SLE.

With the rapid development of mobile networks and widespread use of mobile devices, there is an increasing focus on assigning location-based tasks to mobile users in the context of Mobile Crowd Sensing (MCS). One of the primary challenges in MCS is task assignment, i.e., distributing tasks to suitable users for completion. However, existing work often assumes static offline scenarios where the spatiotemporal information of all users and tasks is pre-determined and known. Neglecting the dynamic spatiotemporal distribution of users and tasks can lead to suboptimal assignment results. In this study, we investigate a novel task assignment problem called Community Task Assignment (CTA). The objective is to enhance the effectiveness and precision of task distribution by considering the sociality of current users and distributing location-based tasks through communities. Initially, we partition users into different communities by abstracting and identifying behavior patterns through the computation of minimum spanning trees, connectivity parameters, and community cohesion. Subsequently, we calculate the match between perception tasks and community behavior pattern features, and task distribution is carried out by the central nodes of the communities based on this match. Experimental validation first confirms the effectiveness of the community partitioning algorithm. Compared to existing algorithms, the proposed method more accurately detects community structures with similar behavioral features in the network. Furthermore, a comparison with existing task assignment algorithms verifies the superiority of the proposed method in terms of average task completion time, task matching rate, and overall utility of task assignments.

The rapid development of electronic information technology and the use of high-power electrical equipment have led to the increasingly serious problem of electromagnetic interference (EMI). Therefore, it is of great significance to study electromagnetic wave absorbing (EWA) materials with good absorbing properties. Compared with other wave absorbing materials, carbon-based nanomaterials such as silicon carbide (SiC), carbon nanotube (CNT), carbon nanowire (CNW) and carbon nanofiber (CNF) have the advantages of low density, large specific surface area/aspect ratio and excellent dielectric properties, which make them stand out. However, impedance mismatch caused by high conductivity and a single microwave loss mechanism seriously affect the absorption performance. In order to overcome the above shortcomings, surface modification, component control, structural design and other methods have been widely used in EWA materials in recent years to improve their absorption performance. In this review, we introduce the mechanism of microwave absorption and summarizes the research progress of one-dimensional carbon based nanomaterials and their composites. The preparation methods and microwave absorption properties of one-dimensional carbon based nanocomposites with different components, morphologies, and microstructures were discussed in detail. Finally, the challenges and future development prospects of one-dimensional carbon based nanomaterials were summarized, providing reference for the development of high-performance microwave absorbing materials.

BackgroundPsoriasis is a highly heterogeneous autoinflammatory disease. At present, heterogeneity in disease has not been adequately translated into concrete treatment options. Our aim was to develop and verify a new stratification scheme that identifies the heterogeneity of psoriasis by the integration of large-scale transcriptomic profiles, thereby identifying patient subtypes and providing personalized treatment options whenever possible.MethodsWe performed functional enrichment and network analysis of upregulated differentially expressed genes using microarray datasets of lesional and non-lesional skin samples from 250 psoriatic patients. Unsupervised clustering methods were used to identify the skin subtypes. Finally, an Xgboost classifier was utilized to predict the effects of methotrexate and commonly prescribed biologics on skin subtypes.ResultsBased on the 163 upregulated differentially expressed genes, psoriasis patients were categorized into three subtypes (subtypes A–C). Immune cells and proinflammatory-related pathways were markedly activated in subtype A, named immune activation. Contrastingly, subtype C, named stroma proliferation, was enriched in integrated stroma cells and tissue proliferation-related signaling pathways. Subtype B was modestly activated in all the signaling pathways. Notably, subtypes A and B presented good responses to methotrexate and interleukin-12/23 inhibitors (ustekinumab) but inadequate responses to tumor necrosis factor-α inhibitors and interleukin-17A receptor inhibitors. Contrastly, subtype C exhibited excellent responses to tumor necrosis factor-α inhibitors (etanercept) and interleukin-17A receptor inhibitors (brodalumab) but not methotrexate and interleukin-12/23 inhibitors.ConclusionsPsoriasis patients can be assorted into three subtypes with different molecular and cellular characteristics based on the heterogeneity of the skin's immune cells and the stroma, determining the clinical responses of conventional therapies.

