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To assess the utility of an automated, statistically-based outbreak detection system to identify clusters of hospital-acquired microorganisms.
Multicenter retrospective cohort study.
The study included 43 hospitals using a common infection prevention surveillance system.
A space–time permutation scan statistic was applied to hospital microbiology, admission, discharge, and transfer data to identify clustering of microorganisms within hospital locations and services. Infection preventionists were asked to rate the importance of each cluster. A convenience sample of 10 hospitals also provided information about clusters previously identified through their usual surveillance methods.
We identified 230 clusters in 43 hospitals involving Gram-positive and -negative bacteria and fungi. Half of the clusters progressed after initial detection, suggesting that early detection could trigger interventions to curtail further spread. Infection preventionists reported that they would have wanted to be alerted about 81% of these clusters. Factors associated with clusters judged to be moderately or highly concerning included high statistical significance, large size, and clusters involving Clostridioides difficile or multidrug-resistant organisms. Based on comparison data provided by the convenience sample of hospitals, only 9 (18%) of 51 clusters detected by usual surveillance met statistical significance, and of the 70 clusters not previously detected, 58 (83%) involved organisms not routinely targeted by the hospitals’ surveillance programs. All infection prevention programs felt that an automated outbreak detection tool would improve their ability to detect outbreaks and streamline their work.
Automated, statistically-based outbreak detection can increase the consistency, scope, and comprehensiveness of detecting hospital-associated transmission.
OBJECTIVES/SPECIFIC AIMS: Our objective was to examine serum E2 levels in dcSSc males in relation to disease characteristics (i.e autoanitbody profile and internal organ involvement) and its impact on survival. METHODS/STUDY POPULATION: We measured serum E2 levels in 83 dcSSc men >50 years old from the University of Pittsburgh Scleroderma Center and healthy controls of similar age. Using statistical modeling, we examined the associations between circulating E2 levels, internal organ involvement, autoantibody profiles, and survival. RESULTS/ANTICIPATED RESULTS: Male dcSSc patients had significantly higher serum E2 levels compared to healthy male controls and compared to dcSSc post-menopausal women of similar age. Male dcSSc patients with high serum E2 levels had significantly more heart involvement and worse survival. Using Cox regression modeling for risk of death, increasing serum E2 levels in anti-Scl-70 antibody positive dcSSc males were associated an increased risk of death. DISCUSSION/SIGNIFICANCE OF IMPACT: DcSSc male patients have higher levels of E2 compared to healthy controls and dcSSc postmenopausal women. Elevated serum E2 levels in dcSSc males >50 are associated with heart involvement and, if anti-Scl-70 antibody positive, worse survival. Our current study expands on our previous work, not only that that E2 exerts pro-fibrotic effects on skin, but also internal organ involvement, overall survival. These data suggest an important role of estrogen imbalance in SSc.
Inequalities in infant mortality rates (IMRs) are rising in some low- and middle-income countries (LMICs) and decreasing in others, but the explanation for these divergent trends is unclear. We investigate whether government expenditures and redistribution are associated with reductions in inequalities in IMRs. We estimated country-level fixed-effects panel regressions for 48 LMICs (142 country observations). Slope and Relative Indices of Inequality in IMRs (SII and RII) were calculated from Demographic and Health Surveys between 1993 and 2013. RII and SII were regressed on government expenditure (total, health and non-health) and redistribution, controlling for gross domestic product (GDP), private health expenditures, a democracy indicator, country fixed effects and time. Mean SII and RII was 39.12 and 0.69, respectively. In multivariate models, a 1 percentage point increase in total government expenditure (% of GDP) was associated with a decrease in SII of −2.468 [95% confidence intervals (CIs): −4.190, −0.746] and RII of −0.026 (95% CIs: −0.048, −0.004). Lower inequalities were associated with higher non-health government expenditure, but not higher government health expenditure. Associations with inequalities were non-significant for GDP, government redistribution, and private health expenditure. Understanding how non-health government expenditure reduces inequalities in IMR, and why health expenditures may not, will accelerate progress towards the Sustainable Development Goals.
