The effects of Sodium-glucose cotransporter 2 inhibitors on adipose tissue in patients with type 2 diabetes: A meta-analysis of randomized controlled trials

PurposeTo systematically evaluate the effect of Sodium-glucose cotransporter 2 (SGLT2) inhibitors on adipose tissue in patients with type 2 diabetes.MethodsWe searched PubMed, Cochrane Library, EMBASE, and Web of science databases for literature pertaining to Randomized controlled trials (RCTs) of SGLT2 inhibitors in treating type 2 diabetes patients. The retrieval time was from the date of establishment of the databases to September 1, 2022. Meta-analysis was performed using RevMan5.4 software.ResultsTotally 551 patients were included in 10 articles. Meta-analysis results showed that compared with the control group, the visceral adipose tissue (WMD = -16.29 cm2, 95% CI: -25.07 ~ -7.50, P<0.00001), subcutaneous adipose tissue (WMD = -19.34 cm2, 95% CI: -36.27 ~ -2.41, P<0.00001), body weight (WMD = -2.36 kg, 95% CI: -2.89 ~ -1.83, P<0.00001) and triglyceride (WMD = -24.41 mg/dl, 95% CI: -45.79 ~ -3.03, P = 0.03) of the trial group significantly reduced.ConclusionSGLT2 inhibitors cause significant reductions in visceral adipose tissue, subcutaneous adipose tissue, body weight and triglycerides in type 2 diabetes patients, which may be attributed to the protective effect of the inhibitors on cardiovascular system

Enhancing Event Sequence Modeling with Contrastive Relational Inference

Neural temporal point processes(TPPs) have shown promise for modeling continuous-time event sequences. However, capturing the interactions between events is challenging yet critical for performing inference tasks like forecasting on event sequence data. Existing TPP models have focused on parameterizing the conditional distribution of future events but struggle to model event interactions. In this paper, we propose a novel approach that leverages Neural Relational Inference (NRI) to learn a relation graph that infers interactions while simultaneously learning the dynamics patterns from observational data. Our approach, the Contrastive Relational Inference-based Hawkes Process (CRIHP), reasons about event interactions under a variational inference framework. It utilizes intensity-based learning to search for prototype paths to contrast relationship constraints. Extensive experiments on three real-world datasets demonstrate the effectiveness of our model in capturing event interactions for event sequence modeling tasks.Comment: 6 pages, 2 figure

Heterologous Boost Following Mycobacterium bovis BCG Reduces the Late Persistent, Rather Than the Early Stage of Intranasal Tuberculosis Challenge Infection

Adults are the leading population affected by tuberculosis (TB) epidemic and death. Developing an effective vaccine against adult TB is urgently needed. Mycobacterium bovis Bacillus Calmette-Guerin (BCG) prime-heterologous boost strategy has been explored extensively to protect adults against primary TB infection, but the majority of experimental regimens have not improved the protection primed by the BCG vaccine. The reason attributed to the failure remains unknown. In this study, CTT3H-based vaccines, namely DMT adjuvanted CTT3H subunit or DNA vaccine (pCTT3H-DMT), and recombinant adenovirus rAdCTT3H were constructed. Protective efficacy and immunogenicity of BCG prime-CTT3H based boosters were compared in C57BL/c mice models of primary or late persistent TB infection. Similar protective efficacy against early intranasal infection was provided by different CTT3H-based vaccines alone in vaccinated mice, and their protection was inferior to that of the BCG vaccine. In addition, CTT3H-based heterologous boosters did not enhance the protection conferred by the BCG vaccine against primary infection. However, all of these three boosters provided stronger protection against late persistent TB infection than BCG alone, regardless of vaccine types. Although BCG prime-boosters elicited Th1-biased responses to the antigen CTT3H, the number of CTT3H-sepcific IFN-γ-expressing TEM (CD62LloCD44hi) and IL-2-expressing TCM (CD62LhiCD44hi) cells in the spleen was not improved before exposure to Mycobacterium tuberculosis infection. In contrast, IFN-γ+ TEM and IL-2+ TCM cells in spleens, especially in lungs were significantly increased in BCG prime-boosters after exposure vaccination. Our results indicate that BCG prime-boost strategy might be a promising measure for the prevention against late persistent TB infection by induction of IFN-γ+ TEM and IL-2+ TCM cells in the lung, which can be used as alternative biomarkers for guiding the clinical practice and future development of TB vaccine for adults

The Stimulative Effect of Yangjing Capsule on Testosterone Synthesis through Nur77 Pathway in Leydig Cells

Yangjing Capsule (YC), an innovative Chinese medicine based on traditional prescription, promotes testosterone synthesis by upregulating the expression of steroidogenic enzymes. Nur77 as a nuclear receptor is known to regulate the expression of many steroid synthetases. This study aimed to explore the potential mechanisms by which YC regulates testosterone synthesis in Leydig cells. Real-time PCR and Western blot analysis were employed to assess the expressions of steroidogenic enzymes and Nur77 after treating MLTC-1 cells with YC. The luciferase reporter gene assay was performed to detect the activity of Nur77 gene promoter. Also, the expressions of steroid synthases were detected after Nur77 gene was knocked down. YC significantly stimulated Nur77 production and upregulated StAR and HSD3B expression, and this agrees with the activity of Nur77 gene promoter that was significantly enhanced by YC. Interestingly, knockdown of Nur77 blocked the above YC’s effects and consequently inhibited testosterone synthesis in MLTC-1 cells. YC promotes StAR and HSD3B expression and upregulates testosterone synthesis in Leydig cells, which is mediated by Nur77 pathway

