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검색결과 540건 처리시간 0.266초

Role of Hyperinsulinemia in Increased Risk of Prostate Cancer: A Case Control Study from Kathmandu Valley

  • Pandeya, Dipendra Raj;Mittal, Ankush;Sathian, Brijesh;Bhatta, Bibek
    • Asian Pacific Journal of Cancer Prevention
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    • 제15권2호
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    • pp.1031-1033
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    • 2014
  • Aim: To investigate the effect of hyperglycemia and hyperinsulinemia on prostate cancer risk. Materials and Methods: This hospital based study was carried out using data retrieved from the register maintained in the Department of Biochemistry of a tertiary care hospital of Kathmandu, Nepal between $31^{st}$ December, 2011 and $31^{st}$ October, 2013. The variables collected were age, serum cholesterol, serum calcium, PSA, fasting blood glucose, serum insulin. Analysis was performed by descriptive statistics and testing of hypothesis using Excel 2003, R 2.8.0, Statistical Package for the Social Sciences (SPSS) for Windows Version 16.0 (SPSS Inc; Chicago, IL, USA) and the EPI Info 3.5.1 Windows Version. Results: Of the total 125 subjects enrolled in our present study, 25 cases were of PCa and 100 were healthy controls. The mean value of fasting plasma glucose was 95.5 mg/dl in cases of prostatic carcinoma and the mean value of fasting plasma insulin was $5.78{\mu}U/ml$ (p value: 0.0001*). The fasting insulin levels ${\mu}U/ml$ were categorized into the different ranges starting from ${\leq}2.75$, >2.75 to ${\leq}4.10$, >4.10 to ${\leq}6.10$, > $6.10{\mu}U/ml$. The maximum number of cases of prostatic carcinoma of fasting insulin levels falls in range of > $6.10{\mu}U/ml$. The highest insulin levels (> $6.10{\mu}U/ml$) were seen to be associated with an 2.55 fold risk of prostatic carcinoma when compared with fasting insulin levels of (< $2.75{\mu}U/ml$). Conclusions: Elevated fasting levels of serum insulin appear to be associated with a higher risk of prostate cancer.

Genome re-sequencing to identify single nucleotide polymorphism markers for muscle color traits in broiler chickens

  • Kong, H.R.;Anthony, N.B.;Rowland, K.C.;Khatri, B.;Kong, B.C.
    • Asian-Australasian Journal of Animal Sciences
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    • 제31권1호
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    • pp.13-18
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    • 2018
  • Objective: Meat quality including muscle color in chickens is an important trait and continuous selective pressures for fast growth and high yield have negatively impacted this trait. This study was conducted to investigate genetic variations responsible for regulating muscle color. Methods: Whole genome re-sequencing analysis using Illumina HiSeq paired end read method was performed with pooled DNA samples isolated from two broiler chicken lines divergently selected for muscle color (high muscle color [HMC] and low muscle color [LMC]) along with their random bred control line (RAN). Sequencing read data was aligned to the chicken reference genome sequence for Red Jungle Fowl (Galgal4) using reference based genome alignment with NGen program of the Lasergene software package. The potential causal single nucleotide polymorphisms (SNPs) showing non-synonymous changes in coding DNA sequence regions were chosen in each line. Bioinformatic analyses to interpret functions of genes retaining SNPs were performed using the ingenuity pathways analysis (IPA). Results: Millions of SNPs were identified and totally 2,884 SNPs (1,307 for HMC and 1,577 for LMC) showing >75% SNP rates could induce non-synonymous mutations in amino acid sequences. Of those, SNPs showing over 10 read depths yielded 15 more reliable SNPs including 1 for HMC and 14 for LMC. The IPA analyses suggested that meat color in chickens appeared to be associated with chromosomal DNA stability, the functions of ubiquitylation (UBC) and quality and quantity of various subtypes of collagens. Conclusion: In this study, various potential genetic markers showing amino acid changes were identified in differential meat color lines, that can be used for further animal selection strategy.

