The Spectrum of Clinical Utilities in Molecular Pathology Testing Procedures for Inherited Conditions and Cancer: A Report of the Association for Molecular Pathology

Clinical utility describes the benefits of each laboratory test for that patient. Many stakeholders have adopted narrow definitions for the clinical utility of molecular testing as applied to targeted pharmacotherapy in oncology, regardless of the population tested or the purpose of the testing. This definition does not address all of the important applications of molecular diagnostic testing. Definitions consistent with a patient-centered approach emphasize and recognize that a clinical test result\u27s utility depends on the context in which it is used and are particularly relevant to molecular diagnostic testing because of the nature of the information they provide. Debates surrounding levels and types of evidence needed to properly evaluate the clinical value of molecular diagnostics are increasingly important because the growing body of knowledge, stemming from the increase of genomic medicine, provides many new opportunities for molecular testing to improve health care. We address the challenges in defining the clinical utility of molecular diagnostics for inherited diseases or cancer and provide assessment recommendations. Starting with a modified analytic validity, clinical validity, clinical utility, and ethical, legal, and social implications model for addressing clinical utility of molecular diagnostics with a variety of testing purposes, we recommend promotion of patient-centered definitions of clinical utility that appropriately recognize the valuable contribution of molecular diagnostic testing to improve patient care

Dissipation and Extra Light in Galactic Nuclei: I. Gas-Rich Merger Remnants

We study the origin and properties of 'extra' or 'excess' central light in the surface brightness profiles of gas-rich merger remnants. Combining a large set of hydrodynamical simulations with data on observed mergers (spanning a broad range of profiles at various masses and degrees of relaxation), we show how to robustly separate the physically meaningful extra light -- stellar populations formed in a compact central starburst during a gas-rich merger -- from the outer profile established by violent relaxation acting on stars already present in the progenitors prior to the final merger. This separation is sensitive to the profile treatment, and we demonstrate that certain fitting procedures can yield physically misleading results. We show that our method reliably recovers the younger starburst population, and examine how the properties of this component scale with mass, gas content, and other aspects of the progenitors. We consider the time evolution of profiles in different bands, and estimate biases introduced by observational studies at different times and wavelengths. We show that extra light is ubiquitous in observed and simulated gas-rich merger remnants, with sufficient mass (~3-30% of the stellar mass) to explain the discrepancy in the maximum phase-space densities of ellipticals and their progenitor spirals. The nature of this central component provides powerful new constraints on the formation histories of observed systems.Comment: 36 pages, 38 figures, accepted for publication in ApJ (minor revisions to match accepted version

Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of sqrt(s) = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.Comment: 24 pages plus author list (36 pages total), 23 figures, 1 table, submitted to European Physical Journal

Measurement of the production cross section for W-bosons in association with jets in pp collisions at s=7 TeV with the ATLAS detector

This Letter reports on a first measurement of the inclusive W + jets cross section in proton-proton collisions at a centre-of-mass energy of 7 TeV at the LHC, with the ATLAS detector. Cross sections, in both the electron and muon decay modes of the W-boson, are presented as a function of jet multiplicity and of the transverse momentum of the leading and next-to-leading jets in the event. Measurements are also presented of the ratio of cross sections sigma (W + >= n)/sigma(W + >= n - 1) for inclusive jet multiplicities n = 1-4. The results, based on an integrated luminosity of 1.3 pb(-1), have been corrected for all known detector effects and are quoted in a limited and well-defined range of jet and lepton kinematics. The measured cross sections are compared to particle-level predictions based on perturbative QCD. Next-to-leading order calculations, studied here for n <= 2, are found in good agreement with the data. Leading-order multiparton event generators, normalized to the NNLO total cross section, describe the data well for all measured jet multiplicitie

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Label-Free Optical Detection of Biomolecular Translocation through Nanopore Arrays

In recent years, nanopores have emerged as exceptionally promising single-molecule sensors due to their ability to detect biomolecules at subfemtomole levels in a label-free manner. Development of a high-throughput nanopore-based biosensor requires multiplexing of nanopore measurements. Electrical detection, however, poses a challenge, as each nanopore circuit must be electrically independent, which requires complex nanofluidics and embedded electrodes. Here, we present an optical method for simultaneous measurements of the ionic current across an array of solid-state nanopores, requiring no additional fabrication steps. Proof-of-principle experiments are conducted that show simultaneous optical detection and characterization of ssDNA and dsDNA using an array of pores. Through a comparison with electrical measurements, we show that optical measurements are capable of accessing equivalent transmembrane current information

