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Find video protocols related to scientific articles indexed in Pubmed.
Population-based cohort study on the risk of malignancy in East Asian children with juvenile idiopathic arthritis.
BMC Cancer
PUBLISHED: 08-29-2014
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To investigate the association and magnitude of risk between JIA, its associated treatment and cancer development in Taiwanese children.
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Acarbose treatment and the risk of cardiovascular disease in type 2 diabetic patients: a nationwide seven-year follow-up study.
J Diabetes Res
PUBLISHED: 04-30-2014
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To investigate the potential benefits of acarbose treatment on cardiovascular disease (CVD) in patients with type 2 diabetes by using nationwide insurance claim dataset.
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Comorbidities of pediatric systemic lupus erythematosus: A 6-year nationwide population-based study.
J Microbiol Immunol Infect
PUBLISHED: 04-14-2014
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Systemic lupus erythematous (SLE) is a systemic and complex disease that can involve multiple organs. To clarify the risk of developing associated comorbidities after a diagnosis of SLE in children, we used the National Health Insurance Research Database (NHIRD) in Taiwan to investigate diseases experienced in these patients. This is the first nationwide population-based study of the comorbidities of pediatric SLE patients.
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A novel approach for discovering condition-specific correlations of gene expressions within biological pathways by using cloud computing technology.
Biomed Res Int
PUBLISHED: 01-22-2014
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Microarrays are widely used to assess gene expressions. Most microarray studies focus primarily on identifying differential gene expressions between conditions (e.g., cancer versus normal cells), for discovering the major factors that cause diseases. Because previous studies have not identified the correlations of differential gene expression between conditions, crucial but abnormal regulations that cause diseases might have been disregarded. This paper proposes an approach for discovering the condition-specific correlations of gene expressions within biological pathways. Because analyzing gene expression correlations is time consuming, an Apache Hadoop cloud computing platform was implemented. Three microarray data sets of breast cancer were collected from the Gene Expression Omnibus, and pathway information from the Kyoto Encyclopedia of Genes and Genomes was applied for discovering meaningful biological correlations. The results showed that adopting the Hadoop platform considerably decreased the computation time. Several correlations of differential gene expressions were discovered between the relapse and nonrelapse breast cancer samples, and most of them were involved in cancer regulation and cancer-related pathways. The results showed that breast cancer recurrence might be highly associated with the abnormal regulations of these gene pairs, rather than with their individual expression levels. The proposed method was computationally efficient and reliable, and stable results were obtained when different data sets were used. The proposed method is effective in identifying meaningful biological regulation patterns between conditions.
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Allopurinol therapy in gout patients does not associate with beneficial cardiovascular outcomes: a population-based matched-cohort study.
PLoS ONE
PUBLISHED: 01-01-2014
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Previous studies have shown an association between gout and/or hyperuricemia and a subsequent increase in cardiovascular disease (CVD) outcomes. Allopurinol reduces vascular oxidative stress, ameliorates inflammatory state, improves endothelial function, and prevents atherosclerosis progression. Accordingly, we tested the hypothesis that a positive association between allopurinol therapy in gout patients and future cardiovascular outcomes is present using a population-based matched-cohort study design.
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Reappraisal of the etiology of extracorpuscular non-autoimmune acquired hemolytic anemia in 2657 hospitalized patients with non-neoplastic disease.
Clin Med Insights Pathol
PUBLISHED: 01-01-2014
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Unlike autoimmune hemolytic anemia (AIHA), literature on the etiological study of non-autoimmune hemolytic anemia (non-AIHA) is scarce. The incidence and prevalence of non-AIHA in different geographic regions are largely unknown perhaps owing to the lack of perspective investigation and different profiles of etiologies from different geographic regions. We aimed to examine the real-world etiology or mechanisms of the non-hereditary non-AIHA from a nationwide population-based administrative claim database in Taiwan.
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Effects of statins on incident dementia in patients with type 2 DM: a population-based retrospective cohort study in Taiwan.
PLoS ONE
PUBLISHED: 01-01-2014
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Patients with Type 2 diabetes (T2DM) are prone to develop dementia. Results from a recent study indicated that statin users had lower chance of developing incident dementia. However there is little information on the potential benefits of statin use on dementia in patients with T2DM cohort.
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An enhanced computational platform for investigating the roles of regulatory RNA and for identifying functional RNA motifs.
BMC Bioinformatics
PUBLISHED: 01-21-2013
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Functional RNA molecules participate in numerous biological processes, ranging from gene regulation to protein synthesis. Analysis of functional RNA motifs and elements in RNA sequences can obtain useful information for deciphering RNA regulatory mechanisms. Our previous work, RegRNA, is widely used in the identification of regulatory motifs, and this work extends it by incorporating more comprehensive and updated data sources and analytical approaches into a new platform.