Identification and Functional Analysis of Differentially Expressed Genes Related to Metastatic Osteosarcoma

  • Niu, Feng;Zhao, Song;Xu, Chang-Yan;Chen, Lin;Ye, Long;Bi, Gui-Bin;Tian, Gang;Gong, Ping;Nie, Tian-Hong
    • Asian Pacific Journal of Cancer Prevention
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    • 제15권24호
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    • pp.10797-10801
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    • 2015
  • Background: To explore the molecular mechanisms of metastatic osteosarcoma (OS) by using the microarray expression profiles of metastatic and non-metastatic OS samples. Materials and Methods: The gene expression profile GSE37552 was downloaded from Gene Expression Omnibus database, including 2 human metastatic OS cell line models and 2 two non-metastatic OS cell line models. The differentially expressed genes (DEGs) were identified by Multtest package in R language. In addition, functional enrichment analysis of the DEGs was performed by WebGestalt, and the protein-protein interaction (PPI) networks were constructed by Hitpredict, then the signal pathways of the genes involved in the networks were performed by Kyoto Encyclopaedia of Genes and Genomes (KEGG) automatic annotation server (KAAS). Results: A total of 237 genes were classified as DEGs in metastatic OS. The most significant up- and down-regulated genes were A2M (alpha-2-macroglobulin) and BCAN (brevican). The DEGs were significantly related to the response to hormone stimulus, and the PPI network of A2M contained IL1B (interleukin), LRP1 (low-density lipoprotein receptor-related protein 1) and PDGF (platelet-derived growth factor). Furthermore, the MAPK signaling pathway and focal adhesion were significantly enriched. Conclusions: A2M and its interactive proteins, such as IL1B, LRP1 and PDGF may be candidate target molecules to monitor, diagnose and treat metastatic OS. The response to hormone stimulus, MAPK signaling pathway and focal adhesion may play important roles in metastatic OS.

Identifying Differentially Expressed Genes and Small Molecule Drugs for Prostate Cancer by a Bioinformatics Strategy

  • Li, Jian;Xu, Ya-Hong;Lu, Yi;Ma, Xiao-Ping;Chen, Ping;Luo, Shun-Wen;Jia, Zhi-Gang;Liu, Yang;Guo, Yu
    • Asian Pacific Journal of Cancer Prevention
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    • 제14권9호
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    • pp.5281-5286
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    • 2013
  • Purpose: Prostate cancer caused by the abnormal disorderly growth of prostatic acinar cells is the most prevalent cancer of men in western countries. We aimed to screen out differentially expressed genes (DEGs) and explore small molecule drugs for prostate cancer. Materials and Methods: The GSE3824 gene expression profile of prostate cancer was downloaded from Gene Expression Omnibus database which including 21 normal samples and 18 prostate cancer cells. The DEGs were identified by Limma package in R language and gene ontology and pathway enrichment analyses were performed. In addition, potential regulatory microRNAs and the target sites of the transcription factors were screened out based on the molecular signature database. In addition, the DEGs were mapped to the connectivity map database to identify potential small molecule drugs. Results: A total of 6,588 genes were filtered as DEGs between normal and prostate cancer samples. Examples such as ITGB6, ITGB3, ITGAV and ITGA2 may induce prostate cancer through actions on the focal adhesion pathway. Furthermore, the transcription factor, SP1, and its target genes ARHGAP26 and USF1 were identified. The most significant microRNA, MIR-506, was screened and found to regulate genes including ITGB1 and ITGB3. Additionally, small molecules MS-275, 8-azaguanine and pyrvinium were discovered to have the potential to repair the disordered metabolic pathways, abd furthermore to remedy prostate cancer. Conclusions: The results of our analysis bear on the mechanism of prostate cancer and allow screening for small molecular drugs for this cancer. The findings have the potential for future use in the clinic for treatment of prostate cancer.

재표본 방법론을 활용한 베이지안 주파수 추정 (Bayesian estimation for frequency using resampling methods)

