Role of the host cell in bacteriophage T4 development. II. Characterization of host mutants that have pleiotropic effects on T4 growth

Mutant host-defective Escherichi coli that fail to propagate bacteriophage T4 and have a pleiotropic effect on T4 development have been isolated and characterized. In phage-infected mutant cells, specific early phage proteins are absent or reduced in amount, phage DNA synthesis is depressed by about 50%, specific structural phage proteins, including some tail and collar components, are deficient or missing, and host-cell lysis is delayed and slow. Almost all phage that can overcome the host block carry mutantions that map in functionally undefined 'nonessential' regions of the T4 genome, most near gene 39. The mutant host strains are temperature sensitive for growth and show simultaneous reversion of the ts phenotype and the inability to propagate T4+. The host mutations are cotransduced with ilv (83 min) and may lie in the gene for transcription termination factor rho

Element-centric clustering comparison unifies overlaps and hierarchy

Clustering is one of the most universal approaches for understanding complex data. A pivotal aspect of clustering analysis is quantitatively comparing clusterings; clustering comparison is the basis for many tasks such as clustering evaluation, consensus clustering, and tracking the temporal evolution of clusters. In particular, the extrinsic evaluation of clustering methods requires comparing the uncovered clusterings to planted clusterings or known metadata. Yet, as we demonstrate, existing clustering comparison measures have critical biases which undermine their usefulness, and no measure accommodates both overlapping and hierarchical clusterings. Here we unify the comparison of disjoint, overlapping, and hierarchically structured clusterings by proposing a new element-centric framework: elements are compared based on the relationships induced by the cluster structure, as opposed to the traditional cluster-centric philosophy. We demonstrate that, in contrast to standard clustering similarity measures, our framework does not suffer from critical biases and naturally provides unique insights into how the clusterings differ. We illustrate the strengths of our framework by revealing new insights into the organization of clusters in two applications: the improved classification of schizophrenia based on the overlapping and hierarchical community structure of fMRI brain networks, and the disentanglement of various social homophily factors in Facebook social networks. The universality of clustering suggests far-reaching impact of our framework throughout all areas of science

The Health Status of Southern Children: A Neglected Regional Disparity

Purpose: Great variations exist in child health outcomes among states in the United States, with southern states consistently ranked among the lowest in the country. Investigation of the geographical distribution of children’s health status and the regional factors contributing to these outcomes has been neglected. We attempted to identify the degree to which region of residence may be linked to health outcomes for children with the specific aim of determining whether living in the southern region of the United States is adversely associated with children’s health status. Methods: A child health index (CHI) that ranked each state in the United States was computed by using statespecific composite scores generated from outcome measures for a number of indicators of child health. Five indicators for physical health were chosen (percent low birth weight infants, infant mortality rate, child death rate, teen death rate, and teen birth rates) based on their historic and routine use to define health outcomes in children. Indicators were calculated as rates or percentages. Standard scores were calculated for each state for each health indicator by subtracting the mean of the measures for all states from the observed measure for each state. Indicators related to social and economic status were considered to be variables that impact physical health, as opposed to indicators of physical health, and therefore were not used to generate the composite child health score. These variables were subsequently examined in this study as potential confounding variables. Mapping was used to redefine regional groupings of states, and parametric tests (2-sample t test, analysis of means, and analysis-of-variance F tests) were used to compare the means of the CHI scores for the regional groupings and test for statistical significance. Multiple regression analysis computed the relationship of region, social and economic indicators, and race to the CHI. Simple linear-regression analyses were used to assess the individual effect of each indicator. Results: A geographic region of contiguous states, characterized by their poor child health outcomes relative to other states and regions of the United States, exists within the “Deep South” (Mississippi, Louisiana, Arkansas, Tennessee, Alabama, Georgia, North Carolina, South Carolina, and Florida). This Deep-South region is statistically different in CHI scores from the US Census Bureau– defined grouping of states in the South. The mean of CHI scores for the Deep-South region was \u3e1 SD below the mean of CHI scores for all states. In contrast, the CHI score means for each of the other 3 regions were all above the overall mean of CHI scores for all states. Regression analysis showed that living in the Deep- South region is a stronger predictor of poor child health outcomes than other consistently collected and reported variables commonly used to predict children’s health. Conclusions: The findings of this study indicate that region of residence in the United States is statistically related to important measures of children’s health and may be among the most powerful predictors of child health outcomes and disparities. This clarification of the poorer health status of children living in the Deep South through spatial analysis is an essential first step for developing a better understanding of variations in the health of children. Similar to early epidemiology work linking geographic boundaries to disease, discovering the mechanisms/pathways/causes by which region influences health outcomes is a critical step in addressing disparities and inequities in child health and one that is an important and fertile area for future research. The reasons for these disparities may be complex and synergistically related to various economic, political, social, cultural, and perhaps even environmental (physical) factors in the region. This research will require the use and development of new approaches and applications of spatial analysis to develop insights into the societal, environmental, and historical determinants of child health that have been neglected in previous child health outcomes and policy research. The public policy implications of the findings in this study are substantial. Few, if any, policies identify these children as a high-risk group on the basis of their region of residence. A better understanding of the depth and breadth of disparities in health, education, and other social outcomes among and within regions of the United States is necessary for the generation of policies that enable policy makers to address and mitigate the factors that influence these disparities. Defining and clarifying the regional boundaries is also necessary to better inform public policy decisions related to resource allocation and the prevention and/or mitigation of the effects of region on child health. The identification of the Deep South as a clearly defined sub-region of the Census Bureau’s regional definition of the South suggests the need to use more culturally and socially relevant boundaries than the Census Bureau regions when analyzing regional data for policy development