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Burden of systemic lupus erythematosus in Taiwan: a population-based survey.
Rheumatol. Int.
PUBLISHED: 01-12-2013
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This population-based study aimed to determine the trend of incidence, prevalence, and mortality of systemic lupus erythematosus (SLE) in a 6-year period in Taiwan. Patients with international classification of diseases ninth revision (ICD-9) code 710.0 were retrieved from the Taiwanese National Health Insurance Research Database (NHIRD), which covered more than 96 % of the entire population, and from the Ministry of Interior between 2003 and 2008 in Taiwan. Patients with SLE registered as catastrophic illness were enrolled for analysis. The incidence rate, prevalence ratio, and mortality rate stratified by sex and age were analyzed. There were a total of 6,675 SLE patients (5,836 females and 839 in males) during the study period. The average annual incidence rate was 4.87 per 100,000 population, and the average female-to-male incidence ratio was 7.15. The ratio increased with age and peaked at the age of 40-49 years, then decreased thereafter. The incidence rate decreased by 4.2 % per year. The highest incidence rate was noted in the 20-29-year-old age group in females and the 70-79-year-old age group in males. The average prevalence and mortality rates were 97.5 and 1.2 per 100,000 population, respectively. Mortality was 3.2 % in patients diagnosed within 1 year and is more prevalent in young patients with average age of 15.6 years. Incidence rate of SLE has been declining in recent years but the prevalence rate has remained steady. The highest mortality rate is among younger patients diagnosed with SLE within 1 year.
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EuLoc: a web-server for accurately predict protein subcellular localization in eukaryotes by incorporating various features of sequence segments into the general form of Chous PseAAC.
J. Comput. Aided Mol. Des.
PUBLISHED: 01-03-2013
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The function of a protein is generally related to its subcellular localization. Therefore, knowing its subcellular localization is helpful in understanding its potential functions and roles in biological processes. This work develops a hybrid method for computationally predicting the subcellular localization of eukaryotic protein. The method is called EuLoc and incorporates the Hidden Markov Model (HMM) method, homology search approach and the support vector machines (SVM) method by fusing several new features into Chous pseudo-amino acid composition. The proposed SVM module overcomes the shortcoming of the homology search approach in predicting the subcellular localization of a protein which only finds low-homologous or non-homologous sequences in a protein subcellular localization annotated database. The proposed HMM modules overcome the shortcoming of SVM in predicting subcellular localizations using few data on protein sequences. Several features of a protein sequence are considered, including the sequence-based features, the biological features derived from PROSITE, NLSdb and Pfam, the post-transcriptional modification features and others. The overall accuracy and location accuracy of EuLoc are 90.5 and 91.2 %, respectively, revealing a better predictive performance than obtained elsewhere. Although the amounts of data of the various subcellular location groups in benchmark dataset differ markedly, the accuracies of 12 subcellular localizations of EuLoc range from 82.5 to 100 %, indicating that this tool is much more balanced than other tools. EuLoc offers a high, balanced predictive power for each subcellular localization. EuLoc is now available on the web at http://euloc.mbc.nctu.edu.tw/.
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Gender differences in colorectal cancer during the past 20 years in Taiwan.
Int J Colorectal Dis
PUBLISHED: 10-04-2011
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Gender differences in colorectal cancer (CRC) incidence have been previously reported. We designed this population-based study to determine if this gender difference was restricted to specific patient subgroups.
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Identifying transcriptional start sites of human microRNAs based on high-throughput sequencing data.
Nucleic Acids Res.
PUBLISHED: 08-05-2011
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MicroRNAs (miRNAs) are critical small non-coding RNAs that regulate gene expression by hybridizing to the 3-untranslated regions (3-UTR) of target mRNAs, subsequently controlling diverse biological processes at post-transcriptional level. How miRNA genes are regulated receives considerable attention because it directly affects miRNA-mediated gene regulatory networks. Although numerous prediction models were developed for identifying miRNA promoters or transcriptional start sites (TSSs), most of them lack experimental validation and are inadequate to elucidate relationships between miRNA genes and transcription factors (TFs). Here, we integrate three experimental datasets, including cap analysis of gene expression (CAGE) tags, TSS Seq libraries and H3K4me3 chromatin signature derived from high-throughput sequencing analysis of gene initiation, to provide direct evidence of miRNA TSSs, thus establishing an experimental-based resource of human miRNA TSSs, named miRStart. Moreover, a machine-learning-based Support Vector Machine (SVM) model is developed to systematically identify representative TSSs for each miRNA gene. Finally, to demonstrate the effectiveness of the proposed resource, an important human intergenic miRNA, hsa-miR-122, is selected to experimentally validate putative TSS owing to its high expression in a normal liver. In conclusion, this work successfully identified 847 human miRNA TSSs (292 of them are clustered to 70 TSSs of miRNA clusters) based on the utilization of high-throughput sequencing data from TSS-relevant experiments, and establish a valuable resource for biologists in advanced research in miRNA-mediated regulatory networks.
