Design and Test Beam Performance of Substructures of the CMS Tracker End Caps

With its total active silicon area of about 200 squaremetres and more than 15000 silicon modules the silicon strip tracker of the CMS experiment at the LHC will be the largest silicon strip detector ever built. While the performance of single silicon modules has already been tested extensively in various test beam experiments, the performance of larger integrated substructures also had to be studied with a particle beam before launching mass production, in order to ensure the envisaged performance of the overall system. In May/June 2004 the performance of a system of two petals of the tracker end caps (TEC), which represents about 1% of the full TEC and forms an autonomous unit in terms of data acquisition, has been studied in a test beam experiment at CERN. In this document the test beam experiment is described and results are presented

Congenital diaphragmatic hernia interval on chromosome 8p23.1 characterized by genetics and protein interaction networks

Chromosome 8p23.1 is a common hotspot associated with major congenital malformations, including congenital diaphragmatic hernia (CDH) and cardiac defects. We present findings from high-resolution arrays in patients who carry a loss (n = 18) or a gain (n = 1) of sub-band 8p23.1. We confirm a region involved in both diaphragmatic and heart malformations. Results from a novel CNVConnect algorithm, prioritizing protein–protein interactions between products of genes in the 8p23.1 hotspot and products of previously known CDH causing genes, implicated GATA4, NEIL2, and SOX7 in diaphragmatic defects. Sequence analysis of these genes in 226 chromosomally normal CDH patients, as well as in a small number of deletion 8p23.1 patients, showed rare unreported variants in the coding region; these may be contributing to the diaphragmatic phenotype. We also demonstrated that two of these three genes were expressed in the E11.5–12.5 primordial mouse diaphragm, the developmental stage at which CDH is thought to occur. This combination of bioinformatics and expression studies can be applied to other chromosomal hotspots, as well as private microdeletions or microduplications, to identify causative genes and their interaction networks