Previous studies have introduced a resonant caisson designed to enhance wave energy extraction in regions with low wave energy density; however, its operational mechanism remains poorly understood. This paper seeks to elucidate the operational mechanism of the resonant caisson by leveraging Star-CCM+ for Computational Fluid Dynamics (CFD) simulations, focusing on the influence of guides and their dimensions on the water levels, flow velocities, and vortex dynamics. The findings demonstrate the remarkable wave-amplification capabilities of the resonant caisson, with the maximum amplification factor reaching 2.31 at the calculated frequency in the absence of guides. Incorporating guides and expanding their radii substantially elevate the flow rates, accelerate the water currents, and alter the vortex patterns, thereby further enhancing the amplification factor. This study will provide a reference for optimizing the design of resonant caissons and wave energy converters based on resonant caissons, thus promoting the effective use of wave energy resources.

Due to the widespread use of mobile intelligent terminal devices, Mobile Crowd Sensing (MCS) applications have gained significant research attention. However, ensuring users privacy remains a critical challenge, as it can hinder users’ willingness to participate actively in tasks. To address the limitations of existing differential privacy protection methods, this paper proposes a novel privacy protection approach based on Artificial Immune Computing (AICppm). Specifically, private information is concealed within a masking carrier, and data scrambling is avoided. The proposed method involves two main steps: first, a carrier preprocessing approach based on a high-pass filter bank is designed to identify candidate positions for perturbation. Then, a carrier steganography algorithm based on multi-objective optimization is used, transforming the perturbation position into an antibody using the artificial immune algorithm. By iteratively searching for antibodies with higher fitness, the optimal perturbation of the offspring population is identified using the improved Strength Pareto Evolution Algorithm (SPEA2). The experimental results demonstrate that the proposed algorithm can withstand the attacks of malicious steganalysis tools, preserving the integrity of the sensing data and enabling real-time processing of private information.

With natural disasters occurring more frequently around the world, their impact on tourism is becoming a serious problem. The existing literature in the field of tourism disaster management focuses mostly on disaster impact analysis, risk assessment, and post-disaster recovery, while the impact of disaster on tourism and tourists is still a new topic. It is necessary to investigate the correlation between the natural disasters and the tourists’ behavior. Taking the famous tourism destination, Qinling Mountain, located in the middle of China, as an example where frequent mountain disasters happened, we investigated 542 youth group tourists using a questionnaire survey and analyzed the influence of risk perception, disaster knowledge, and emotional attachment on tourists’ travel behavioral intentions. The results showed that 1) risk perception has a negative effect on tourists’ behavioral intentions; 2) disaster knowledge and tourism emotional attachment have a positive effect on tourists’ behavioral intention; and 3) the moderation role of gender is not significant, while the moderation role of education level is significant. Therefore, this analysis is of great importance for research dealing with the theory of tourism disaster and the management practice of disaster-prone tourism destinations.

Abstract Background Ticks are blood-sucking arthropods that can transmit diseases to humans and animals. These arthropods are the second most important vectors of pathogens. MicroRNAs are a class of conserved small noncoding RNAs that play regulatory roles in gene expression at the post-transcriptional level. Molting is an important biological process in arthropods. Research on the molting process is important for understanding tick physiology and control. Methods Dual-luciferase reporter assays were used to assess the role of miRNA let-7 in ecdysteroid receptor (ECR) biology. The expression levels of ECR and let-7 were measured by real-time qPCR before and after tick molting. To explore the function of let-7 and ECR, we performed overexpression and knocking down of let-7 and RNAi of ECR in tick nymphs. The biological function of let-7 in molting was explored by injecting nymphs, ten days after engorgement, with let-7 agomir for overexpression and let-7 antagomir for knocking down. The rate of molting was then determined. ECR dsRNA was injected into ticks to evaluate the function of ECR by gene silencing. The expression of ECR and let-7 was measured using RT-qPCR. All data were analyzed using GraphPad Prism v.6. Results The results of the luciferase assay using a eukaryotic expression system revealed that ECR was a natural target of let-7. Let-7 overexpressed by agomir affected the rate of molting (P

As an interdisciplinary research area, fractional circuits and systems have attracted extensive attention of scholars and researchers for their superior performance and potential applications. The passive realization of the fractional-order (FO) immittance function plays an important role in fractional circuits' theory, which is useful in fractional circuit design and modeling. This paper deals with the passive synthesis of FO three-element-kind circuits. First, the method is given for judging the immittance functions of FO three-element-kind circuits. Then, by making use of impedance scaling and variable substitution, the synthesis method of such an FO immittance function is proposed, which is based on the bivariate reactance synthesis method. Finally, a procedure is proposed to realize such immittance functions using the three-element-kind circuit. And several examples are given to illustrate the proposed method.