Whether monozygotic (MZ) and dizygotic (DZ) twins differ from each other in a variety of phenotypes is important for genetic twin modeling and for inferences made from twin studies in general. We analyzed whether there were differences in individual, maternal and paternal education between MZ and DZ twins in a large pooled dataset. Information was gathered on individual education for 218,362 adult twins from 27 twin cohorts (53% females; 39% MZ twins), and on maternal and paternal education for 147,315 and 143,056 twins respectively, from 28 twin cohorts (52% females; 38% MZ twins). Together, we had information on individual or parental education from 42 twin cohorts representing 19 countries. The original education classifications were transformed to education years and analyzed using linear regression models. Overall, MZ males had 0.26 (95% CI [0.21, 0.31]) years and MZ females 0.17 (95% CI [0.12, 0.21]) years longer education than DZ twins. The zygosity difference became smaller in more recent birth cohorts for both males and females. Parental education was somewhat longer for fathers of DZ twins in cohorts born in 1990–1999 (0.16 years, 95% CI [0.08, 0.25]) and 2000 or later (0.11 years, 95% CI [0.00, 0.22]), compared with fathers of MZ twins. The results show that the years of both individual and parental education are largely similar in MZ and DZ twins. We suggest that the socio-economic differences between MZ and DZ twins are so small that inferences based upon genetic modeling of twin data are not affected.
The Reverse Engineering Road to Computing Life
Philip K. Maini, Mathematical Institute, Andrew Wiles Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK,
Thomas E. Woolley, Mathematical Institute, Andrew Wiles Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK,
Eamonn A. Gaffney, Mathematical Institute, Andrew Wiles Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK,
Ruth E. Baker, Mathematical Institute, Andrew Wiles Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK
Elucidating the mechanisms underlying the formation of structure and form is one of the great challenges in developmental biology. From an initial, seemingly spatially uniform mass of cells, emerge the spectacular patterns that characterise the animal kingdom – butterfly wing patterns, animal coat markings, skeletal structures, skin organs, horns etc. (Figure 9.1). Although genes obviously play a key role, the study of genetics alone does not tell us why certain genes are switched on or off in specific places and how the properties they impart to cells result in the highly coordinated emergence of pattern and form. Modern genomics has revealed remarkable molecular similarity among different animal species. Specifically, biological diversity typically emerges from differences in regulatory DNA rather than detailed protein coding sequences. This implicit universality highlights that many aspects of animal development can be understood from studies of exemplar species such as fruit flies and zebrafish while also motivating theoretical studies to explore and understand the underlying common mechanisms beyond a simply descriptive level.
However, when Alan Turing wrote his seminal paper, ‘The chemical basis of morphogenesis’ (Turing, 1952), such observations were many decades away. At that time biology was following a very traditional classification route of list-making activities. Indeed, there was very little theory regarding development other than D'Arcy Thompson's classic 1917 work (see Thompson, 1992, for the abridged version) exploring how biological forms arose, though even this was still very much at the descriptive rather than the mechanistic level.
Undeterred, Turing started exploring the question of how developmental systems might undertake symmetry-breaking and thus create and amplify structure from seeming uniformity. For example, if one looks at a cross-section of a tree trunk, it has circular symmetry which is broken when a branch starts to grow outwards. Turing proposed an underlying mechanism explaining how asymmetric structure could emerge dynamically, without innate hardwiring. In particular, he described how a symmetric pattern, for instance of a growth hormone, could break up so that more hormone was concentrated on one part of the circle, thus inducing extra growth there.
In order to achieve such behaviour Turing came up with a truly ingenious theory. He considered a system of chemicals reacting with each other and assumed that in the well-mixed case (no spatial heterogeneities) this system exhibited an equilibrium (steady) state which was stable.