Manifold Elastic Net: A Unified Framework for Sparse Dimension Reduction

It is difficult to find the optimal sparse solution of a manifold learning based dimensionality reduction algorithm. The lasso or the elastic net penalized manifold learning based dimensionality reduction is not directly a lasso penalized least square problem and thus the least angle regression (LARS) (Efron et al. \cite{LARS}), one of the most popular algorithms in sparse learning, cannot be applied. Therefore, most current approaches take indirect ways or have strict settings, which can be inconvenient for applications. In this paper, we proposed the manifold elastic net or MEN for short. MEN incorporates the merits of both the manifold learning based dimensionality reduction and the sparse learning based dimensionality reduction. By using a series of equivalent transformations, we show MEN is equivalent to the lasso penalized least square problem and thus LARS is adopted to obtain the optimal sparse solution of MEN. In particular, MEN has the following advantages for subsequent classification: 1) the local geometry of samples is well preserved for low dimensional data representation, 2) both the margin maximization and the classification error minimization are considered for sparse projection calculation, 3) the projection matrix of MEN improves the parsimony in computation, 4) the elastic net penalty reduces the over-fitting problem, and 5) the projection matrix of MEN can be interpreted psychologically and physiologically. Experimental evidence on face recognition over various popular datasets suggests that MEN is superior to top level dimensionality reduction algorithms.Comment: 33 pages, 12 figure

Research on the Spatiotemporal Pattern and Influencing Mechanism of Coastal Urban Vitality: A Case Study of Bayuquan

Enhancing the spatial vitality of coastal cities is beneficial for the sustainable development of urban construction. However, how to fully utilize coastal resources and boost urban vitality is an important issue. This study takes the coastal city of Bayuquan in China’s cold region as an example. Firstly, we conducted field investigations and data mining in Bayuquan, utilizing Baidu heat map data to measure the spatial–temporal vitality of different areas in Bayuquan. Secondly, we used Moran’s I test to examine the spatial autocorrelation of coastal spatial vitality. Lastly, with the help of the OLS and GWR models, we explored the factors influencing spatial vitality and the urban built environment. The research findings indicate the following: (1) There are spatial–temporal differences in the vitality of different areas in Bayuquan, heavily influenced by the tourist season. (2) The OLS results show that the impact of the built environment on spatial vitality exhibits spatial heterogeneity during different tourist seasons. However, we found no spatial heterogeneity in the influencing factors in the harbor district. (3) The harbor district and the tourism-driven district re quire differentiated construction guidance. Facility functions and block morphology mainly influence the vitality of the harbor district, while the vitality of the tourism-driven district is primarily affected by its aesthetic characteristics. This study can propose differentiated regional construction guidance and specific feasible coastal urban design strategies for seasonally influenced coastal city construction. It holds significant implications for improving urban living quality and is vital to urban decision-makers, planners, and stakeholders

How to Apply Data Mining Technology to the Study of Agricultural Information Data Resources?

This paper makes a brief description of the definition and methods of data mining. It describes the characteristics of agricultural data (value delivery, specialization, spatio-temporal bidimensionality) and the status of application of data mining technology in agriculture

Interturn Short Fault Detection and Location of Permanent Magnet Wind Generator Based on Negative Sequence Current Residuals

This article proposes a model-based method for the detection and phase location of interturn short fault (ISF) in the permanent magnet synchronous generator (PMSG). The simplified mathematical model of PMSG with ISF on dq-axis is established to analyze the fault signature. The current residuals are accurately estimated through Luenberger observer based on the expanded mathematical model of PMSG. In current residuals, the second harmonics are extracted using negative sequence park transform and angular integral filtering to construct the fault detection index. In addition, the unbalance characteristics of three-phase current after ISF can reflect the location of the fault phase, based on which the location indexes are defined. Simulation results for various operating and fault severity conditions primarily validate the effectiveness and robustness of diagnosis method in this paper

Dynamic recrystallization analysis of reduction pretreatment process by multi-phase field method

The reduction pretreatment (RP) process is an effective method to improve billet quality, and the deformation recrystallization plays an important role in the process. Exploring the RP process parameters, a dynamic recrystallization model of GCr15 steel was established by the phase-field method and physical simulation. The recrystallization kinetics and flow stress curves during hot compression were simulated by using this mode. The effects of deformation parameters and initial grain size on the dynamic recrystallization were investigated. Moreover, by using the results obtained by Finite element method (FEM), dynamic recrystallization during the RP process was investigated though this model. It was found that increasing the deformation temperature, deformation rate and decreasing the initial grain size can promote the dynamic recrystallization kinetics. Large Zener-Hollomon parameters can enhance recrystallized grain refinement, while the recrystallized grain size was not affected by the initial grain size. During the RP process, when the reduction is insufficient (10%), partial recrystallization occurs in the billet. With the increase of reduction from 10% to 16%, the area of complete recrystallization increases gradually. When the reduction is the same, the recrystallization in the billet center increases with the decrease of casting speed. When the reduction is 10%, partial recrystallization occurs in the billet center at a casting speed of 0.7 m min ^−1 , and fully recrystallization occurs in the billet center with a casting speed of 0.5 m min ^−1 . Thus, when the reduction is difficult to increase further, the recrystallization in the billet center can be improved by decreasing the casting speed