  • 박노진
    • 응용통계연구
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    • 제30권6호
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    • pp.877-888
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    • 2017
  • 시계열 자료의 주기를 파악하기 위해 스펙트럴 분석이 널리 이용되고 있다. 전력 스펙트럼이나 피리오도그램을 통해서 주파수를 추정하고 그로부터 순환 주기를 계산한다. 한편에서는 통계학의 한 축인 베이지안 기법을 활용한 주파수 추정법이 연구되어 사용되고 있다. 그런데 베이지안 주파수 추정량이 수학 공식을 통해 분석적으로 표현이 가능하지 않음으로 인해 신뢰구간 추정 같은 심도 깊은 통계학적 분석이 용이하지 않은 상화에서 컴퓨터를 이용한 수치해석적인 방법으로 신뢰구간을 추정하였다. 본 논문에서는 베이지안 주파수에 대한 보다 심도 있는 분석을 위해 모수를 재표본하는 Markov chain Monte Carlo (MCMC)을 이용한 추정과 데이터를 재표본하는 시계열 재표본을 통한 추정을 시도해 보았다. 예제로서 부동산 매매/전세 가격 지수 데이터을 사용하였고 매매와 전세 가격 지수간에 3.7개월 정도의 주기 차이가 존재하나 통계학적으로는 유의미한 차이라고 할 수 없음을 알았다.

근적외 분광분석법을 이용한 한국산과 미국산 잎담배의 판별분석

  • 장기철;김용옥;이경구
    • 한국연초학회지
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    • 제20권2호
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    • pp.191-197
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    • 1998
  • Discriminant analysis using near infrared spectra derived from Korean Flue-cured(KF) and American Flue-cured(AF), and also Korean Burley(KB) and American Burley(AB) tobacco was done to classify flue-cured and burley tobacco as either grown in Korea or grown in the USA. Samples were scanned in the wavelength of 400 ~ 2500 nm by near infrared analyzer(NIRSystem Co., model 6500). The discrimination equations for flue-cured and burley tobacco were developed using partial least square 2 method in Infrasoft International NIRS 3 software package. KF samples used for the development of the discrimination equations were higher contents of total sugar, crude ash and chlorine, and higher value of leaf density and brightness, but lower contents of nicotine, total nitrogen and ether extracts, and higher value of redness than those of AF samples. KB samples were higher contents of nicotine, crude ash and chlorine, but lower contents of ether extracts and value of brightness than those of AB samples. On 3 dimensional graph drawn with 3 principal component scores calculated with 3 principal component from KF and KB sample spectra, KF sample spectra were significantly different from AF, and also KB sample spectra were significantly different from AB. The discrimination equations of flue-cured and burley were developed with 3 principal component, respectively. The discrimination equations for flue-cured and burley had a standard error of 0.03 and 0.04, and a R2 of 0.88 and 0.84, respectively. The tobacco samples used for the development of discrimination equation were perfectly classified as KF and AF by flue-cured discrimination equation, and also perfectly classified KB and AB by burley discrimination equation, respectively. The correct classification rates of KF and AF samples not used for the development of discrimination equations were 9S % (828 out of 869 samples) and 98 % (98 out of 100 samples) by flue-cured discrimination equations, and KB and AB samples were 94%(345 out of 368 samples) and 100%(42 out of 42 samples) by burley discrimination equations, respectively.

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승용차량의 소음저감을 위한 시험과 시뮬레이션을 이용한 대시 시스템의 특성 연구 (Study on the Characteristics of a Dash System Based on Test and Simulation for Vehicle Noise Reduction)

  • 유지우;채기상;조진호
    • 한국소음진동공학회논문집
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    • 제22권11호
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    • pp.1071-1077
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    • 2012
  • Low frequency noises(up to about 200 Hz) such as booming are mainly caused by particular modes, and in general the solutions may be found based on mode controls where conventional methods such as FEM can be used. However, at higher frequencies between 0.3~1 kHz, as the number of modes rapidly increases, radiation characteristics from structures, performances of damping sheets and sound packages may be more crucial rather than particular modes, and consequently the conventional FEM may be less practical in dealing with this kinds of structure-borne problems. In this context, so-called 'mid-frequency simulation model' based on FE-SEA hybrid method is studied and validated to reduce noise in this frequency region. Energy transmission loss(i.e. air borne noise) is also studied. A dash panel component is chosen for this study, which is an important path that transmits both structure-borne and air borne energies into the cavity. Design modifications including structural modifications, attachment of damping sheets and application of different sound packages are taken into account and the corresponding noise characteristics are experimentally identified. It is found that the dash member behaves as a noise path. The damping sheet and sound packages have similar influences on both sound radiation and transmission loss. The comparison between experiments and simulations shows that this model could be used to predict the tendency of noise improvement.