A trend toward greater body size in dizygotic (DZ) than in monozygotic (MZ) twins has been suggested by some but not all studies, and this difference may also vary by age. We analyzed zygosity differences in mean values and variances of height and body mass index (BMI) among male and female twins from infancy to old age. Data were derived from an international database of 54 twin cohorts participating in the COllaborative project of Development of Anthropometrical measures in Twins (CODATwins), and included 842,951 height and BMI measurements from twins aged 1 to 102 years. The results showed that DZ twins were consistently taller than MZ twins, with differences of up to 2.0 cm in childhood and adolescence and up to 0.9 cm in adulthood. Similarly, a greater mean BMI of up to 0.3 kg/m2 in childhood and adolescence and up to 0.2 kg/m2 in adulthood was observed in DZ twins, although the pattern was less consistent. DZ twins presented up to 1.7% greater height and 1.9% greater BMI than MZ twins; these percentage differences were largest in middle and late childhood and decreased with age in both sexes. The variance of height was similar in MZ and DZ twins at most ages. In contrast, the variance of BMI was significantly higher in DZ than in MZ twins, particularly in childhood. In conclusion, DZ twins were generally taller and had greater BMI than MZ twins, but the differences decreased with age in both sexes.
For over 100 years, the genetics of human anthropometric traits has attracted scientific interest. In particular, height and body mass index (BMI, calculated as kg/m2) have been under intensive genetic research. However, it is still largely unknown whether and how heritability estimates vary between human populations. Opportunities to address this question have increased recently because of the establishment of many new twin cohorts and the increasing accumulation of data in established twin cohorts. We started a new research project to analyze systematically (1) the variation of heritability estimates of height, BMI and their trajectories over the life course between birth cohorts, ethnicities and countries, and (2) to study the effects of birth-related factors, education and smoking on these anthropometric traits and whether these effects vary between twin cohorts. We identified 67 twin projects, including both monozygotic (MZ) and dizygotic (DZ) twins, using various sources. We asked for individual level data on height and weight including repeated measurements, birth related traits, background variables, education and smoking. By the end of 2014, 48 projects participated. Together, we have 893,458 height and weight measures (52% females) from 434,723 twin individuals, including 201,192 complete twin pairs (40% monozygotic, 40% same-sex dizygotic and 20% opposite-sex dizygotic) representing 22 countries. This project demonstrates that large-scale international twin studies are feasible and can promote the use of existing data for novel research purposes.
In North America, terrestrial records of biodiversity and climate change that span Marine Oxygen Isotope Stage (MIS) 5 are rare. Where found, they provide insight into how the coupling of the ocean–atmosphere system is manifested in biotic and environmental records and how the biosphere responds to climate change. In 2010–2011, construction at Ziegler Reservoir near Snowmass Village, Colorado (USA) revealed a nearly continuous, lacustrine/wetland sedimentary sequence that preserved evidence of past plant communities between ~140 and 55 ka, including all of MIS 5. At an elevation of 2705 m, the Ziegler Reservoir fossil site also contained thousands of well-preserved bones of late Pleistocene megafauna, including mastodons, mammoths, ground sloths, horses, camels, deer, bison, black bear, coyotes, and bighorn sheep. In addition, the site contained more than 26,000 bones from at least 30 species of small animals including salamanders, otters, muskrats, minks, rabbits, beavers, frogs, lizards, snakes, fish, and birds. The combination of macro- and micro-vertebrates, invertebrates, terrestrial and aquatic plant macrofossils, a detailed pollen record, and a robust, directly dated stratigraphic framework shows that high-elevation ecosystems in the Rocky Mountains of Colorado are climatically sensitive and varied dramatically throughout MIS 5.
Urban ethnic minority youth are often exposed to high levels of aggression and violence. As such, many aggression intervention programs that have been designed with suburban nonethnic minority youth have been used or slightly adapted in order to try and meet the needs of high-risk urban youth. The current study contributes to the literature base by examining how well a range of social–cognitive, emotional distress and victimization, and prosocial factors are related to youth aggression in a sample of urban youth. This study utilized data gathered from 109 9- to 15-year-old youth (36.7% male; 84.4% African American) and their parents or caregivers. A series of hierarchical multiple regressions were fit predicting youth aggression from social–cognitive variables, victimization and distress, and prosocial variables, controlling for youth gender and age. Each set of variables explained a significant and unique amount of the variance in youth aggressive behavior. The full model including all predictors accounted for 41% of the variance in aggression. Models suggest that youth with stronger beliefs supportive of violence, youth who experience more overt victimization, and youth who experience greater distress in overtly aggressive situations are likely to be more aggressive. In contrast, youth with higher self-esteem and youth who endorse greater leadership efficacy are likely to be less aggressive. Contrary to hypotheses, hostile attributional bias and knowledge of social information processing, experience of relational victimization, distress in relationally aggressive situations, and community engagement were not associated with aggression. Our study is one of the first to address these important questions for low-income, predominately ethnic minority urban youth, and it has clear implications for adapting aggression prevention programs to be culturally sensitive for urban African American youth.