Dengue virus (DENV) is primarily transmitted by the bite of an infected mosquito of Aedes aegypti and Aedes albopictus, and symptoms caused may range from mild dengue fever to severe dengue hemorrhagic fever and dengue shock syndrome. Reverse genetic system represents a valuable tool for the study of DENV virology, infection, pathogenesis, etc. Here, we generated and characterized an eukaryotic-activated full-length infectious cDNA clone for a DENV serotype 1 (DENV-1) isolate, D19044, collected in 2019. Initially, nearly the full genome was determined by sequencing overlapping RT-PCR products, and was classified to be genotype I DENV-1. D19044 wild-type cDNA clone (D19044_WT) was assembled by four subgenomic fragments, in a specific order, into a low-copy vector downstream the CMV promoter. D19044_WT released the infectious virus at a low level (1.26 × 103 focus forming units per milliliter [FFU/mL]) following plasmid transfection of BHK-21 cells. Further adaptation by consecutive virus passages up to passage 37, and seven amino acid substitutions (7M) were identified from passage-recovered viruses. The addition of 7M (D19044_7M) greatly improved viral titer (7.5 × 104 FFU/mL) in transfected BHK-21 culture, and virus infections in 293T, Huh7.5.1, and C6/36 cells were also efficient. D19044_7M plasmid was genetically stable in transformant bacteria after five transformation-purification cycles, which did not change the capacity of producing infectious virus. Moreover, the D19044_7M virus was inhibited by mycophenolic acid in a dose-dependent manner. In conclusion, we have developed a DNA-launched full-length infectious clone for a genotype I isolate of DENV-1, with genetic stability in transformant bacteria, thus providing a useful tool for the study of DENV-1.

Water vapor (WV) is a vital basis of water and energy cycles and varies with space and time. When researching the variations of moisture in the atmosphere, it is intuitive to think about the total WV of the atmosphere column, precipitable water (PW). It is an element that needs high-altitude observations. A surface quantity, surface WV pressure (SVP), has a close relationship to PW because of the internal physical linkage between them. The stability of their linkage at climatic scales is verified using monthly mean data from 1979 to 2021, while studies before mainly focused on daily and annual cycles in local areas. The consistency of their variations is checked with three reanalysis datasets from three angles, the interannual variations, the long-term trends, and the empirical orthogonal function (EOF) modes. Results show that the interannual correlation of SVP and PW can reach a level that is quite high and are significant in most areas, and the weak correlation mainly exists over low-latitude oceans. The long-term trends, as well as the first EOF modes of these two quantities, also show that their variations are consistent, with spatial correlation coefficients between the long-term trends of two variables that are generally over 0.6, but specific differences appearing in some regions including the Tropical Indian Ocean and Middle Africa. With the correspondence of PW and SVP, the variations of total column WV can be indicated by surface elements. The correspondence is also meaningful for the analysis of the co-variation in total column vapor and temperature. For example, we could research the relations between SVP and air temperature, and they can reflect the co-variance of total column vapor and near-surface air temperature, which can avoid analyzing the relation between column-integrated moisture content and surface air temperature directly.

It has generally been regarded that, in the warming climate, atmospheric water vapor may increase due to the enhancement in surface evaporation, which is expected from the Clausius–Clapeyron (C–C) equation, along with the assumption that relative humidity experiences small changes. If the variation in relative humidity is small, the response of water vapor to temperature will be closely in line with the C–C equation. However, whether relative humidity experiences large or small changes needs be assessed, and the change of relative humidity should be compared with the change in surface–air temperature. In this study, we link surface vapor pressure, which characterizes atmospheric water vapor, to surface-air temperature, and treat both the temperature and relative humidity as influencing factors. A method based on linear regression is applied to compare the interannual variabilities of relative humidity and temperature in the interannual variation in surface vapor pressure. Whether the year-to-year perturbation of relative humidity is important, compared with the perturbation in surface-air temperature, is explored Results show that, at high latitudes of both hemispheres, the variation in vapor pressure is dominated by air temperature, and relative humidity has small positive contributions. Thus, the variation in relative humidity over these regions is comparably small, and the response of water vapor to temperature can well follow the C–C equation. Differently, at mid-low latitudes, especially on land, air temperature plays a negative role in the variation in vapor pressure. Relative humidity offsets the negative contribution and dominates the variation in vapor pressure, suggesting that the variation in the relative humidity over these regions is comparably large. Hence, the response of water vapor to temperature deviate from the C–C equation. Analysis indicates that the different results of the dominance from the two influencing factors are affected by the dual effects of precipitation or wet-air transport over land. Both precipitation and the transport of cold wet air could break the C–C relation between water vapor pressure and temperature.

