63 research outputs found

    Polymorphisms of the _ENPP1_ gene are not associated with type 2 diabetes or obesity in the Chinese Han population

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    *Objective:* Type 2 Diabetes mellitus is a metabolic disorder characterized by chronic hyperglycemia and with a major feature of insulin resistance. Genetic association studies have suggested that _ENPP1_ might play a potential role in susceptibility to type 2 diabetes and obesity. Our study aimed to examine the association between _ENPP1_ and type 2 diabetes and obesity.

*Design:* Association study between two SNPs, rs1044498 (K121Q) and rs7754561 of ENPP1 and diabetes and obesity in the Chinese Han population.

*Subjects:* 1912 unrelated patients (785 male and 1127 female with a mean age 63.8 ± 9 years), 236 IFG/IGT subjects (83 male and 153 female with a mean age 64 ± 9 years) and 2041 controls (635 male and 1406 female with a mean age 58 ± 9 years).
 
*Measurements:* Subjects were genotyped for two SNPs using TaqMan technology on an ABI7900 system and tested by regression analysis.

*Results:* By logistic regression analysis, rs1044498 (K121Q) and rs7754561 showed no statistical association with type 2 diabetes, obesity under additive, dominant and recessive models either before or after adjusting for sex and age. Haplotype analysis found a marginal association of haplotype C-G (p=0.05) which was reported in the previous study.

*Conclusion:* Our investigation did not replicated the positive association found previously and suggested that the polymorphisms of _ENPP1_ might not play a major role in the susceptibility to type 2 diabetes or obesity in the Chinese Han population

    Tianshengyuan-1 (TSY-1) regulates cellular Telomerase activity by methylation of TERT promoter.

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    Telomere and Telomerase have recently been explored as anti-aging and anti-cancer drug targets with only limited success. Previously we showed that the Chinese herbal medicine Tianshengyuan-1 (TSY-1), an agent used to treat bone marrow deficiency, has a profound effect on stimulating Telomerase activity in hematopoietic cells. Here, the mechanism of TSY-1 on cellular Telomerase activity was further investigated using HL60, a promyelocytic leukemia cell line, normal peripheral blood mononuclear cells, and CD34+ hematopoietic stem cells derived from umbilical cord blood. TSY-1 increases Telomerase activity in normal peripheral blood mononuclear cells and CD34+ hematopoietic stem cells with innately low Telomerase activity but decreases Telomerase activity in HL60 cells with high intrinsic Telomerase activity, both in a dose-response manner. Gene profiling analysis identified Telomerase reverse transcriptase (TERT) as the potential target gene associated with the TSY-1 effect, which was verified by both RT-PCR and western blot analysis. The β-galactosidase reporter staining assay showed that the effect of TSY-1 on Telomerase activity correlates with cell senescence. TSY-1 induced hypomethylation within TERT core promoter in HL60 cells but induced hypermethylation within TERT core promoter in normal peripheral blood mononuclear cells and CD34+ hematopoietic stem cells. TSY-1 appears to affect the Telomerase activity in different cell lines differently and the effect is associated with TERT expression, possibly via the methylation of TERT promoter

    Adaptive Locality Preserving Regression

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    This paper proposes a novel discriminative regression method, called adaptive locality preserving regression (ALPR) for classification. In particular, ALPR aims to learn a more flexible and discriminative projection that not only preserves the intrinsic structure of data, but also possesses the properties of feature selection and interpretability. To this end, we introduce a target learning technique to adaptively learn a more discriminative and flexible target matrix rather than the pre-defined strict zero-one label matrix for regression. Then a locality preserving constraint regularized by the adaptive learned weights is further introduced to guide the projection learning, which is beneficial to learn a more discriminative projection and avoid overfitting. Moreover, we replace the conventional `Frobenius norm' with the special l21 norm to constrain the projection, which enables the method to adaptively select the most important features from the original high-dimensional data for feature extraction. In this way, the negative influence of the redundant features and noises residing in the original data can be greatly eliminated. Besides, the proposed method has good interpretability for features owing to the row-sparsity property of the l21 norm. Extensive experiments conducted on the synthetic database with manifold structure and many real-world databases prove the effectiveness of the proposed method.Comment: The paper has been accepted by IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), and the code can be available at https://drive.google.com/file/d/1iNzONkRByIaUhXwdEhOkkh_0d2AAXNE8/vie

