Single-cell profiling for advancing birth defects research and prevention

Cellular analysis of developmental processes and toxicities has traditionally entailed bulk methods (e.g., transcriptomics) that lack single cell resolution or tissue localization methods (e.g., immunostaining) that allow only a few genes to be monitored in each experiment. Recent technological advances have enabled interrogation of genomic function at the single-cell level, providing new opportunities to unravel developmental pathways and processes with unprecedented resolution. Here, we review emerging technologies of single-cell RNA-sequencing (scRNA-seq) to globally characterize the gene expression sets of different cell types and how different cell types emerge from earlier cell states in development. Cell atlases of experimental embryology and human embryogenesis at single-cell resolution will provide an encyclopedia of genes that define key stages from gastrulation to organogenesis. This technology, combined with computational models to discover key organizational principles, was recognized by Science magazine as the “Breakthrough of the year” for 2018 due to transformative potential on the way we study how human cells mature over a lifetime, how tissues regenerate, and how cells change in diseases (e.g., patient-derived organoids to screen disease-specific targets and design precision therapy). Profiling transcriptomes at the single-cell level can fulfill the need for greater detail in the molecular progression of all cell lineages, from pluripotency to adulthood and how cell–cell signaling pathways control progression at every step. Translational opportunities emerge for elucidating pathogenesis of genetic birth defects with cellular precision and improvements for predictive toxicology of chemical teratogenesis

A direct D-bar reconstruction algorithm for recovering a complex conductivity in 2-D

A direct reconstruction algorithm for complex conductivities in $W^{2,\infty}(\Omega)$, where $\Omega$ is a bounded, simply connected Lipschitz domain in $\mathbb{R}^2$, is presented. The framework is based on the uniqueness proof by Francini [Inverse Problems 20 2000], but equations relating the Dirichlet-to-Neumann to the scattering transform and the exponentially growing solutions are not present in that work, and are derived here. The algorithm constitutes the first D-bar method for the reconstruction of conductivities and permittivities in two dimensions. Reconstructions of numerically simulated chest phantoms with discontinuities at the organ boundaries are included.Comment: This is an author-created, un-copyedited version of an article accepted for publication in [insert name of journal]. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at 10.1088/0266-5611/28/9/09500

The Genetic and Environmental Sources of Resemblance Between Normative Personality and Personality Disorder Traits

Recent work has suggested a high level of congruence between normative personality, most typically represented by the big five factors, and abnormal personality traits. In 2,293 Norwegian adult twins ascertained from a population-based registry, the authors evaluated the degree of sharing of genetic and environmental influences on normative personality, assessed by the Big Five Inventory (BFI), and personality disorder traits (PDTs), assessed by the Personality Inventory for DSM-S-Norwegian Brief Form (PID-5NBF). For four of the five BFI dimensions, the strongest genetic correlation was observed with the expected PID-5-NBF dimension (e.g., neuroticism with negative affectivity [+], conscientiousness with disinhibition [-]). However, neuroticism, conscientiousness, and agreeableness had substantial genetic correlations with other PID-S-NBF dimensions (e.g., neuroticism with compulsivity [+], agreeableness with detachment [-]). Openness had no substantial genetic correlations with any PID-5-NBF dimension. The proportion of genetic risk factors shared in aggregate between the BFI traits and the PID-5-NBF dimensions was quite high for conscientiousness and neuroticism, relatively robust for extraversion and agreeableness, but quite low for openness. Of the six PID-S-NBF dimensions, three (negative affectivity, detachment, and disinhibition) shared, in aggregate, most of their genetic risk factors with normative personality traits. Genetic factors underlying psychoticism, antagonism, and compulsivity were shared to a lesser extent, suggesting that they are influenced by etiological factors not well indexed by the BFI

Experimental investigation of the Landau-Pomeranchuk-Migdal effect in low-Z targets

In the CERN NA63 collaboration we have addressed the question of the potential inadequacy of the commonly used Migdal formulation of the Landau-Pomeranchuk-Migdal (LPM) effect by measuring the photon emission by 20 and 178 GeV electrons in the range 100 MeV - 4 GeV, in targets of LowDensityPolyEthylene (LDPE), C, Al, Ti, Fe, Cu, Mo and, as a reference target, Ta. For each target and energy, a comparison between simulated values based on the LPM suppression of incoherent bremsstrahlung is shown, taking multi-photon effects into account. For these targets and energies, we find that Migdal's theoretical formulation is adequate to a precision of better than about 5%, irrespective of the target substance.Comment: 8 pages, 13 figure

Preferential attachment of communities: the same principle, but a higher level

The graph of communities is a network emerging above the level of individual nodes in the hierarchical organisation of a complex system. In this graph the nodes correspond to communities (highly interconnected subgraphs, also called modules or clusters), and the links refer to members shared by two communities. Our analysis indicates that the development of this modular structure is driven by preferential attachment, in complete analogy with the growth of the underlying network of nodes. We study how the links between communities are born in a growing co-authorship network, and introduce a simple model for the dynamics of overlapping communities.Comment: 7 pages, 3 figure

Chromosomal instability in untreated primary prostate cancer as an indicator of metastatic potential.