This paper proposes a modified tangential contact stiffness model considering friction’s effect, which is the first key step to establish the dynamic model of the fixture-workpiece system, and this is the foundation of vibration suppression for the manufacturing process of aerospace blades. According to Love’s elastic deformation, the model’s derivation process starts with the potential function in each coordinate axis’s direction respectively. The generalized Hertz contact theory is employed to calculate the contact forces in this model. The symmetrical characteristic of the contact area has simplified the derivation process to obtain the eventual tangential contact stiffness model. A validation experiment focusing on a tangential stiffness measuring is achieved by putting two spherical objects in contact together to get the tangential contact stiffness. Based on the data collected in this experiment, a comparison with a most similar existed model is carried out, and the result shows that the relative error of this modified model are all less than 10%, while the original model’s (the most similar model) relative error exceeding 50% captures more than 3/4 of the 30 data sets randomly selected in each experiment group, and that means the modification of this paper brings great improvement to the contact stiffness model.

Abstract Background The hard tick Haemaphysalis longicornis is widely distributed in eastern Asia, New Zealand and Australia and is considered the major vector of Theileria and Babesia, harmful parasites to humans and animals. Female ticks need successful blood meals to complete the life-cycle. Therefore, elucidation of the underlying molecular mechanisms of H. longicornis development and reproduction is considered important for developing control strategies against the tick and tick-borne pathogens. Methods Luciferase assays were used to identify the targets of micro RNA miR-275 in vitro. RNAi of Vitellogenin (Vg) was used in phenotype rescue experiments of ticks with miR-275 inhibition, and these analyses were used to identify the authentic target of miR-275 in vivo. The expression of miR-275 in different tissues and developmental stages of ticks was assessed by real-time PCR. To elucidate the functions of miR-275 in female ticks, we injected a miR-275 antagomir into female ticks and observed the phenotypic changes. Statistical analyses were performed with GraphPad5 using Student’s t-test. Results In this study, we identified Vg-2 as an authentic target of miR-275 both in vitro and in vivo by luciferase assays and phenotype rescue experiments. miR-275 plays the regulatory role in a tissue-specific manner and differentially in developmental stages. Silencing of miR-275 resulted in blood digestion problems, substantially impaired ovary development and significantly reduced egg mass (P

In this paper, we consider a networked fractional SIR model. After proving the existence and uniqueness of the solution, we obtain the basic reproduction number, the disease-free equilibrium point and the endemic equilibrium point. By constructing the Lyapunov function, we show that the endemic equilibrium is globally asymptotically stable when the basic reproduction number is greater than 1, and the disease-free equilibrium is globally asymptotically stable when the basic reproduction number is less than 1. Finally, numerical simulations are carried out to verify these theoretical results. Thus, the stability theory of Laplacian diffusion is extended to the graph Laplacian model. [ABSTRACT FROM AUTHOR]

Aiming at the problem that some traditional high voltage circuit breaker fault diagnosis methods were over-dependent on subjective experience, the accuracy was not very high and the generalization ability was poor, a fault diagnosis method for energy storage mechanism of high voltage circuit breaker, which based on Convolutional Neural Network (CNN) characteristic matrix constructed by sound-vibration signal, was proposed. In this paper, firstly, the morphological filtering was used for background noise cancellation of sound signal, and the time scale alignment method based on kurtosis and envelope similarity were proposed to ensure the synchronism of the sound-vibration signal. Secondly, the Pearson correlation coefficient was used to construct two-dimensional image characteristic matrix for the expanded sound-vibration signal. Finally, the characteristic matrix was trained by utilizing CNN. Local Response Normalization (LRN) and core function decorrelation were utilized to improve the structure of CNN model, which reduced the bad impact of large data fluctuation of energy storage process on the diagnostic accuracy of circuit breaker energy storage mechanism. Compared with the traditional method, the proposed method has obvious advantages, whose total accurate rate up to 98.2% and generalization performance is excellent. [ABSTRACT FROM AUTHOR]