Comparative analysis of 3D-culture system for murine neonatal heart regeneration: a systematic approach for big gene expression data

[[abstract]]Cardiovascular diseases are the leading cause of death worldwide. Loss or dysfunction of cardiomyocytes is associated with many forms of heart disease. The adult mammalian heart has a limited regenerative ability after damage, leading to the formation of fibrotic scar tissues, hypertrophy, contractile dysfunction and ul-timately, organ failure. In contrast, neonatal mammalian cardiomyocytes retain a significant replenishing potential briefly after birth. There is increasing enthusiasm to grow neonatal cardiomyocytes in 3D culture systems to artificially restore heart function. Various scaffolds and matrices are available, but the molecular and cellu-lar mechanisms underlying proliferation and differentiation of neonatal mammalian cardiomyocytes are not very well understood. Here, we utilize a systematic strategy to analyze the extensive genome-scale gene expression profiles of two different 3D constructs. We present a comprehensive comparison that may help improve the protocols for growing cardiomyocytes in a 3D culture system.[[notice]]補正完畢[[incitationindex]]EI[[conferencetype]]國際[[conferencedate]]20140513~20140516[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Tainan, Taiwa

Myocardial Infarction Classification by Morphological Feature Extraction from Big 12-Lead ECG Data

[[abstract]]Rapid and accurate diagnosis of patients with acute myocardial infarction is vital. The ST segment in Electrocardiography (ECG) represents the change of electric potential during the period from the end of ventricular depolarization to the beginning of repolarization and plays an important role in the detection of myocardial infarction. However, ECG monitoring generates big volumes of data and the underlying complexity must be extracted by a combination of methods. This study combines the advantages of polynomial approximation and principal component analysis. The proposed approach is stable for the 12-lead ECG data collected from the PTB database and achieves an accuracy of 98.07%.[[notice]]補正完畢[[incitationindex]]EI[[conferencetype]]國際[[conferencedate]]20140513~20140516[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Tainan, Taiwa

Cluster-based Classification of Diabetic Nephropathy among Type 2

[[abstract]]The prevalence of type 2 diabetes is increasing at an alarming rate. Various complications are associated with type 2 diabetes, with diabetic nephropathy being the leading cause of renal failure among diabetics. Often, when patients are diagnosed with diabetic nephropathy, their renal functions have already been significantly damaged, speeding up the progression towards end stage renal disease. Therefore, a risk prediction tool may be beneficial for the implementation of early treatment and prevention. In the present study, we propose to develop a prediction model integrating clustering and classification approaches for the identification of diabetic nephropathy among type 2 diabetes patients. Clinical and genotyping data are obtained from 345 type 2 diabetic patients(160 with non-diabetic nephropathy and 185 with diabetic nephropathy). The performance of using clinical features alone for cluster-based classification is compared with that of utilizing a combination of clinical and genetic attributes. We find that the inclusion of genetic features yield better prediction results. Further refinement of the proposed approach has the potential to facilitate the accurate identification of diabetic nephropathy and the development of better treatment in a clinical setting.[[incitationindex]]EI[[conferencetype]]國際[[conferencedate]]20140507~2014009[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Kyoto, Japa

SOHSite: incorporating evolutionary information and physicochemical properties to identify protein S-sulfenylation sites

Distribution of KEGG pathway annotations for S-sulfenylated proteins. (DOCX 15 kb

Gene Expression Profiling of Biological Pathway Alterations by Radiation Exposure