Comprehensive resequence analysis of a 97 kb region of chromosome 10q11.2 containing the MSMB gene associated with prostate cancer

Genome-wide association studies of prostate cancer have identified single nucleotide polymorphism (SNP) markers in a region of chromosome 10q11.2, harboring the microseminoprotein-β (MSMB) gene. Both the gene product of MSMB, the prostate secretory protein 94 (PSP94) and its binding protein (PSPBP), have been previously investigated as serum biomarkers for prostate cancer progression. Recent functional work has shown that different alleles of the significantly associated SNP in the promoter of MSMB found to be associated with prostate cancer risk, rs10993994, can influence its expression in tumors and in vitro studies. Since it is plausible that additional variants in this region contribute to the risk of prostate cancer, we have used next-generation sequencing technology to resequence a ~97-kb region that includes the area surrounding MSMB (chr10: 51,168,025–51,265,101) in 36 prostate cancer cases, 26 controls of European origin, and 8 unrelated CEPH individuals in order to identify additional variants to investigate in functional studies. We identified 241 novel polymorphisms within this region, including 142 in the 51-kb block of linkage disequilibrium (LD) that contains rs10993994 and the proximal promoter of MSMB. No sites were observed to be polymorphic within the exons of MSMB

Identification of Neural Outgrowth Genes using Genome-Wide RNAi

While genetic screens have identified many genes essential for neurite outgrowth, they have been limited in their ability to identify neural genes that also have earlier critical roles in the gastrula, or neural genes for which maternally contributed RNA compensates for gene mutations in the zygote. To address this, we developed methods to screen the Drosophila genome using RNA-interference (RNAi) on primary neural cells and present the results of the first full-genome RNAi screen in neurons. We used live-cell imaging and quantitative image analysis to characterize the morphological phenotypes of fluorescently labelled primary neurons and glia in response to RNAi-mediated gene knockdown. From the full genome screen, we focused our analysis on 104 evolutionarily conserved genes that when downregulated by RNAi, have morphological defects such as reduced axon extension, excessive branching, loss of fasciculation, and blebbing. To assist in the phenotypic analysis of the large data sets, we generated image analysis algorithms that could assess the statistical significance of the mutant phenotypes. The algorithms were essential for the analysis of the thousands of images generated by the screening process and will become a valuable tool for future genome-wide screens in primary neurons. Our analysis revealed unexpected, essential roles in neurite outgrowth for genes representing a wide range of functional categories including signalling molecules, enzymes, channels, receptors, and cytoskeletal proteins. We also found that genes known to be involved in protein and vesicle trafficking showed similar RNAi phenotypes. We confirmed phenotypes of the protein trafficking genes Sec61alpha and Ran GTPase using Drosophila embryo and mouse embryonic cerebral cortical neurons, respectively. Collectively, our results showed that RNAi phenotypes in primary neural culture can parallel in vivo phenotypes, and the screening technique can be used to identify many new genes that have important functions in the nervous system

A comprehensive resequence analysis of the KLK15–KLK3–KLK2 locus on chromosome 19q13.33

Single nucleotide polymorphisms (SNPs) in the KLK3 gene on chromosome 19q13.33 are associated with serum prostate-specific antigen (PSA) levels. Recent genome wide association studies of prostate cancer have yielded conflicting results for association of the same SNPs with prostate cancer risk. Since the KLK3 gene encodes the PSA protein that forms the basis for a widely used screening test for prostate cancer, it is critical to fully characterize genetic variation in this region and assess its relationship with the risk of prostate cancer. We have conducted a next-generation sequence analysis in 78 individuals of European ancestry to characterize common (minor allele frequency, MAF >1%) genetic variation in a 56 kb region on chromosome 19q13.33 centered on the KLK3 gene (chr19:56,019,829–56,076,043 bps). We identified 555 polymorphic loci in the process including 116 novel SNPs and 182 novel insertion/deletion polymorphisms (indels). Based on tagging analysis, 144 loci are necessary to tag the region at an r2 threshold of 0.8 and MAF of 1% or higher, while 86 loci are required to tag the region at an r2 threshold of 0.8 and MAF >5%. Our sequence data augments coverage by 35 and 78% as compared to variants in dbSNP and HapMap, respectively. We observed six non-synonymous amino acid or frame shift changes in the KLK3 gene and three changes in each of the neighboring genes, KLK15 and KLK2. Our study has generated a detailed map of common genetic variation in the genomic region surrounding the KLK3 gene, which should be useful for fine-mapping the association signal as well as determining the contribution of this locus to prostate cancer risk and/or regulation of PSA expression