Antidiabetic effect of Tibetan medicine Tang-Kang-Fu-San in db/db mice via activation of PI3K/Akt and AMPK pathways

This study was to investigate the anti-diabetic effects and molecular mechanisms of Tang-Kang-Fu-San (TKFS), a traditional Tibetan medicine, in treating type 2 diabetes mellitus of spontaneous diabetic db/db mice. Firstly HPLC fingerprint analysis was performed to gain the features of the chemical compositions of TKFS. Next different doses of TKFS (0.5 g/kg, 1.0 g/kg, and 2.0 g/kg) were administrated via oral gavage to db/db mice and their controls for 4 weeks. TKFS significantly lowered hyperglycemia and ameliorated insulin resistance (IR) in db/db mice, indicated by results from multiple tests, including fasting blood glucose test, intraperitoneal insulin and glucose tolerance tests, fasting serum insulin levels and homeostasis model assessment of IR analysis as well as histology of pancreas islets. TKFS also decreased concentrations of serum triglyceride, total and low-density lipoprotein cholesterol, even though it did not change the mouse body weights. Results from western blot and immunohistochemistry analysis indicated that TKFS reversed the down-regulation of p-Akt and p-AMPK, and increased the translocation of Glucose transporter type 4 in skeletal muscles of db/db mice. In all, TKFS had promising benefits in maintaining the glucose homeostasis and reducing IR. The underlying molecular mechanisms are related to promote Akt and AMPK activation and Glucose transporter type 4 translocation in skeletal muscles. Our work showed that multicomponent Tibetan medicine TKFS acted synergistically on multiple molecular targets and signaling pathways to treat type 2 diabetes mellitus

Comparison of retinal thickness measurements of normal eyes between topcon algorithm and a graph based algorithm

To assess the agreement between Topcon built-in algorithm and our developed graph based algorithm, the retinal thickness of 9-sectors on an Early Treatment of Diabetic Retinopathy Study(ETDRS) chart measurements for normal subjects was compared. A total of fifty eyes were enrolled in this study. The overall and sectoral thickness on ETDRS chart were calculated using Topcon built-in algorithm and our developed three-dimensional graph based algorithm. Correlation analysis and agreement analysis were performed between the commercial algorithm and our algorithm. A high degree of correlation was found between the results obtained from the two methods was from 0.856 to 0.960. It’s showed that our developed graph based algorithm can provide excellent performance similar to Topcon algorithm

An automated framework of inner segment/outer segment defect detection for retinal SD-OCT images

The integrity of inner segment/outer segment (IS/OS) has high correlation with lower visual acuity in patients suffering from blunt trauma. An automated 3D IS/OS defect detection method based on the SD-OCT images was proposed. First, 11 surfaces were automatically segmented using the multiscale 3D graph-search approach. Second, the sub-volumes between surface 7 and 8 containing IS/OS region around the fovea (diameter of mm) were extracted and flattened based on the segmented retinal pigment epithelium layer. Third, 5 kinds of texture based features were extracted for each voxel. A KNN classifier was trained and each voxel was classified as disrupted or nondisrupted and the responding defect volume was calculated. The proposed method was trained and tested on 9 eyes from 9 trauma subjects using the leave-one-out cross validation method. The preliminary results demonstrated the feasibility and efficiency of the proposed method

A tool wear condition monitoring approach for end milling based on numerical simulation

As an important research area of modern manufacturing, tool condition monitoring (TCM) has attracted much attention, especially artificial intelligence (AI)- based TCM method. However, the training samples obtained in practical experiments have the problem of sample missing and sample insufficiency. A numerical simulation- based TCM method is proposed to solve the above problem. First, a numerical model based on Johnson-Cook model is established, and the model parameters are optimized through orthogonal experiment technology, in which the KL divergence and cosine similarity are used as the evaluation indexes. Second, samples under various tool wear categories are obtained by the optimized numerical model above to provide missing samples not present in the practical experiments and expand sample size. The effectiveness of the proposed method is verified by its application in end milling TCM experiments. The results indicate the classification accuracies of four classifiers (SVM, RF, DT, and GRNN) can be improved significantly by the proposed TCM method

Influence of alpha and gamma radiolysis on Pu retention in the solvent TBP/kerosene

