The Type 2 Deiodinase Thr92Ala Polymorphism

Objective. Type 2 deiodinase (Dio2) is an enzyme responsible for the conversion of T4 to T3. The Thr92Ala polymorphism has been shown related to an increased risk for developing type 2 diabetes mellitus (T2DM). The aim of this study is to assess the association between this polymorphism and glycemic control in T2DM patients as marked by the HbA1C levels. Design and Methods. The terms “rs225014,” “thr92ala,” “T92A,” or “dio2 a/g” were used to search for eligible studies in the PubMed, Embase, and Cochrane databases and Google Scholar. A systematic review and meta-analysis of studies including both polymorphism testing and glycated hemoglobin (HbA1C) assays were performed. Results. Four studies were selected, totaling 2190 subjects. The pooled mean difference of the studies was 0.48% (95% CI, 0.18–0.77%), indicating that type 2 diabetics homozygous for the Dio2 Thr92Ala polymorphism had higher HbA1C levels. Conclusions. Homozygosity for the Dio2 Thr92Ala polymorphism is associated with higher HbA1C levels in T2DM patients. To confirm this conclusion, more studies of larger populations are needed

Data-Driven Modeling of Landau Damping by Physics-Informed Neural Networks

Kinetic approaches are generally accurate in dealing with microscale plasma physics problems but are computationally expensive for large-scale or multiscale systems. One of the long-standing problems in plasma physics is the integration of kinetic physics into fluid models, which is often achieved through sophisticated analytical closure terms. In this study, we successfully construct a multi-moment fluid model with an implicit fluid closure included in the neural network using machine learning. The multi-moment fluid model is trained with a small fraction of sparsely sampled data from kinetic simulations of Landau damping, using the physics-informed neural network (PINN) and the gradient-enhanced physics-informed neural network (gPINN). The multi-moment fluid model constructed using either PINN or gPINN reproduces the time evolution of the electric field energy, including its damping rate, and the plasma dynamics from the kinetic simulations. For the first time, we introduce a new variant of the gPINN architecture, namely, gPINN$p$ to capture the Landau damping process. Instead of including the gradients of all the equation residuals, gPINN$p$ only adds the gradient of the pressure equation residual as one additional constraint. Among the three approaches, the gPINN$p$-constructed multi-moment fluid model offers the most accurate results. This work sheds new light on the accurate and efficient modeling of large-scale systems, which can be extended to complex multiscale laboratory, space, and astrophysical plasma physics problems.Comment: 11 pages, 7 figure

Online English writing teaching method that enhances teacher–student interaction

A significant component of the online learning platform is the online exercise assessment system, which has access to a wealth of past student exercise data that may be used for data mining research. However, the data from the present online exercise system is not efficiently used, making each exercise less relevant for students and decreasing their interest and interaction with the teacher as she explains the activities. In light of this, this research creates an exercise knowledge map based on the connections between workouts, knowledge points, and previous tournaments. The neural matrix was then improved using cross-feature sharing and feature augmentation units to deconstruct the workout recommendation model. The study also developed an interactive text sentiment analysis model based on the expansion of the self-associative word association network to assess how students interacted after the introduction of the personalized exercise advice teaching approach. The outcomes demonstrated that the suggested model’s mean diversity value at completion was 0.93, an increase of 0.14 and 0.23 over collaborative filtering algorithm and DeepFM (deep factor decompose modle), respectively, and that the proposed model’s final convergence value was 92.3%, an improvement of 2.3 and 4.1% over the latter two models. The extended model used in the study outperformed the support vector machine (SVM) and Random Forest models in terms of accuracy by 5.9 and 1.7%, respectively. In terms of F1 value indicator, the model proposed by the research has a value of 90.4%, which is 2.5 and 2.1% higher than the SVM model and Random Forest model; in terms of recall rate indicators, the model proposed by the research institute has a value of 94.3%, which is an increase of 6.2 and 9.8% compared to the latter two models. This suggests that the study’s methodology has some application potential and is advantageous in terms of customized recommendation and interactive sentiment recognition

Comparative analysis of tissue expression and methylation reveal the crucial hypoxia genes in hypoxia resistant animals

