Actual neighborhood-level crime predicts body mass index z-score changes in a multi-racial/ethnic sample of children

Longitudinal studies are warranted to clarify the influence crime has on health outcomes in children especially children representing multiple racial/ethnic backgrounds. To address this need, the current study examined whether neighborhood-level crime predicted changes in body mass index z (BMIz) scores in 373 White (W), 627 African American (AA), 1020 Hispanic (H), and 88 Asian (A), five to ten year-old boys and girls living in urban neighborhoods. Heights and weights were assessed at baseline (2012) and three-years later and used to calculate BMIz scores. Characteristics of zip codes where students lived during the three-year period were obtained at baseline from various sources. The Crime Risk Index (CRI) for each zip code was calculated using actual crime statistics. Multiple linear regression analyses were conducted to examine associations between baseline CRI and follow-up BMIz scores while controlling for other variables including BMIz at baseline. The CRI and BMIz scores differed significantly by race/ethnicity with the highest values for both noted in H. Regression analyses indicated that the CRI accounted for a significant percentage of the variance in follow-up BMIz scores in the overall sample. When race/ethnicity was considered, the CRI predicted follow-up BMIz scores only in W children. The CRI was not significantly associated with BMIz scores in the other races/ethnicities. The impact actual, neighborhood-level crime has on BMI in children is complex. Based on the existing evidence, considering actual crime as a primary target in obesity prevention would be premature especially in racial/ethnicity minority children living in urban areas

Generation of a Kupffer Cell-evading Adenovirus for Systemic and Liver-directed Gene Transfer

As much as 90% of an intravenously (i.v.) injected dose of adenovirus serotype 5 (Ad5) is absorbed and destroyed by liver Kupffer cells. Viruses that escape these cells can then transduce hepatocytes after binding factor X (FX). Given that interactions with FX and Kupffer cells are thought to occur on the Ad5 hexon protein, we replaced its exposed hypervariable regions (HVR) with those from Ad6. When tested in vivo in BALB/c mice and in hamsters, the Ad5/6 chimera mediated \u3e10 times higher transduction in the liver. This effect was not due to changes in FX binding. Rather, Ad5/6 appeared to escape Kupffer cell uptake as evidenced by producing no Kupffer cell death in vivo, not requiring predosing in vivo, and being phagocytosed less efficiently by macrophages in vitro compared to Ad5. When tested as a helper-dependent adenovirus (Ad) vector, Ad5/6 mediated higher luciferase and factor IX transgene expression than either helper-dependent adenoviral 5 (HD-Ad5) or HD-Ad6 vectors. These data suggest that the Ad5/6 hexon-chimera evades Kupffer cells and may have utility for systemic and liver-directed therapies

Generation of a Kupffer Cell-evading Adenovirus for Systemic and Liver-directed Gene Transfer

As much as 90% of an intravenously (i.v.) injected dose of adenovirus serotype 5 (Ad5) is absorbed and destroyed by liver Kupffer cells. Viruses that escape these cells can then transduce hepatocytes after binding factor X (FX). Given that interactions with FX and Kupffer cells are thought to occur on the Ad5 hexon protein, we replaced its exposed hypervariable regions (HVR) with those from Ad6. When tested in vivo in BALB/c mice and in hamsters, the Ad5/6 chimera mediated \u3e10 times higher transduction in the liver. This effect was not due to changes in FX binding. Rather, Ad5/6 appeared to escape Kupffer cell uptake as evidenced by producing no Kupffer cell death in vivo, not requiring predosing in vivo, and being phagocytosed less efficiently by macrophages in vitro compared to Ad5. When tested as a helper-dependent adenovirus (Ad) vec- tor, Ad5/6 mediated higher luciferase and factor IX trans- gene expression than either helper-dependent adenoviral 5 (HD-Ad5) or HD-Ad6 vectors. These data suggest that the Ad5/6 hexon-chimera evades Kupffer cells and may have utility for systemic and liver-directed therapies

Species D Adenoviruses as Oncolytics against B-cell Cancers

Purpose: Oncolytic viruses are self-amplifying anticancer agents that make use of the natural ability of viruses to kill cells. Adenovirus serotype 5 (Ad5) has been extensively tested against solid cancers, but less so against B-cell cancers because these cells do not generally express the coxsackie and adenoviral receptor (CAR). To determine whether other adenoviruses might have better potency, we mined the adenovirus virome of 55 serotypes for viruses that could kill B-cell cancers. Experimental Design: Fifteen adenoviruses selected to represent Ad species B, C, D, E, and F were tested in vitro against cell lines and primary patient B-cell cancers for their ability to infect, replicate in, and kill these cells. Select viruses were also tested against B-cell cancer xenografts in immunodeficient mice. Results: Species D adenoviruses mediated most robust killing against a range of B-cell cancer cell lines, against primary patient marginal zone lymphoma cells, and against primary patient CD138þ myeloma cells in vitro. When injected into xenografts in vivo, single treatment with select species D viruses Ad26 and Ad45 delayed lymphoma growth. Conclusions: Relatively unstudied species Dadenoviruses have a unique ability to infect and replicate in B-cell cancers as compared with other adenovirus species. These data suggest these viruses have unique biology in B cells and support translation of novel species D adenoviruses as oncolytics against B-cell cancers

Neurofilament is superior to cytokeratin 20 in supporting cutaneous origin for neuroendocrine carcinoma