In light of the issue of radiolysis of the solvent system in PUREX process, alpha and gamma radiation stability of tributyl phosphate (TBP)/kerosene (OK) have been studied in this paper, in which 238Pu dissolved in the organic phase and 60Co are selected as alpha and gamma irradiation sources, respectively. The amount of the degradation products not easily removed after the washing process has been measured by the plutonium retention. The effects of the absorbed dose, the TBP volume fraction, the cumulative absorbed dose and the presence of UO2 2+ and Zr4+ on the radiolysis of the solvents have been investigated. The results have indicated that the Pu retention increases with the increase of the absorbed dose after alpha or gamma irradiation, and is larger for the solvent containing less TBP. There is competition between UO2 2+ and Pu4+ to complex with the degradation products, and Zr4+ accelerates the radiolysis of the system

An Empirical Study of the Role of Higher Education in Building a Green Economy

The relationship between higher education and economic development has long been emphasized in the research on economics and education. Much of the existing literature focuses on the gross domestic product (GDP) as a core measure of a nation’s economic accounting system, but this may neglect some negative effects of production, such as resource depletion and environmental damage. Under such circumstances, the concept of “green GDP” was conceived to consider environmental influence simultaneously with the economy. It is, however, only theoretically feasible due to the complexity in calculating environmental pollution and the unavailability of data about resource consumption. Considering the measurement problems, this paper proposes a new approach to indirectly estimate green GDP. Using this approach, we mainly explore the impact of higher education on economic growth, especially regarding the development of a green economy. Results show that (a) higher education plays a significant role in building a green economy, and (b) green GDP is more responsive to changes in higher education than the traditional GDP. This study provides empirical evidence for the substantial contribution that higher education makes in promoting green economic growth to achieve comprehensive sustainable development

Tool wear condition monitoring in milling process based on data fusion enhanced long short-term memory network under different cutting conditions

Tool wear condition monitoring (TCM) is essential for milling process to ensure the machining quality, and the long short-term memory network (LSTM) is a good choice for predicting tool wear value. However, the robustness of LSTM- based method is poor when cutting condition changes. A novel method based on data fusion enhanced LSTM is proposed to estimate tool wear value under different cutting conditions. Firstly, vibration time series signal collected from milling process are transformed to feature space through empirical mode decomposition, variational mode decomposition and fourier synchro squeezed transform. And then few feature series are selected by neighborhood component analysis to reduce dimension of the signal features. Finally, these selected feature series are input to train the bidirectional LSTM network and estimate tool wear value. Applications of the proposed method to milling TCM experiments demonstrate it outperforms significantly SVR- based and RNN- based methods under different cutting conditions

Image3_A bibliometric and scientific knowledge map study of the drug therapies for asthma-related study from 1982 to 2021.tif

Objective: Asthma drug research has been increasing yearly, and its clinical application value has increasingly attracted attention. This study aimed to analyze the development status, research hotspots, research frontiers, and future development trends of the research works on drugs for patients with asthma, especially severe asthma.Methods: Asthma drug-related articles published between 1982 and 2021 were retrieved from the Web of Science Core Collection (WOSCC) database, and only articles published in English were included. CiteSpace and VOSviewer software were utilized to conduct collaborative network analysis of countries/regions, institutions, keywords, and co-citation analysis of references.Results: A total of 3,234 asthma drug-related eligible articles were included. The United States was in a leading position, and Karolinska Institute (Sweden) was the most active institution. The most prolific journal in this field was Journal of Asthma, and the most cited journal was Journal of Allergy and Clinical Immunology. Keyword co-occurrence studies suggested that the current hotspots and frontiers were as follows: ① asthma: fully revealing the potential of existing conventional asthma drugs, determining the best drug delivery system, and indicating the best combination. To continue to explore potential targets for severe asthma or other phenotypes. Inhaled glucocorticoids and budesonide are still one of the important aspects of current asthma drug research and ② severe asthma: the research and development of new drugs, especially monoclonal antibodies including omalizumab, mepolizumab, and benralizumab to improve asthma control and drug safety, have become a research hotspot in recent years, highlighting the importance of “target” selection.Conclusion: This study demonstrates the global research hotspots and trends of the research works on drugs for patients with asthma/severe asthma. It can help scholars quickly understand the current status and hotspots of research in this field.</p