CONGRESSIONALLY MANDATED EXTENSION EVALUATION

Teaching/Communication/Extension/Profession,

Sketch-To-Solution: An Exploration of Viscous CFD with Automatic Grids

Numerical simulation of the Reynolds-averaged NavierStokes (RANS) equations has become a critical tool for the design of aerospace vehicles. However, the issues that affect the grid convergence of three dimensional RANS solutions are not completely understood, as documented in the AIAA Drag Prediction Workshop series. Grid adaption methods have the potential for increasing the automation and discretization error control of RANS solutions to impact the aerospace design and certification process. The realization of the CFD Vision 2030 Study includes automated management of errors and uncertainties of physics-based, predictive modeling that can set the stage for ensuring a vehicle is in compliance with a regulation or specification by using analysis without demonstration in flight test (i.e., certification or qualification by analysis). For example, the Cart3D inviscid analysis package has automated Cartesian cut-cell gridding with output-based error control. Fueled by recent advances in the fields of anisotropic grid adaptation, error estimation, and geometry modeling, a similar work flow is explored for viscous CFD simulations; where a CFD application engineer provides geometry, boundary conditions, and flow parameters, and the sketch-to-solution process yields a CFD simulation through automatic, error-based, grid adaptation

Recent Archeological Work in Kachemak Bay, Gulf of Alaska

Excavations since 1974 have built upon de Laguna's pioneering classification of Pacific Eskimo prehistory. The Chugachik site (SEL 033) yielded abundant artifactual and paleoenvironmental information dated mainly between c. 350 B.C. and 250 A.D. While artifacts were scarce at Cottonwood Creek (SEL 030), dated at about 200 A.D., data on human biology, paleopathology, social stratification and mortuary ceremonialism were recovered. The Yukon Island Fox Farm Bluff site (SEL 041) dates to c. 500-900 A.D. and yielded a new culture showing connections with the Alaska Peninsula. Future research should focus on the earlier prehistory of the bay, the classic problem of the Pacific Eskimo-Tanaina Athapaskan transition, and the paleoenvironmental record

Zygotic Expression of the caudal Homolog pal-1 Is Required for Posterior Patterning in Caenorhabditis elegans Embryogenesis

AbstractPrevious work has shown that the Caenorhabditis elegans gene pal-1, a homolog of Drosophila caudal, is required maternally for blastomere specification in the early embryo and postembryonically for tail development in males. We show here that embryonic (zygotic) transcription of pal-1 is also required for posterior patterning during later embryogenesis. Embryos homozygous for strong loss-of-function mutations arrest as nonviable L1 larvae with gross posterior defects. PAL-1 protein produced from zygotic transcripts is expressed dynamically during gastrulation and morphogenesis in specific cells of all major lineages except the germ line. Most expressing cells are undergoing cell movements or forming midline structures or both. Mutant embryos exhibit defects involving most of the expressing cells. Aberrant early cell positions are observed in posterior hypodermis, both in the C-lineage cells that express pal-1 and in the neighboring hypodermal seam cell precursors, which do not, as well as in posterior muscle derived from the C and D lineages. Defects in late gastrulation, ventral hypodermal enclosure, and formation of the rectum result from failures of cell movements of ABp and MS descendants. Limited mosaic analysis supports the view that most of the required pal-1 functions are cell autonomous

MICROBIAL BASED CHLORINATED ETHENE DESTRUCTION

A mixed culture of Dehalococcoides species is provided that has an ability to catalyze the complete dechlorination of polychlorinated ethenes such as PCE, TCE, cDCE, 1,1-DCE and vinyl chloride as well as halogenated ethanes such as 1,2-DCA and EDB. The mixed culture demonstrates the ability to achieve dechlorination even in the presence of high source concentrations of chlorinated ethenes