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Characterization and prediction of mRNA polyadenylation sites in human genes.
Med Biol Eng Comput
PUBLISHED: 01-02-2011
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The accurate identification of potential poly(A) sites has contributed to all many studies with regard to alternative polyadenylation. The aim of this study was the development of a machine-learning methodology that will help to discriminate real polyadenylation signals from randomly occurring signals in genomic sequence. Since previous studies have revealed that RNA secondary structure in certain genes has significant impact, the authors tried to computationally pinpoint common structural patterns around the poly(A) sites and to investigate how RNA secondary structure may influence polyadenylation. This involved an initial study on the impact of RNA structure and it was found using motif search tools that hairpin structures might be important. Thus, it was propose that, in addition to the sequence pattern around poly(A) sites, there exists a widespread structural pattern that is also employed during human mRNA polyadenylation. In this study, the authors present a computational model that uses support vector machines to predict human poly(A) sites. The results show that this predictive model has a comparable performance to the current prediction tool. In addition, it was identified common structural patterns associated with polyadenylation using several motif finding programs and this provides new insight into the role of RNA secondary structure plays in polyadenylation.
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A novel preprocessing method using Hilbert Huang Transform for MALDI-TOF and SELDI-TOF mass spectrometry data.
PLoS ONE
PUBLISHED: 08-05-2010
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Mass spectrometry is a high throughput, fast, and accurate method of protein analysis. Using the peaks detected in spectra, we can compare a normal group with a disease group. However, the spectrum is complicated by scale shifting and is also full of noise. Such shifting makes the spectra non-stationary and need to align before comparison. Consequently, the preprocessing of the mass data plays an important role during the analysis process. Noises in mass spectrometry data come in lots of different aspects and frequencies. A powerful data preprocessing method is needed for removing large amount of noises in mass spectrometry data.
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A computation to integrate the analysis of genetic variations occurring within regulatory elements and their possible effects.
J. Comput. Biol.
PUBLISHED: 12-28-2009
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Single nucleotide polymorphisms (SNPs) and short tandem repeats (STRs) are the most common genetic variations, are widespread within genomes, and form the diversity within species. These genetic variations affect many regulatory elements such as transcription factor binding sites (TFBSs), DNA methylation sites on CpG islands, and microRNA target sites; these elements have been found to play major as well as indirect roles in regulating gene expression. Currently, systems are available to display such genetic variation occurring within regulatory elements. To understand and display all the potential variation described above, we have developed a web-based system tool, the Regulatory Element and Genetic Variation Viewer (REGV Viewer [REGV]), which provides a friendly web interface for users and shows genetic variation information within regulatory elements by either inputting a gene list or selecting a chromosome by name. Moreover, our tool not only supports logic operation queries, but after a query is submitted, it also shows a high-throughput simulation, including combined data, statistical graphs, and graphical views of the genetic variants and regulatory elements. Additionally, when the SNP variation occurs within TFBSs and if the SNP allele frequency and TFBS position weight matrices (PWMs) are available, our system will show the new putative TFBSs resulting from the SNP variation.
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Computational identification of riboswitches based on RNA conserved functional sequences and conformations.
RNA
PUBLISHED: 05-21-2009
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Riboswitches are cis-acting genetic regulatory elements within a specific mRNA that can regulate both transcription and translation by interacting with their corresponding metabolites. Recently, an increasing number of riboswitches have been identified in different species and investigated for their roles in regulatory functions. Both the sequence contexts and structural conformations are important characteristics of riboswitches. None of the previously developed tools, such as covariance models (CMs), Riboswitch finder, and RibEx, provide a web server for efficiently searching homologous instances of known riboswitches or considers two crucial characteristics of each riboswitch, such as the structural conformations and sequence contexts of functional regions. Therefore, we developed a systematic method for identifying 12 kinds of riboswitches. The method is implemented and provided as a web server, RiboSW, to efficiently and conveniently identify riboswitches within messenger RNA sequences. The predictive accuracy of the proposed method is comparable with other previous tools. The efficiency of the proposed method for identifying riboswitches was improved in order to achieve a reasonable computational time required for the prediction, which makes it possible to have an accurate and convenient web server for biologists to obtain the results of their analysis of a given mRNA sequence. RiboSW is now available on the web at http://RiboSW.mbc.nctu.edu.tw/.