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147795/1/his13758.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147795/2/his13758_am.pd

Punctuated equilibria and 1/f noise in a biological coevolution model with individual-based dynamics

We present a study by linear stability analysis and large-scale Monte Carlo simulations of a simple model of biological coevolution. Selection is provided through a reproduction probability that contains quenched, random interspecies interactions, while genetic variation is provided through a low mutation rate. Both selection and mutation act on individual organisms. Consistent with some current theories of macroevolutionary dynamics, the model displays intermittent, statistically self-similar behavior with punctuated equilibria. The probability density for the lifetimes of ecological communities is well approximated by a power law with exponent near -2, and the corresponding power spectral densities show 1/f noise (flicker noise) over several decades. The long-lived communities (quasi-steady states) consist of a relatively small number of mutualistically interacting species, and they are surrounded by a ``protection zone'' of closely related genotypes that have a very low probability of invading the resident community. The extent of the protection zone affects the stability of the community in a way analogous to the height of the free-energy barrier surrounding a metastable state in a physical system. Measures of biological diversity are on average stationary with no discernible trends, even over our very long simulation runs of approximately 3.4x10^7 generations.Comment: 20 pages RevTex. Minor revisions consistent with published versio

Statistical mechanics of voting

Decision procedures aggregating the preferences of multiple agents can produce cycles and hence outcomes which have been described heuristically as `chaotic'. We make this description precise by constructing an explicit dynamical system from the agents' preferences and a voting rule. The dynamics form a one dimensional statistical mechanics model; this suggests the use of the topological entropy to quantify the complexity of the system. We formulate natural political/social questions about the expected complexity of a voting rule and degree of cohesion/diversity among agents in terms of random matrix models---ensembles of statistical mechanics models---and compute quantitative answers in some representative cases.Comment: 9 pages, plain TeX, 2 PostScript figures included with epsf.tex (ignore the under/overfull \vbox error messages

The maximum entropy formalism and the idiosyncratic theory of biodiversity

Why does the neutral theory, which is based on unrealistic assumptions, predict diversity patterns so accurately? Answering questions like this requires a radical change in the way we tackle them. The large number of degrees of freedom of ecosystems pose a fundamental obstacle to mechanistic modelling. However, there are tools of statistical physics, such as the maximum entropy formalism (MaxEnt), that allow transcending particular models to simultaneously work with immense families of models with different rules and parameters, sharing only well-established features. We applied MaxEnt allowing species to be ecologically idiosyncratic, instead of constraining them to be equivalent as the neutral theory does. The answer we found is that neutral models are just a subset of the majority of plausible models that lead to the same patterns. Small variations in these patterns naturally lead to the main classical species abundance distributions, which are thus unified in a single framework

Robustness Through Regime Flips in Collapsing Ecological Networks

© 2019, Crown. There has been considerable progress in our perception of organized complexity in recent years. Recurrent debates on the dynamics and stability of complex systems have provided several insights, but it is very difficult to find identifiable patterns in the relationship between complex network structure and dynamics. Traditionally an arena for theoreticians, much of this research has been invigorated by demonstration of alternate stable states in real world ecosystems such as lakes, coral reefs, forests and grasslands. In this work, we use topological connectivity attributes of eighty six ecological networks and link these with random and targeted perturbations, to obtain general patterns of behaviour of complex real world systems. We have analyzed the response of each ecological network to individual, grouped and cascading extinctions, and the results suggest that most networks are robust to loss of specialists until specific thresholds are reached in terms of network geodesics. If the extinctions persist beyond these thresholds, a state change or ‘flip’ occurs and the structural properties are altered drastically, although the network does not collapse. As opposed to simpler or smaller networks, we find larger networks to contain multiple states that may in turn, ensure long-term persistence, suggesting that complexity can endow resilience to ecosystems. The concept of critical transitions in ecological networks and the implications of these findings for complex systems characterized by networks are likely to be profound with immediate significance for ecosystem conservation, invasion biology and restoration ecology.Non

Robust estimation of microbial diversity in theory and in practice

Quantifying diversity is of central importance for the study of structure, function and evolution of microbial communities. The estimation of microbial diversity has received renewed attention with the advent of large-scale metagenomic studies. Here, we consider what the diversity observed in a sample tells us about the diversity of the community being sampled. First, we argue that one cannot reliably estimate the absolute and relative number of microbial species present in a community without making unsupported assumptions about species abundance distributions. The reason for this is that sample data do not contain information about the number of rare species in the tail of species abundance distributions. We illustrate the difficulty in comparing species richness estimates by applying Chao's estimator of species richness to a set of in silico communities: they are ranked incorrectly in the presence of large numbers of rare species. Next, we extend our analysis to a general family of diversity metrics ("Hill diversities"), and construct lower and upper estimates of diversity values consistent with the sample data. The theory generalizes Chao's estimator, which we retrieve as the lower estimate of species richness. We show that Shannon and Simpson diversity can be robustly estimated for the in silico communities. We analyze nine metagenomic data sets from a wide range of environments, and show that our findings are relevant for empirically-sampled communities. Hence, we recommend the use of Shannon and Simpson diversity rather than species richness in efforts to quantify and compare microbial diversity.Comment: To be published in The ISME Journal. Main text: 16 pages, 5 figures. Supplement: 16 pages, 4 figure