Gene Expression Profiling of Human Decidual Macrophages: Evidence for Immunosuppressive Phenotype

Background: Although uterine macrophages are thought to play an important regulatory role at the maternal-fetal interface, their global gene expression profile is not known. Methodology/Principal Findings: Using micro-array comprising approximately 14,000 genes, the gene expression pattern of human first trimester decidual CD14+ monocytes/macrophages was characterized and compared with the expression profile of the corresponding cells in blood. Some of the key findings were confirmed by real time PCR or by secreted protein. A unique gene expression pattern intrinsic of first trimester decidual CD14+ cells was demonstrated. A large number of regulated genes were functionally related to immunomodulation and tissue remodelling, corroborating polarization patterns of differentiated macrophages mainly of the alternatively activated M2 phenotype. These include known M2 markers such as CCL-18, CD209, insulin-like growth factor (IGF)-1, mannose receptor c type (MRC)-1 and fibronectin-1. Further, the selective up-regulation of triggering receptor expressed on myeloid cells (TREM)-2, alpha-2-macroglobulin (A2M) and prostaglandin D2 synthase (PGDS) provides new insights into the regulatory function of decidual macrophages in pregnancy that may have implications in pregnancy complications. Conclusions/Significance: The molecular characterization of decidual macrophages presents a unique transcriptional profile replete with important components for fetal immunoprotection and provides several clues for further studies of these cells.Original Publication:Charlotte Gustafsson (Lidström), Jenny Mjösberg, Andreas Matussek, Robert Geffers, Leif Matthiesen, Göran Berg, Surendra Sharma, Jan Buer and Jan Ernerudh, Gene expression profiling of human decidual macrophages: Evidence for immunosuppressive phenotype, 2008, PLoS ONE, (3), 4, e2078.http://dx.doi.org/10.1371/journal.pone.0002078Copyright: Public Library of Science (PLoS)http://www.plos.org

A strategy to discover new organizers identifies a putative heart organizer

Organizers are regions of the embryo that can both induce new fates and impart pattern on other regions. So far, surprisingly few organizers have been discovered, considering the number of patterned tissue types generated during development. This may be because their discovery has relied on transplantation and ablation experiments. Here we describe a new approach, using chick embryos, to discover organizers based on a common gene expression signature, and use it to uncover the anterior intestinal portal (AIP) endoderm as a putative heart organizer. We show that the AIP can induce cardiac identity from non-cardiac mesoderm and that it can pattern this by specifying ventricular and suppressing atrial regional identity. We also uncover some of the signals responsible. The method holds promise as a tool to discover other novel organizers acting during development

Extraction of the Muon Signals Recorded with the Surface Detector of the Pierre Auger Observatory Using Recurrent Neural Networks

We present a method based on the use of Recurrent Neural Networks to extract the muon component from the time traces registered with water-Cherenkov detector (WCD) stations of the Surface Detector of the Pierre Auger Observatory. The design of the WCDs does not allow to separate the contribution of muons to the time traces obtained from the WCDs from those of photons, electrons and positrons for all events. Separating the muon and electromagnetic components is crucial for the determination of the nature of the primary cosmic rays and properties of the hadronic interactions at ultra-high energies. We trained a neural network to extract the muon and the electromagnetic components from the WCD traces using a large set of simulated air showers, with around 450 000 simulated events. For training and evaluating the performance of the neural network, simulated events with energies between 1018.5, eV and 1020 eV and zenith angles below 60 degrees were used. We also study the performance of this method on experimental data of the Pierre Auger Observatory and show that our predicted muon lateral distributions agree with the parameterizations obtained by the AGASA collaboration