Tibetan goat and Tibetan sheep are species peculiar to Qinghai-Tibetan Plateau which is the highest plateau in the world, and have high hypoxia resistance to the extremely bad environment. Unlike monogastrics, how the genes change responding to hypoxia in ruminants remains unclear. In the present study, three healthy animals of every breeds, including Tibetan sheep, Tibetan goat, Chuanzhong goat and Small-Tailed Han sheep were selected. The expression of factor inhibiting HIF 1 (FIH-1), hypoxia inducible factor 1α (HIF-1α), HIF-3α and erythropoietin (EPO) in various tissues, including heart, liver, lungs, kidney, muscle and brain, were investigated. EPO was observed highly expressed in all the tissues of Tibetan goats and Tibetan sheep compared with low-altitude animals respectively, implied that higher expression of EPO may give the explanation for the hypoxia resistance of plateau animals. Besides, we also cloned the promoters of FIH-1, HIF-1α, HIF-3α and EPO in goats and sheep, analyzed their core regions and CpG islands. Higher methylation rate was observed in HIF-1α, HIF-3α and EPO, while lower methylation rate hit on FIH-1. These data may be beneficial for revealing the response mechanism to hypoxia of plateau animals.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Eco-environment and coupling coordination and quantification of urbanization in Yangtze River delta considering spatial non-stationarity

Since the 21st century, the rapid development of China’s mega-city clusters has posed a major threat to the healthy and coordinated development of cities. Therefore, it is necessary to be develop the comprehend the state of coupling coordination among mega-city cluster and EEQ under mesoscale. In this study, the largest Yangtze River Delta urban agglomeration is taken as the research object, NS-RSEI is constructed to evaluate the EEQ of the Yangtze River Delta, and the coupling coordination mechanism on the long-time series of the Yangtze River Delta in recent 20 years is explored by means of spatio-temporal analysis. The outcome verify that CCD of the Yangtze River Delta growth with a strong spatial dependence from 2001 to 2020, showing a spatial distribution pattern of " East West high-low". Above all, this study shows that urbanization is the main factor determining the development of CCD. In addition, compared with the traditional remote sensing eco-environment monitoring model, NS-RSEI proposed in this study shows better ability in mesoscale environmental monitoring, and provides great convenience for mesoscale EEQ evaluation. This study fills the research gap of the interactive coupling mechanism between urbanization and eco-environment quality of mesoscale mega-city group, and provides a new perspective on the sustainable development of megacity clusters

The Type 2 Deiodinase Thr92Ala Polymorphism Is Associated with Worse Glycemic Control in Patients with Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis

Objective. Type 2 deiodinase (Dio2) is an enzyme responsible for the conversion of T4 to T3. The Thr92Ala polymorphism has been shown related to an increased risk for developing type 2 diabetes mellitus (T2DM). The aim of this study is to assess the association between this polymorphism and glycemic control in T2DM patients as marked by the HbA1C levels. Design and Methods. The terms “rs225014,” “thr92ala,” “T92A,” or “dio2 a/g” were used to search for eligible studies in the PubMed, Embase, and Cochrane databases and Google Scholar. A systematic review and meta-analysis of studies including both polymorphism testing and glycated hemoglobin (HbA1C) assays were performed. Results. Four studies were selected, totaling 2190 subjects. The pooled mean difference of the studies was 0.48% (95% CI, 0.18–0.77%), indicating that type 2 diabetics homozygous for the Dio2 Thr92Ala polymorphism had higher HbA1C levels. Conclusions. Homozygosity for the Dio2 Thr92Ala polymorphism is associated with higher HbA1C levels in T2DM patients. To confirm this conclusion, more studies of larger populations are needed

Mining Ground Surface Information Extraction and Topographic Analysis Using UAV Video Data

Taking the Xiangwang bauxite mining of Xiaoyi City, Shanxi Province as the research object, the DJi “Wu”inspire2 model Unmanned aerial vehicle (UAV) was used to obtain the video data, image data and Ground control points (GCP) data of a typical pit in the study area. Based on the two kinds of data source (video data and image data), the Digital surface model (DSM) of the research area was acquired with or without ground control points through aerial triangulation and block adjustment. Using the DSM obtained by the two data source, the distribution of elevation, slope, slope direction, surface fluctuation and surface roughness was extracted and compared. Research shows that the DSM, acquired by the ContextCapture software without GCP, using video data obtained by aerial shooting around one interest point, can qualitatively reflect the topographic distribution of the land surface. The DSM got by the video data with the GCP can achieve the similar accuracy with the result obtained by image data, and the topographic information acquired by the two kinds of data source has highly similar characteristics in spatial and numerical distribution. It can be concluded through comparison and analysis of the topographical factors that steep slopes with complex topography and large elevation difference distributes in the northwest-central of the pit, of which northwest and southwest slopes can be easily eroded by wind and rain, so attention should be paid to slop stability monitoring and disaster prevention in this area. As a whole, the results show that video data obtained by UAV can not only reflect the dynamic changes of the land surface qualitatively, but also can describe the distribution of surface topography quantitatively through processing to get the DSM. It has great application potential in the field of disaster emergency monitoring and geological hazard risk assessment in mining areas