Shizuka Uchida | PubMed Health

PubMed2007

Upregulations of Gata4 and oxytocin receptor are important in cardiomyocyte differentiation processes of P19CL6 cells.

Oxytocin induces P19 cells to differentiate into cardiomyocytes possibly through the oxytocin/oxytocin receptor system. We added oxytocin to the growth medium of P19CL6, a subline of P19, but they did not differentiate into cardiomyocytes as indicated by RT-PCR and Western blotting results. During the cardiac commitment time of P19CL6 cells, the mRNA expression levels of the oxytocin receptor were upregulated by the addition of oxytocin as well as DMSO, but an upregulation of Gata4 expression levels was only observed for the cells induced by DMSO. The in silico analysis of the upstream sequence of the oxytocin receptor predicted putative binding sites for Gata4 and Nkx2.5. These results suggest that upregulations of the oxytocin receptor and Gata4 are important for cardiomyocyte differentiation processes.

Animals↗

PubMed2005

Detection and normalization of biases present in spotted cDNA microarray data: a composite method addressing dye, intensity-dependent, spatially-dependent, and print-order biases.

Microarrays are often used to identify target genes that trigger specific diseases, to elucidate the mechanisms of drug effects, and to check SNPs. However, data from microarray experiments are well known to contain biases resulting from the experimental protocols. Therefore, in order to elucidate biological knowledge from the data, systematic biases arising from their protocols must be removed prior to any data analysis. To remove these biases, many normalization methods are used by researchers. However, not all biases are eliminated from the microarray data because not all types of errors from experimental protocols are known. In this paper, we report an effective way of removing various types of biases by treating each microarray dataset independently to detect biases present in the dataset. After the biases contained in each dataset were identified, a combination of normalization methods specifically made for each dataset was applied to remove biases one at a time.

Algorithms↗