Extragalactic Radio Continuum Surveys and the Transformation of Radio Astronomy

Next-generation radio surveys are about to transform radio astronomy by discovering and studying tens of millions of previously unknown radio sources. These surveys will provide new insights to understand the evolution of galaxies, measuring the evolution of the cosmic star formation rate, and rivalling traditional techniques in the measurement of fundamental cosmological parameters. By observing a new volume of observational parameter space, they are also likely to discover unexpected new phenomena. This review traces the evolution of extragalactic radio continuum surveys from the earliest days of radio astronomy to the present, and identifies the challenges that must be overcome to achieve this transformational change.Comment: To be published in Nature Astronomy 18 Sept 201

Inferring the joint demographic history of multiple populations from multidimensional SNP frequency data

Demographic models built from genetic data play important roles in illuminating prehistorical events and serving as null models in genome scans for selection. We introduce an inference method based on the joint frequency spectrum of genetic variants within and between populations. For candidate models we numerically compute the expected spectrum using a diffusion approximation to the one-locus two-allele Wright-Fisher process, involving up to three simultaneous populations. Our approach is a composite likelihood scheme, since linkage between neutral loci alters the variance but not the expectation of the frequency spectrum. We thus use bootstraps incorporating linkage to estimate uncertainties for parameters and significance values for hypothesis tests. Our method can also incorporate selection on single sites, predicting the joint distribution of selected alleles among populations experiencing a bevy of evolutionary forces, including expansions, contractions, migrations, and admixture. As applications, we model human expansion out of Africa and the settlement of the New World, using 5 Mb of noncoding DNA resequenced in 68 individuals from 4 populations (YRI, CHB, CEU, and MXL) by the Environmental Genome Project. We also combine our demographic model with a previously estimated distribution of selective effects among newly arising amino acid mutations to accurately predict the frequency spectrum of nonsynonymous variants across three continental populations (YRI, CHB, CEU).Comment: 17 pages, 4 figures, supporting information included with sourc

The Plant Pathogen Pseudomonas syringae pv. tomato Is Genetically Monomorphic and under Strong Selection to Evade Tomato Immunity

Recently, genome sequencing of many isolates of genetically monomorphic bacterial human pathogens has given new insights into pathogen microevolution and phylogeography. Here, we report a genome-based micro-evolutionary study of a bacterial plant pathogen, Pseudomonas syringae pv. tomato. Only 267 mutations were identified between five sequenced isolates in 3,543,009 nt of analyzed genome sequence, which suggests a recent evolutionary origin of this pathogen. Further analysis with genome-derived markers of 89 world-wide isolates showed that several genotypes exist in North America and in Europe indicating frequent pathogen movement between these world regions. Genome-derived markers and molecular analyses of key pathogen loci important for virulence and motility both suggest ongoing adaptation to the tomato host. A mutational hotspot was found in the type III-secreted effector gene hopM1. These mutations abolish the cell death triggering activity of the full-length protein indicating strong selection for loss of function of this effector, which was previously considered a virulence factor. Two non-synonymous mutations in the flagellin-encoding gene fliC allowed identifying a new microbe associated molecular pattern (MAMP) in a region distinct from the known MAMP flg22. Interestingly, the ancestral allele of this MAMP induces a stronger tomato immune response than the derived alleles. The ancestral allele has largely disappeared from today's Pto populations suggesting that flagellin-triggered immunity limits pathogen fitness even in highly virulent pathogens. An additional non-synonymous mutation was identified in flg22 in South American isolates. Therefore, MAMPs are more variable than expected differing even between otherwise almost identical isolates of the same pathogen strain

Significance of Aurora B overexpression in hepatocellular carcinoma. Aurora B Overexpression in HCC

<p>Abstract</p> <p>Background</p> <p>To investigate the significance of Aurora B expression in hepatocellular carcinoma (HCC).</p> <p>Methods</p> <p>The <it>Aurora B </it>and <it>Aurora A </it>mRNA level was measured in 160 HCCs and the paired nontumorous liver tissues by reverse transcription-polymerase chain reaction. Mutations of the <it>p53 </it>and <it>β-catenin </it>genes were analyzed in 134 and 150 tumors, respectively, by direct sequencing of exon 2 to exon 11 of <it>p53 </it>and exon 3 of <it>β-catenin</it>. Anticancer effects of AZD1152-HQPA, an Aurora B kinase selective inhibitor, were examined in Huh-7 and Hep3B cell lines.</p> <p>Results</p> <p><it>Aurora B </it>was overexpressed in 98 (61%) of 160 HCCs and in all 7 HCC cell lines examined. The overexpression of <it>Aurora B </it>was associated with <it>Aurora A </it>overexpression (<it>P </it>= 0.0003) and <it>p53 </it>mutation (<it>P </it>= 0.002) and was inversely associated with <it>β</it>-<it>catenin </it>mutation (<it>P </it>= 0.002). <it>Aurora B </it>overexpression correlated with worse clinicopathologic characteristics. Multivariate analysis confirmed that <it>Aurora B </it>overexpression was an independent poor prognostic factor, despite its interaction with Aurora A overexpression and mutations of <it>p53 </it>and <it>β</it>-<it>catenin</it>. In Huh-7 and Hep3B cells, AZD1152-HQPA induced proliferation blockade, histone H3 (Ser10) dephosphorylation, cell cycle disturbance, and apoptosis.</p> <p>Conclusion</p> <p><it>Aurora B </it>overexpression is an independent molecular marker predicting tumor invasiveness and poor prognosis of HCC. Aurora B kinase selective inhibitors are potential therapeutic agents for HCC treatment.</p