Our aim was to describe the epidemiology and incidence of community-onset invasive S. aureus disease in children presenting to our hospital, and to compare the clonal complexes and virulence genes of S. aureus strains causing invasive and non-invasive disease. The virulence gene repertoire of invasive disease isolates was characterized using DNA microarray and compared with the virulence gene repertoire of non-invasive S. aureus isolates. Over the study period, 163 children had an invasive S. aureus infection. There was no difference in the distribution of clonal complexes or in the prevalence of genes encoding virulence factors between invasive and non-invasive isolates. Future research should include a strong focus on identifying the host and environmental factors that, along with organism virulence factors, are contributing to the patterns of invasive S. aureus disease observed in New Zealand.
The distribution of alloying elements in the constituent phases of a C-containing γ-TiAl based alloy has been characterized locally by atom probe tomography. The major elements of the alloy under consideration – Ti, Al, Nb, and Mo – are distributed uniformly within each of the constituent phases. Furthermore, Mo is preferentially dissolved in the βo-phase, whereas Nb content is similar in all phases. The selected C concentration of the alloy is below the overall solubility limit as no precipitates have been observed. Therefore, C is enriched in the α2-phase, whereas the βo-phase is depleted of C. In addition, βo/γ-interfaces have been prepared by site specific sample preparation and characterized by atom probe tomography. Segregation of Mo and C into the interfaces and their close vicinity was observed.
After almost three decades of intensive fundamental research and development activities intermetallic titanium aluminides based on the -TiAl phase have found applications in automotive and aircraft engine industries. The advantages of this class of innovative high-temperature materials are their low density as well as their good strength and creep properties up to 750°C. A drawback, however, is their limited ductility at room temperature, which is reflected by a low plastic strain at fracture. This behavior can be attributed to a limited dislocation movement along with microstructural inhomogeneity. Advanced TiAl alloys, such as β-solidifying TNM™ alloys, are complex multi-phase materials which can be processed by ingot or powder metallurgy as well as precision casting methods. Each production process leads to specific microstructures which can be altered and optimized by thermo-mechanical processing and/or subsequent heat-treatments. The background of these heat-treatments is at least twofold, i.e. concurrent increase of ductility at room temperature and creep strength at elevated temperature. In order to achieve this goal the knowledge of the occurring solidification processes and phase transformation sequences is essential. Therefore, thermodynamic calculations were conducted to predict phase fraction diagrams of engineering TiAl alloys. After experimental verification, these phase diagrams provided the base for the development of heat treatments to adjust balanced mechanical properties. To determine the influence of deformation and kinetic aspects, sophisticated ex- and in-situ methods have been employed to investigate the evolution of the microstructure during thermo-mechanical processing and subsequent multi-step heat-treatments. For example, in-situ high-energy X-ray diffraction was conducted to study dynamic recovery and recrystallization processes during hot-deformation tests. Summarizing all results a consistent picture regarding microstructure formation and its impact on mechanical properties in TNM alloys can be given.
An understanding of molecular interactions is essential for insight into biological systems at the molecular scale. Among the various components of molecular interactions, electrostatics are of special importance because of their long-range nature and their influence on polar or charged molecules, including water, aqueous ions, proteins, nucleic acids, carbohydrates, and membrane lipids. In particular, robust models of electrostatic interactions are essential for understanding the solvation properties of biomolecules and the effects of solvation upon biomolecular folding, binding, enzyme catalysis, and dynamics. Electrostatics, therefore, are of central importance to understanding biomolecular structure and modeling interactions within and among biological molecules. This review discusses the solvation of biomolecules with a computational biophysics view toward describing the phenomenon. While our main focus lies on the computational aspect of the models, we provide an overview of the basic elements of biomolecular solvation (e.g. solvent structure, polarization, ion binding, and non-polar behavior) in order to provide a background to understand the different types of solvation models.