Wireless machine-to-machine networks 2013

Editoria

Comparison and Identification of Estrogen-Receptor Related Gene Expression Profiles in Breast Cancer of Different Ethnic Origins

The interactions between genetic variants in estrogen receptor (ER) have been identified to be associated with an increased risk of breast cancer. Available evidence indicates that genetic variance within a population plays a crucial role in the occurrence of breast cancer. Thus, the comparison and identification of ER-related gene expression profiles in breast cancer of different ethnic origins could be useful for the development of genetic variant cancer therapy. In this study, we performed microarray experiment to measure the gene expression profiles of 59 Taiwanese breast cancer patients; and through comparative bioinformatics analysis against published U.K. datasets, we revealed estrogen-receptor (ER) related gene expression between Taiwanese and British patients. In addition, SNP databases and statistical analysis were used to elucidate the SNPs associated with ER status. Our microarray results indicate that the expression pattern of the 65 genes in ER+ patients was dissimilar from that of the ER- patients. Seventeen mutually exclusive genes in ER-related breast cancer of the two populations with more than one statistically significant SNP in genotype and allele frequency were identified. These 17 genes and their related SNPs may be important in population-specific ER regulation of breast cancer. This study provides a global and feasible approach to study population-unique SNPs in breast cancer of different ethnic origins

Fibronectin and laminin promote differentiation of human mesenchymal stem cells into insulin producing cells through activating Akt and ERK

<p>Abstract</p> <p>Background</p> <p>Islet transplantation provides a promising cure for Type 1 diabetes; however it is limited by a shortage of pancreas donors. Bone marrow-derived multipotent mesenchymal stem cells (MSCs) offer renewable cells for generating insulin-producing cells (IPCs).</p> <p>Methods</p> <p>We used a four-stage differentiation protocol, containing neuronal differentiation and IPC-conversion stages, and combined with pellet suspension culture to induce IPC differentiation.</p> <p>Results</p> <p>Here, we report adding extracellular matrix proteins (ECM) such as fibronectin (FN) or laminin (LAM) enhances pancreatic differentiation with increases in insulin and Glut2 gene expressions, proinsulin and insulin protein levels, and insulin release in response to elevated glucose concentration. Adding FN or LAM induced activation of Akt and ERK. Blocking Akt or ERK by adding LY294002 (PI3K specific inhibitor), PD98059 (MEK specific inhibitor) or knocking down Akt or ERK failed to abrogate FN or LAM-induced enhancement of IPC differentiation. Only blocking both of Akt and ERK or knocking down Akt and ERK inhibited the enhancement of IPC differentiation by adding ECM.</p> <p>Conclusions</p> <p>These data prove IPC differentiation by MSCs can be modulated by adding ECM, and these stimulatory effects were mediated through activation of Akt and ERK pathways.</p

Associations between child maltreatment, PTSD, and internet addiction among Taiwanese students

AbstractThis study examines (1) the associations between multiple types of child maltreatment and Internet addiction, and (2) the mediating effects of post-traumatic stress disorder (PTSD) on these associations. We collected data from a national proportionately stratified random sample of 6233 fourth-grade students in Taiwan in 2014. We conducted bivariate correlations and sets of multiple regression analyses to examine the associations between multiple types of maltreatment (5 types in total) and Internet addiction, and to identify the mediating role of PTSD. The results reveal that being male and experiencing abuse (psychological neglect, physical neglect, paternal physical violence, sexual violence) were associated with increased risk among children of developing PTSD and Internet addiction. Moreover, PTSD mediated the associations between multiple types of maltreatment (except maternal physical violence) and Internet addiction. This study demonstrates (1) the effects of multiple types of maltreatment on the PTSD and Internet addiction of children and (2) the importance of early prevention and intervention in addressing related public-health concerns

Major Functional Transcriptome of an Inferred Center Regulator of an ER(−) Breast Cancer Model System

We aimed to find clinically relevant gene activities ruled by the signal transducer and activator of transcription 3 (STAT3) proteins in an ER(−) breast cancer population via network approach. STAT3 is negatively associated with both lymph nodal category and stage. MYC is a component of STAT3 network. MYC and STAT3 may co-regulate gene expressions for Warburg effect, stem cell like phenotype, cell proliferation and angiogenesis. We identified a STAT3 network in silico showing its ability in predicting its target gene expressions primarily for specific tumor subtype, tumor progression, treatment options and prognostic features. The aberrant expressions of MYC and STAT3 are enriched in triple negatives (TN). They promote histological grade, vascularity, metastasis and tumor anti-apoptotic activities. VEGFA, STAT3, FOXM1 and METAP2 are druggable targets. High levels of METAP2, MMP7, IGF2 and IGF2R are unfavorable prognostic factors. STAT3 is an inferred center regulator at early cancer development predominantly in TN

A Supervised Network Analysis on Gene Expression Profiles of Breast Tumors Predicts a 41-Gene Prognostic Signature of the Transcription Factor MYB

Background. MYB is predicted to be a favorable prognostic predictor in a breast cancer population. We proposed to find the inferred mechanism(s) relevant to the prognostic features of MYB via a supervised network analysis. Methods. Both coefficient of intrinsic dependence (CID) and Galton Pierson’s correlation coefficient (GPCC) were combined and designated as CIDUGPCC. It is for the univariate network analysis. Multivariate CID is for the multivariate network analysis. Other analyses using bioinformatic tools and statistical methods are included. Results. ARNT2 is predicted to be the essential gene partner of MYB. We classified four prognostic relevant gene subpools in three breast cancer cohorts as feature types I–IV. Only the probes in feature type II are the potential prognostic feature of MYB. Moreover, we further validated 41 prognosis relevant probes to be the favorable prognostic signature. Surprisingly, two additional family members of MYB are elevated to promote poor prognosis when both levels of MYB and ARNT2 decline. Both MYBL1 and MYBL2 may partially decrease the tumor suppressive activities that are predicted to be up-regulated by MYB and ARNT2. Conclusions. The major prognostic feature of MYB is predicted to be determined by the MYB subnetwork (41 probes) that is relevant across subtypes