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Incorporating support vector machine for identifying protein tyrosine sulfation sites.
J Comput Chem
PUBLISHED: 04-18-2009
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Tyrosine sulfation is a post-translational modification of many secreted and membrane-bound proteins. It governs protein-protein interactions that are involved in leukocyte adhesion, hemostasis, and chemokine signaling. However, the intrinsic feature of sulfated protein remains elusive and remains to be delineated. This investigation presents SulfoSite, which is a computational method based on a support vector machine (SVM) for predicting protein sulfotyrosine sites. The approach was developed to consider structural information such as concerning the secondary structure and solvent accessibility of amino acids that surround the sulfotyrosine sites. One hundred sixty-two experimentally verified tyrosine sulfation sites were identified using UniProtKB/SwissProt release 53.0. The results of a five-fold cross-validation evaluation suggest that the accessibility of the solvent around the sulfotyrosine sites contributes substantially to predictive accuracy. The SVM classifier can achieve an accuracy of 94.2% in five-fold cross validation when sequence positional weighted matrix (PWM) is coupled with values of the accessible surface area (ASA). The proposed method significantly outperforms previous methods for accurately predicting the location of tyrosine sulfation sites.
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Incorporating structural characteristics for identification of protein methylation sites.
J Comput Chem
PUBLISHED: 03-06-2009
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Studies over the last few years have identified protein methylation on histones and other proteins that are involved in the regulation of gene transcription. Several works have developed approaches to identify computationally the potential methylation sites on lysine and arginine. Studies of protein tertiary structure have demonstrated that the sites of protein methylation are preferentially in regions that are easily accessible. However, previous studies have not taken into account the solvent-accessible surface area (ASA) that surrounds the methylation sites. This work presents a method named MASA that combines the support vector machine with the sequence and structural characteristics of proteins to identify methylation sites on lysine, arginine, glutamate, and asparagine. Since most experimental methylation sites are not associated with corresponding protein tertiary structures in the Protein Data Bank, the effective solvent-accessible prediction tools have been adopted to determine the potential ASA values of amino acids in proteins. Evaluation of predictive performance by cross-validation indicates that the ASA values around the methylation sites can improve the accuracy of prediction. Additionally, an independent test reveals that the prediction accuracies for methylated lysine and arginine are 80.8 and 85.0%, respectively. Finally, the proposed method is implemented as an effective system for identifying protein methylation sites. The developed web server is freely available at http://MASA.mbc.nctu.edu.tw/.
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Diabetic patients with severe sepsis admitted to intensive care unit do not fare worse than non-diabetic patients: a nationwide population-based cohort study.
PLoS ONE
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We sought to examine whether type 2 diabetes increases the risk of acute organ dysfunction and of hospital mortality following severe sepsis that requires admission to an intensive care unit (ICU).
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Gout and subsequent increased risk of cardiovascular mortality in non-diabetics aged 50 and above: a population-based cohort study in Taiwan.
BMC Cardiovasc Disord
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Limited data are available on the risk ratios for fatal cardiovascular disease (CVD) outcome from gout and chronic kidney disease (CKD) in non-diabetic individuals.
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Evaluation of the appropriate age range of colorectal cancer screening based on the changing epidemiology in the past 20 years in taiwan.
ISRN Gastroenterol
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Introduction. According to the recommendation of the United States Preventative Services Task Force, most countries provide average-risk screening for colorectal cancers (CRCs) between the ages of 50 and 75 years. However, the age range of screening should be modified because of an increasing life span. Methods. Totally 124,314 CRC cases were registered in Taiwan Cancer Registry from 1988 to 2007. The 20-year study period was divided into four 5-year increments. We divided the patients into four age groups (under age 50, age 50-74, age 74-84, and over age 85) in each increment to determine whether there were changes in the age distribution. Results. In the subgroup of patients under age 50, the number of CRC cases increased, but they accounted for a decreasing proportion of the total CRCs. In the 50-74 age group, the proportion of CRC cases also dropped. In contrast, the proportion increased in the 75-84 age group. Therefore, 43.63% of CRC patients would not be delegated to screen in the period of 2003-2007 if the CRC screening were restricted in the 50-74 age group. Conclusions. CRC screening for healthy individuals aged over 75 years is necessary.
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Metachronous colorectal cancer in Taiwan: analyzing 20 years of data from Taiwan Cancer Registry.
Int. J. Clin. Oncol.
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The risk of metachronous colorectal cancer in patients with colorectal cancer is higher than the rate of sporadic colorectal cancer in the average population. We conducted a large-scale, population-based study, with many more clinical cases than in previously published studies, to calculate the incidence of metachronous colorectal cancer.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.