Presentations of children to emergency departments across Europe and the COVID-19 pandemic: A multinational observational study

BACKGROUND: During the initial phase of the Coronavirus Disease 2019 (COVID-19) pandemic, reduced numbers of acutely ill or injured children presented to emergency departments (EDs). Concerns were raised about the potential for delayed and more severe presentations and an increase in diagnoses such as diabetic ketoacidosis and mental health issues. This multinational observational study aimed to study the number of children presenting to EDs across Europe during the early COVID-19 pandemic and factors influencing this and to investigate changes in severity of illness and diagnoses. METHODS AND FINDINGS: Routine health data were extracted retrospectively from electronic patient records of children aged 18 years and under, presenting to 38 EDs in 16 European countries for the period January 2018 to May 2020, using predefined and standardized data domains. Observed and predicted numbers of ED attendances were calculated for the period February 2020 to May 2020. Poisson models and incidence rate ratios (IRRs), using predicted counts for each site as offset to adjust for case-mix differences, were used to compare age groups, diagnoses, and outcomes. Reductions in pediatric ED attendances, hospital admissions, and high triage urgencies were seen in all participating sites. ED attendances were relatively higher in countries with lower SARS-CoV-2 prevalence (IRR 2.26, 95% CI 1.90 to 2.70, p < 0.001) and in children aged <12 months (12 to <24 months IRR 0.86, 95% CI 0.84 to 0.89; 2 to <5 years IRR 0.80, 95% CI 0.78 to 0.82; 5 to <12 years IRR 0.68, 95% CI 0.67 to 0.70; 12 to 18 years IRR 0.72, 95% CI 0.70 to 0.74; versus age <12 months as reference group, p < 0.001). The lowering of pediatric intensive care admissions was not as great as that of general admissions (IRR 1.30, 95% CI 1.16 to 1.45, p < 0.001). Lower triage urgencies were reduced more than higher triage urgencies (urgent triage IRR 1.10, 95% CI 1.08 to 1.12; emergent and very urgent triage IRR 1.53, 95% CI 1.49 to 1.57; versus nonurgent triage category, p < 0.001). Reductions were highest and sustained throughout the study period for children with communicable infectious diseases. The main limitation was the retrospective nature of the study, using routine clinical data from a wide range of European hospitals and health systems. CONCLUSIONS: Reductions in ED attendances were seen across Europe during the first COVID-19 lockdown period. More severely ill children continued to attend hospital more frequently compared to those with minor injuries and illnesses, although absolute numbers fell. TRIAL REGISTRATION: ISRCTN91495258 https://www.isrctn.com/ISRCTN91495258

The removal of multiplicative, systematic bias allows integration of breast cancer gene expression datasets – improving meta-analysis and prediction of prognosis

BACKGROUND: The number of gene expression studies in the public domain is rapidly increasing, representing a highly valuable resource. However, dataset-specific bias precludes meta-analysis at the raw transcript level, even when the RNA is from comparable sources and has been processed on the same microarray platform using similar protocols. Here, we demonstrate, using Affymetrix data, that much of this bias can be removed, allowing multiple datasets to be legitimately combined for meaningful meta-analyses. RESULTS: A series of validation datasets comparing breast cancer and normal breast cell lines (MCF7 and MCF10A) were generated to examine the variability between datasets generated using different amounts of starting RNA, alternative protocols, different generations of Affymetrix GeneChip or scanning hardware. We demonstrate that systematic, multiplicative biases are introduced at the RNA, hybridization and image-capture stages of a microarray experiment. Simple batch mean-centering was found to significantly reduce the level of inter-experimental variation, allowing raw transcript levels to be compared across datasets with confidence. By accounting for dataset-specific bias, we were able to assemble the largest gene expression dataset of primary breast tumours to-date (1107), from six previously published studies. Using this meta-dataset, we demonstrate that combining greater numbers of datasets or tumours leads to a greater overlap in differentially expressed genes and more accurate prognostic predictions. However, this is highly dependent upon the composition of the datasets and patient characteristics. CONCLUSION: Multiplicative, systematic biases are introduced at many stages of microarray experiments. When these are reconciled, raw data can be directly integrated from different gene expression datasets leading to new biological findings with increased statistical power