고등학생들의 에이즈(후천성 면역 결핍증)에 대한 지식과 태도에 관한 연구 - K시 일부 고등학생 대상 - (A Study of the Knowledge, Attitude and Needs of AIDS Education of Senior High School Students)

  • 박인혜;윤현숙;한유정
    • 한국학교보건학회지
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    • 제9권2호
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    • pp.239-248
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    • 1996
  • This descriptive study was done to investigate the degree of knowledge and attitudes, the need of health education, and the relationship between knowledge and attitudes concerning AIDS in senior high school students. The data was collected from 386 senior high school students(200 boys, 180 girls) in K city. The data was gathered by a self reporting questionnaire, from Nov. 22nd to the 30th, 1995. Data was analyzed using the descriptive statistics methods: t-test, F-test, Pearson-Correlation Coefficient, GLM with the statistical computer package, SAS. The Result of this study were as follows : 1. The mean score of knowledge about AIDS was 42.70 from a total score of 58, showing significant differences between boys and girls (p<0.0001). 2. The mean score of attitudes about AIDS was 29.95 from a total score of 40, showing no significant differences between boys and girls. 3. The selected contents that the students want to learn were prevention, etiology, transmission, symptoms, and treatment of AIDS in that order. 4. The relationship between knowledge and attitude about AIDS show a positive correlation and is statistically significant(r=0.27, p<0.0001). The information obtained from this study will provi a useful data to develop a practical health education program about AIDS for senior high school students.

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RNAseq 빅데이터에서 유전자 선택을 위한 밀집도-의존 정규화 기반의 서포트-벡터 머신 병합법 (Combining Support Vector Machine Recursive Feature Elimination and Intensity-dependent Normalization for Gene Selection in RNAseq)

  • 김차영
    • 인터넷정보학회논문지
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    • 제18권5호
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    • pp.47-53
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    • 2017
  • 고처리 시퀀싱과 빅데이터 및 크라우드 컴퓨팅에 혁신이 일어나면서, RNA 시퀀싱도 획기적인 변화가 일어, RNAseq가 기존의 DNA 마이크로어레이를 대체하여, 빅-데이터를 형성하고 있다. 현재, RANseq 이용한 유전자 조절망(GRN) 까지 연구가 활성화 되고 있는데, 그 중 한 분야가 GRN의 기본 요소인 특징 유전자를 빅-데이터에서도 구별하고 기존에 알려진 것 외에 새로운 역할을 찾는 것이다. 그러나, 이러한 연구 방향에 부합하는 빅-데이터를 처리할 수 있는 컴퓨테이션 방법이 아직까지 매우 부족하다. 따라서 본 논문에서는 RNAseq 빅-데이터를 처리할 수 있도록 기존의 SVM-RFE알고리즘을 밀집도-의존 정규화에 병합하여, NCBI-GEO와 같은 빅-데이터에서 공개된 일부의 데이터에 개선된 알고리즘을 적용하고 해당 알고리즘에 의해 나온 결과의 성능을 평가한다.

역삼투압 해수담수화(SWRO) 플랜트에서 독립변수의 다중공선성을 고려한 예측모델에 관한 연구 (A Study on the Prediction Model Considering the Multicollinearity of Independent Variables in the Seawater Reverse Osmosis)

  • 한인섭;윤연아;장태우;김용수
    • 품질경영학회지
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    • 제48권1호
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    • pp.171-186
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    • 2020
  • Purpose: The purpose of this study is conducting of predictive models that considered multicollinearity of independent variables in order to carry out more efficient and reliable predictions about differential pressure in seawater reverse osmosis. Methods: The main variables of each RO system are extracted through factor analysis. Common variables are derived through comparison of RO system # 1 and RO system # 2. In order to carry out the prediction modeling about the differential pressure, which is the target variable, we constructed the prediction model reflecting the regression analysis, the artificial neural network, and the support vector machine in R package, and figured out the superiority of the model by comparing RMSE. Results: The number of factors extracted from factor analysis of RO system #1 and RO system #2 is same. And the value of variability(% Var) increased as step proceeds according to the analysis procedure. As a result of deriving the average RMSE of the models, the overall prediction of the SVM was superior to the other models. Conclusion: This study is meaningful in that it has been conducting a demonstration study of considering the multicollinearity of independent variables. Before establishing a predictive model for a target variable, it would be more accurate predictive model if the relevant variables are derived and reflected.