    PlantQTL-GE: a database system for identifying candidate genes in rice and Arabidopsis by gene expression and QTL information

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    We have designed and implemented a web-based database system, called PlantQTL-GE, to facilitate quantitatine traits locus (QTL) based candidate gene identification and gene function analysis. We collected a large number of genes, gene expression information in microarray data and expressed sequence tags (ESTs) and genetic markers from multiple sources of Oryza sativa and Arabidopsis thaliana. The system integrates these diverse data sources and has a uniform web interface for easy access. It supports QTL queries specifying QTL marker intervals or genomic loci, and displays, on rice or Arabidopsis genome, known genes, microarray data, ESTs and candidate genes and similar putative genes in the other plant. Candidate genes in QTL intervals are further annotated based on matching ESTs, microarray gene expression data and cis-elements in regulatory sequences. The system is freely available at

    Study on empirical model and CFD about pressure rising in Cab during door closure

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    Aiming at the problem that there is a strong eardrum pressure in the passenger car during the closing process, two analysis and prediction methods, fast formula prediction and CFD simulation based on accurate models, are proposed. The regression model of ear pressure comfort was established by DOE method and multiple linear regression; The simulation software star-CCM+ is applied to simulate and analyze the dynamic characteristics of the flow field in the cockpit during the closing process by using the overlapping grid technology, and the pressure change curve near the ear is obtained. Finally, the CFD numerical simulation model is established by comparing and analyzing the regression prediction analysis results and the real vehicle test data. The results show that the effects of closing speed, effective opening area of pressure relief valve and air tightness of the whole vehicle on the pressure of passengers’ eardrums decrease in turn, and the prediction error of multiple linear regression equation is 17 %; The analysis error of the internal flow field dynamic characteristic model based on refined modeling is 8 %. This study provides a theoretical basis for solving the problem of rapid prediction of eardrum pressure and optimization of engineering structure

    The Technology of Mould Steel for Online Pre-hardening

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    AbstractThis article describes a production method of mould steel pre-hardening, and focus on the advantage of this method, The technical core of method is the variable frequency and variable amplitude pulse uniform high-precision temperature control, which achieved by using strong-medium-weak water cooling, gas-water cooling and gas mist cooling composite cooling control technology. Optimizing the cooling rate path is a good method of optimizing quenched organization and structure

    Comparison of time trends in the incidence of primary liver cancer between China and the United States: an age–period–cohort analysis of the Global Burden of Disease 2019

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    BackgroundChina and the United States (US) ranked first and third in terms of new liver cancer cases and deaths globally in 2020. Therefore, a comprehensive assessment of trends in the incidence of primary liver cancer with four major etiological factors between China and the US during the past 30 years with age-period-cohort (APC) analyses is warranted.MethodsData were obtained from the Global Burden of Disease 2019, and period/cohort relative risks were estimated by APC modeling from 1990 to 2019.ResultsIn 2019, there were 211,000 new liver cancer cases in China and 28,000 in the US, accounting for 39.4% and 5.2% of global liver cancer cases, respectively. For China, the age-standardized incidence rate (ASIR) consecutively decreased before 2005 but increased slightly since then, whereas the ASIR continuously increased in the US. Among the four etiological factors of liver cancer, the fastest reduction in incidence was observed in hepatitis B virus-related liver cancer among Chinese women, and the fastest increase was in nonalcoholic steatosis hepatitis (NASH)-related liver cancer among American men. The greatest reduction in the incidence of liver cancer was observed at the age of 53 years in Chinese men (-5.2%/year) and 33 years in Chinese women (-6.6%/year), while it peaked at 58 years old in both American men and women (4.5%/year vs . 2.8%/year). Furthermore, the period risks of alcohol- and NASH-related liver cancer among Chinese men have been elevated since 2013. Simultaneously, leveled- off period risks were observed in hepatitis C viral-related liver cancer in both American men and women.ConclusionsCurrently, both viral and lifestyle factors have been and will continue to play an important role in the time trends of liver cancer in both countries. More tailored and efficient preventive strategies should be designed to target both viral and lifestyle factors to prevent and control liver cancer
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