Electrically Induced Shape Oscillation of Drops as a Means of Direct-Contact Heat Transfer Enhancement: Part 2-Heat Transfer

The heat transfer enhancement caused by the application of a low-frequency (1 ~ 16 Hz

Analysis of Area-Specific Expression Patterns of RORbeta, ER81 and Nurr1 mRNAs in Rat Neocortex by Double In Situ Hybridization and Cortical Box Method

BACKGROUND: The mammalian neocortex is subdivided into many areas, each of which exhibits distinctive lamina architecture. To investigate such area differences in detail, we chose three genes for comparative analyses, namely, RORbeta, ER81 and Nurr1, mRNAs of which have been reported to be mainly expressed in layers 4, 5 and 6, respectively. To analyze their qualitative and quantitative coexpression profiles in the rat neocortex, we used double in situ hybridization (ISH) histochemistry and cortical box method which we previously developed to integrate the data of different staining and individuals in a standard three-dimensional space. PRINCIPAL FINDINGS: Our new approach resulted in three main observations. First, the three genes showed unique area distribution patterns that are mostly complementary to one another. The patterns revealed by cortical box method matched well with the cytoarchitectonic areas defined by Nissl staining. Second, at single cell level, RORbeta and ER81 mRNAs were coexpressed in a subpopulation of layer 5 neurons, whereas Nurr1 and ER81 mRNAs were not colocalized. Third, principal component analysis showed that the order of hierarchical processing in the cortex correlates well with the expression profiles of these three genes. Based on this analysis, the dysgranular zone (DZ) in the somatosensory area was considered to exhibit a profile of a higher order area, which is consistent with previous proposal. CONCLUSIONS/SIGNIFICANCE: The tight relationship between the expression of the three layer specific genes and functional areas were revealed, demonstrating the usefulness of cortical box method in the study on the cerebral cortex. In particular, it allowed us to perform statistical evaluation and pattern matching, which would become important in interpreting the ever-increasing data of gene expression in the cortex

Long non-coding RNAs and cancer: a new frontier of translational research?

Author manuscriptTiling array and novel sequencing technologies have made available the transcription profile of the entire human genome. However, the extent of transcription and the function of genetic elements that occur outside of protein-coding genes, particularly those involved in disease, are still a matter of debate. In this review, we focus on long non-coding RNAs (lncRNAs) that are involved in cancer. We define lncRNAs and present a cancer-oriented list of lncRNAs, list some tools (for example, public databases) that classify lncRNAs or that scan genome spans of interest to find whether known lncRNAs reside there, and describe some of the functions of lncRNAs and the possible genetic mechanisms that underlie lncRNA expression changes in cancer, as well as current and potential future applications of lncRNA research in the treatment of cancer.RS is supported as a fellow of the TALENTS Programme (7th R&D Framework Programme, Specific Programme: PEOPLE—Marie Curie Actions—COFUND). MIA is supported as a PhD fellow of the FCT (Fundação para a Ciência e Tecnologia), Portugal. GAC is supported as a fellow by The University of Texas MD Anderson Cancer Center Research Trust, as a research scholar by The University of Texas System Regents, and by the Chronic Lymphocytic Leukemia Global Research Foundation. Work in GAC’s laboratory is supported in part by the NIH/ NCI (CA135444); a Department of Defense Breast Cancer Idea Award; Developmental Research Awards from the Breast Cancer, Ovarian Cancer, Brain Cancer, Multiple Myeloma and Leukemia Specialized Programs of Research Excellence (SPORE) grants from the National Institutes of Health; a 2009 Seena Magowitz–Pancreatic Cancer Action Network AACR Pilot Grant; the Laura and John Arnold Foundation and the RGK Foundation

The Genetic Signatures of Noncoding RNAs

The majority of the genome in animals and plants is transcribed in a developmentally regulated manner to produce large numbers of non–protein-coding RNAs (ncRNAs), whose incidence increases with developmental complexity. There is growing evidence that these transcripts are functional, particularly in the regulation of epigenetic processes, leading to the suggestion that they compose a hitherto hidden layer of genomic programming in humans and other complex organisms. However, to date, very few have been identified in genetic screens. Here I show that this is explicable by an historic emphasis, both phenotypically and technically, on mutations in protein-coding sequences, and by presumptions about the nature of regulatory mutations. Most variations in regulatory sequences produce relatively subtle phenotypic changes, in contrast to mutations in protein-coding sequences that frequently cause catastrophic component failure. Until recently, most mapping projects have focused on protein-coding sequences, and the limited number of identified regulatory mutations have been interpreted as affecting conventional cis-acting promoter and enhancer elements, although these regions are often themselves transcribed. Moreover, ncRNA-directed regulatory circuits underpin most, if not all, complex genetic phenomena in eukaryotes, including RNA interference-related processes such as transcriptional and post-transcriptional gene silencing, position effect variegation, hybrid dysgenesis, chromosome dosage compensation, parental imprinting and allelic exclusion, paramutation, and possibly transvection and transinduction. The next frontier is the identification and functional characterization of the myriad sequence variations that influence quantitative traits, disease susceptibility, and other complex characteristics, which are being shown by genome-wide association studies to lie mostly in noncoding, presumably regulatory, regions. There is every possibility that many of these variations will alter the interactions between regulatory RNAs and their targets, a prospect that should be borne in mind in future functional analyses