[[abstract]]Though damage caused by radiation has been the focus of rigorous research, the mechanisms through which radiation exerts harmful effects on cells are complex and not well-understood. In particular, the influence of low dose radiation exposure on the regulation of genes and pathways remains unclear. In an attempt to investigate the molecular alterations induced by varying doses of radiation, a genome-wide expression analysis was conducted. Peripheral blood mononuclear cells were collected from five participants and each sample was subjected to 0.5 Gy, 1 Gy, 2.5 Gy, and 5 Gy of cobalt 60 radiation, followed by array-based expression profiling. Gene set enrichment analysis indicated that the immune system and cancer development pathways appeared to be the major affected targets by radiation exposure. Therefore, 1 Gy radioactive exposure seemed to be a critical threshold dosage. In fact, after 1 Gy radiation exposure, expression levels of several genes including FADD, TNFRSF10B, TNFRSF8, TNFRSF10A, TNFSF10, TNFSF8, CASP1, and CASP4 that are associated with carcinogenesis and metabolic disorders showed significant alterations. Our results suggest that exposure to low-dose radiation may elicit changes in metabolic and immune pathways, potentially increasing the risk of immune dysfunctions and metabolic disorders.[[notice]]補正完畢[[incitationindex]]SCI[[incitationindex]]EI[[booktype]]電子

Construction of a Prediction Model for Nephropathy among Obese Patients Using Genetic and Clinical Features

[[abstract]]Obesity is a complex disease arising from an excessive accumula-tion of body fat which leads to various complications such as diabetes, hyper-tension, and renal diseases. The growing prevalence of obesity is also becom-ing a major risk factor for nephropathy. When patients are diagnosed with nephropathy, their progression towards renal failure is usually inevitable. Therefore, a prediction tool will help medical doctors identify patients with a higher risk of developing nephropathy and implement early treatment or pre-vention. In this study, we attempted to construct a diagnostic support system for nephropathy using clinical and genetic traits. Our results show that pre-diction models involving the use of both genetic and clinical features yielded the best classification performance. Our finding is in accordance with the complex nature of obesity-related nephropathy and support the notion of us-ing genetic traits to design a personalized diagnostic model.[[notice]]補正完畢[[conferencetype]]國際[[conferencedate]]20150519~20150522[[booktype]]紙本[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Ho Chi Minh City, Vietna

Metagenome and Metatranscriptome Profiling of Moderate and Severe COPD Sputum in Taiwanese Han Males

<div><p>Chronic obstructive pulmonary disease (COPD) is an inflammatory lung disorder characterized by the progressive obstruction of airflow and is currently the fourth leading cause of death in the world. The pathogenesis of COPD is thought to involve bacterial infections and inflammations. Owing to advancement in sequencing technology, evidence is emerging that supports an association between the lung microbiome and COPD. However, few studies have looked into the expression profile of the bacterial communities in the COPD lungs. In this study, we analyzed the sputum microbiome of four moderate and four severe COPD male patients both at the DNA and RNA level, using next generation sequencing technology. We found that bacterial composition determined by 16S rRNA gene sequencing may not directly translate to the set of actively expressing bacteria as defined by transcriptome sequencing. The two sequencing data agreed on <i>Prevotella</i>, <i>Rothia</i>, <i>Neisseria</i>, <i>Porphyromonas</i>, <i>Veillonella</i>, <i>Fusobacterium</i> and <i>Streptococcus</i> being among the most differentially abundant genera between the moderate and severe COPD samples, supporting their association with COPD severity. However, the two sequencing analyses disagreed on the relative abundance of these bacteria in the two COPD groups, implicating the importance of studying the actively expressing bacteria for enriching our understanding of COPD. Though we have described the metatranscriptome profiles of the lung microbiome in moderate and severe COPD, further investigations are required to determine the functional basis underlying the relationship between the microbial species in the lungs and pathogenesis of COPD.</p></div

Analytical flow of our study.

<p>Analytical flow of our study.</p

Metatranscriptome sequencing results for the bacterial metagenome in the sputum of moderate and severe COPD subjects.

<p>Metatranscriptome sequencing results for the bacterial metagenome in the sputum of moderate and severe COPD subjects.</p

Top 10 genera showing the most difference in relative sequence abundance at the genus level in the moderate and severe patients.

<p>A) Top 10 most different genera in relative 16S rRNA sequence abundance. B) Top 10 most different genera in relative transcript sequence abundance.</p