Adaptation of HIV-1 Depends on the Host-Cell Environment

Many viruses have the ability to rapidly develop resistance against antiviral drugs and escape from the host immune system. To which extent the host environment affects this adaptive potential of viruses is largely unknown. Here we show that for HIV-1, the host-cell environment is key to the adaptive potential of the virus. We performed a large-scale selection experiment with two HIV-1 strains in two different T-cell lines (MT4 and C8166). Over 110 days of culture, both virus strains adapted rapidly to the MT4 T-cell line. In contrast, when cultured on the C8166 T-cell line, the same strains did not show any increase in fitness. By sequence analyses and infections with viruses expressing either yellow or cyan fluorescent protein, we were able to show that the absence of adaptation was linked to a lower recombination rate in the C8166 T-cell line. Our findings suggest that if we can manipulate the host-cellular factors that mediate viral evolution, we may be able to significantly retard viral adaptability

Proteomic Analysis of Grape Berry Cell Cultures Reveals that Developmentally Regulated Ripening Related Processes Can Be Studied Using Cultured Cells

The original publication is available at http:/www.plosone.orgBackground: This work describes a proteomics profiling method, optimized and applied to berry cell suspensions to evaluate organ-specific cultures as a platform to study grape berry ripening. Variations in berry ripening within a cluster(s) on a vine and in a vineyard are a major impediment towards complete understanding of the functional processes that control ripening, specifically when a characterized and homogenous sample is required. Berry cell suspensions could overcome some of these problems, but their suitability as a model system for berry development and ripening needs to be established first. Methodology/Principal Findings: In this study we report on the proteomic evaluation of the cytosolic proteins obtained from synchronized cell suspension cultures that were established from callus lines originating from green, véraison and ripe Vitis vinifera berry explants. The proteins were separated using liquid phase IEF in a Microrotofor cell and SDS PAGE. This method proved superior to gel-based 2DE. Principal component analysis confirmed that biological and technical repeats grouped tightly and importantly, showed that the proteomes of berry cultures originating from the different growth/ripening stages were distinct. A total of twenty six common bands were selected after band matching between different growth stages and twenty two of these bands were positively identified. Thirty two % of the identified proteins are currently annotated as hypothetical. The differential expression profile of the identified proteins, when compared with published literature on grape berry ripening, suggested common trends in terms of relative abundance in the different developmental stages between real berries and cell suspensions. Conclusions: The advantages of having suspension cultures that accurately mimic specific developmental stages are profound and could significantly contribute to the study of the intricate regulatory and signaling networks responsible for berry development and ripening. © 2011 Sharathchandra et al.Publishers' Versio

Archaeological Support for the Three-Stage Expansion of Modern Humans across Northeastern Eurasia and into the Americas

Background Understanding the dynamics of the human range expansion across northeastern Eurasia during the late Pleistocene is central to establishing empirical temporal constraints on the colonization of the Americas [1]. Opinions vary widely on how and when the Americas were colonized, with advocates supporting either a pre-[2] or post-[1], [3], [4], [5], [6] last glacial maximum (LGM) colonization, via either a land bridge across Beringia [3], [4], [5], a sea-faring Pacific Rim coastal route [1], [3], a trans-Arctic route [4], or a trans-Atlantic oceanic route [5]. Here we analyze a large sample of radiocarbon dates from the northeast Eurasian Upper Paleolithic to identify the origin of this expansion, and estimate the velocity of colonization wave as it moved across northern Eurasia and into the Americas. Methodology/Principal Findings We use diffusion models [6], [7] to quantify these dynamics. Our results show the expansion originated in the Altai region of southern Siberia ~46kBP , and from there expanded across northern Eurasia at an average velocity of 0.16 km per year. However, the movement of the colonizing wave was not continuous but underwent three distinct phases: 1) an initial expansion from 47-32k calBP; 2) a hiatus from ~32-16k calBP, and 3) a second expansion after the LGM ~16k calBP. These results provide archaeological support for the recently proposed three-stage model of the colonization of the Americas [8], [9]. Our results falsify the hypothesis of a pre-LGM terrestrial colonization of the Americas and we discuss the importance of these empirical results in the light of alternative models. Conclusions/Significance Our results demonstrate that the radiocarbon record of Upper Paleolithic northeastern Eurasia supports a post-LGM terrestrial colonization of the Americas falsifying the proposed pre-LGM terrestrial colonization of the Americas. We show that this expansion was not a simple process, but proceeded in three phases, consistent with genetic data, largely in response to the variable climatic conditions of late Pleistocene northeast Eurasia. Further, the constraints imposed by the spatiotemporal gradient in the empirical radiocarbon record across this entire region suggests that North America cannot have been colonized much before the existing Clovis radiocarbon record suggests