90 research outputs found

    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

    The Value of VTTQ Combined with B-mode US for Distinguishing Benign from Malignant Breast Masses by Comparing with SE: A Clinical Research

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    Objective The purpose of this study was to compare the diagnostic performance of virtual touch tissue quantification (VTTQ) combined with B-mode ultrasonograpgy (US), strain elastography (SE) combined with B-mode US and B-mode US alone in differentiating the properties of breast lesions. Methods A retrospective database was queried for 283 healthy subjects and 100 consecutive patients with 130 breast lesions. All the cases were examined by B-mode US, VTTQ and SE. Histological diagnosis was used as the reference standard. The area under the receiver operating curve (AUC) values of each data set was compared.Results Twenty-two lesions were determined as malignant and 108 as benign. The best cutoff point of VTTQ was 7.82 m/s. The AUC of B-mode US combined with VTTQ or SE was greater than that of B-mode US alone (0.913 or 0.918 vs. 0.797) (P = 0.007 and 0.012).Conclusion Both VTTQ and SE could give help to B-mode US in distinguishing benign from malignant breast lesions about elastography values. There was no difference between them

    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

    Automatically Recognizing Medication and Adverse Event Information From Food and Drug Administration\u27s Adverse Event Reporting System Narratives

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    BACKGROUND: The Food and Drug Administration\u27s (FDA) Adverse Event Reporting System (FAERS) is a repository of spontaneously-reported adverse drug events (ADEs) for FDA-approved prescription drugs. FAERS reports include both structured reports and unstructured narratives. The narratives often include essential information for evaluation of the severity, causality, and description of ADEs that are not present in the structured data. The timely identification of unknown toxicities of prescription drugs is an important, unsolved problem. OBJECTIVE: The objective of this study was to develop an annotated corpus of FAERS narratives and biomedical named entity tagger to automatically identify ADE related information in the FAERS narratives. METHODS: We developed an annotation guideline and annotate medication information and adverse event related entities on 122 FAERS narratives comprising approximately 23,000 word tokens. A named entity tagger using supervised machine learning approaches was built for detecting medication information and adverse event entities using various categories of features. RESULTS: The annotated corpus had an agreement of over .9 Cohen\u27s kappa for medication and adverse event entities. The best performing tagger achieves an overall performance of 0.73 F1 score for detection of medication, adverse event and other named entities. C ONCLUSIONS: In this study, we developed an annotated corpus of FAERS narratives and machine learning based models for automatically extracting medication and adverse event information from the FAERS narratives. Our study is an important step towards enriching the FAERS data for postmarketing pharmacovigilance

    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
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