BackgroundMetastatic prostate cancer (PC) is highly lethal. The ability to identify primary tumors capable of dissemination is an unmet need in the quest to understand lethal biology and improve patient outcomes. Previous studies have linked chromosomal instability (CIN), which generates aneuploidy following chromosomal missegregation during mitosis, to PC progression. Evidence of CIN includes broad copy number alterations (CNAs) spanning > 300 base pairs of DNA, which may also be measured via RNA expression signatures associated with CNA frequency. Signatures of CIN in metastatic PC, however, have not been interrogated or well defined. We examined a published 70-gene CIN signature (CIN70) in untreated and castration-resistant prostate cancer (CRPC) cohorts from The Cancer Genome Atlas (TCGA) and previously published reports. We also performed transcriptome and CNA analysis in a unique cohort of untreated primary tumors collected from diagnostic prostate needle biopsies (PNBX) of localized (M0) and metastatic (M1) cases to determine if CIN was linked to clinical stage and outcome.MethodsPNBX were collected from 99 patients treated in the VA Greater Los Angeles (GLA-VA) Healthcare System between 2000 and 2016. Total RNA was extracted from high-grade cancer areas in PNBX cores, followed by RNA sequencing and/or copy number analysis using OncoScan. Multivariate logistic regression analyses permitted calculation of odds ratios for CIN status (high versus low) in an expanded GLA-VA PNBX cohort (n = 121).ResultsThe CIN70 signature was significantly enriched in primary tumors and CRPC metastases from M1 PC cases. An intersection of gene signatures comprised of differentially expressed genes (DEGs) generated through comparison of M1 versus M0 PNBX and primary CRPC tumors versus metastases revealed a 157-gene "metastasis" signature that was further distilled to 7-genes (PC-CIN) regulating centrosomes, chromosomal segregation, and mitotic spindle assembly. High PC-CIN scores correlated with CRPC, PC-death and all-cause mortality in the expanded GLA-VA PNBX cohort. Interestingly, approximately 1/3 of M1 PNBX cases exhibited low CIN, illuminating differential pathways of lethal PC progression.ConclusionsMeasuring CIN in PNBX by transcriptome profiling is feasible, and the PC-CIN signature may identify patients with a high risk of lethal progression at the time of diagnosis

Multi-decadal marine- and land-terminating glacier recession in the Ammassalik region, southeast Greenland

Landsat imagery was applied to elucidate glacier fluctuations of land- and marine-terminating outlet glaciers from the Greenland Ice Sheet (GrIS) and local land-terminating glaciers and ice caps (GIC) peripheral to the GrIS in the Ammassalik region, Southeast Greenland, during the period 1972–2011. Data from 21 marine-terminating glaciers (including the glaciers Helheim, Midgaard, and Fenris), the GrIS land-terminating margin, and 35 GIC were examined and compared to observed atmospheric air temperatures, precipitation, and reconstructed ocean water temperatures (at 400 m depth in the Irminger Sea). Here, we document that net glacier recession has occurred since 1972 in the Ammassalik region for all glacier types and sizes, except for three GIC. The land-terminating GrIS and GIC reflect lower marginal and areal changes than the marine-terminating outlet glaciers. The mean annual land-terminating GrIS and GIC margin recessions were about three to five times lower than the GrIS marine-terminating recession. The marine-terminating outlet glaciers had an average net frontal retreat for 1999–2011 of 0.098 km yr<sup>−1</sup>, which was significantly higher than in previous sub-periods 1972–1986 and 1986–1999. For the marine-terminating GrIS, the annual areal recession rate has been decreasing since 1972, while increasing for the land-terminating GrIS since 1986. On average for all the observed GIC, a mean net frontal retreat for 1986–2011 of 0.010 ± 0.006 km yr<sup>−1</sup> and a mean areal recession of around 1% per year occurred; overall for all observed GIC, a mean recession rate of 27 ± 24% occurred based on the 1986 GIC area. Since 1986, five GIC melted away in the Ammassalik area

Shape oscillations in non-degenerate Bose gases - transition from the collisionless to the hydrodynamic regime

We investigate collective oscillations of non-degenerate clouds of Rb-87 atoms as a function of density in an elongated magnetic trap. For the low-lying M=0 monopole-quadrupole shape oscillation we measure the oscillation frequencies and damping rates. At the highest densities the mean-free-path is smaller than the axial dimension of the sample, which corresponds to collisionally hydrodynamic conditions. This allows us to cover the cross-over from the collisionless to the hydrodynamic regime. The experimental results show good agreement with theory. We also analyze the influence of trap anharmonicities on the oscillations in relation to observed temperature dependencies of the dipole and quadrupole oscillation frequencies. We present convenient expressions to quantify these effects.Comment: 10 pages, 5 figure

Spectral transitions in networks

We study the level spacing distribution p(s) in the spectrum of random networks. According to our numerical results, the shape of p(s) in the Erdos-Renyi (E-R) random graph is determined by the average degree , and p(s) undergoes a dramatic change when is varied around the critical point of the percolation transition, =1. When > 1, the p(s) is described by the statistics of the Gaussian Orthogonal Ensemble (GOE), one of the major statistical ensembles in Random Matrix Theory, whereas at =1 it follows the Poisson level spacing distribution. Closely above the critical point, p(s) can be described in terms of an intermediate distribution between Poisson and the GOE, the Brody-distribution. Furthermore, below the critical point p(s) can be given with the help of the regularised Gamma-function. Motivated by these results, we analyse the behaviour of p(s) in real networks such as the Internet, a word association network and a protein protein interaction network as well. When the giant component of these networks is destroyed in a node deletion process simulating the networks subjected to intentional attack, their level spacing distribution undergoes a similar transition to that of the E-R graph.Comment: 11 pages, 5 figure

Garbage Can in the Lab

We develop an experimental setting where the assumptions and predictions of the garbage can model can be tested. A careful recon- struction of the original simulation model let us select parameters that leave room for potential variations in individual behavior. Our experi- mental design replicates these parameters and thereby facilitates comparison of human behavior with the original model. We find that the majority strategy of human subjects is consistent with the original model, but exhibits some behavioral diversity. Human subjects exhibit fluid diverse behaviors that improve coordination in the face of uncertainty, but hinder collective learning that can improve group performance