An IGF-I promoter polymorphism modifies the relationships between birth weight and risk factors for cardiovascular disease and diabetes at age 36

BACKGROUND: Biochemical testing for pheochromocytoma by measurement of fractionated plasma metanephrines is limited by false positive rates of up to 18% in people without known genetic predisposition to the disease. The plasma normetanephrine fraction is responsible for most false positives and plasma normetanephrine increases with age. The objective of this study was to determine if we could improve the specificity of fractionated plasma measurements, by statistically adjusting for age. METHODS: An age-adjusted metanephrine score was derived using logistic regression from 343 subjects (including 33 people with pheochromocytoma) who underwent fractionated plasma metanephrine measurements as part of investigations for suspected pheochromocytoma at Mayo Clinic Rochester (derivation set). The performance of the age-adjusted score was validated in a dataset of 158 subjects (including patients 23 with pheochromocytoma) that underwent measurements of fractionated plasma metanephrines at Mayo Clinic the following year (validation dataset). None of the participants in the validation dataset had known genetic predisposition to pheochromocytoma. RESULTS: The sensitivity of the age-adjusted metanephrine score was the same as that of traditional interpretation of fractionated plasma metanephrine measurements, yielding a sensitivity of 100% (23/23, 95% confidence interval [CI] 85.7%, 100%). However, the false positive rate with traditional interpretation of fractionated plasma metanephrine measurements was 16.3% (22/135, 95% CI, 11.0%, 23.4%) and that of the age-adjusted score was significantly lower at 3.0% (4/135, 95% CI, 1.2%, 7.4%) (p < 0.001 using McNemar's test). CONCLUSION: An adjustment for age in the interpretation of results of fractionated plasma metanephrines may significantly decrease false positives when using this test to exclude sporadic pheochromocytoma. Such improvements in false positive rate may result in savings of expenditures related to confirmatory imaging.     

Design of a data model for developing laboratory information management and analysis systems for protein production

Data management has emerged as one of the central issues in the high-throughput processes of taking a protein target sequence through to a protein sample. To simplify this task, and following extensive consultation with the international structural genomics community, we describe here a model of the data related to protein production. The model is suitable for both large and small facilities for use in tracking samples, experiments, and results through the many procedures involved. The model is described in Unified Modeling Language (UML). In addition, we present relational database schemas derived from the UML. These relational schemas are already in use in a number of data management projects.     

Human metabolic phenotypes link directly to specific dietary preferences in healthy individuals

Individual human health is determined by a complex interplay between genes, environment, diet, lifestyle, and symbiotic gut microbial activity. Here, we demonstrate a new "nutrimetabonomic" approach in which spectroscopically generated metabolic phenotypes are correlated with behavioral/psychological dietary preference, namely, "chocolate desiring" or "chocolate indifferent". Urinary and plasma metabolic phenotypes are characterized by differential metabolic biomarkers, measured using 1H NMR spectroscopy, including the postprandial lipoprotein profile and gut microbial co-metabolism. These data suggest that specific dietary preferences can influence basal metabolic state and gut microbiome activity that in turn may have long-term health consequences to the host. Nutrimetabonomics appears as a promising approach for the classification of dietary responses in populations and personalized nutritional management.     

A mixed-model quantitative trait loci (QTL) analysis for multiple-environment trial data using environmental covariables for QTL-by-environment interactions, with an example in maize

Complex quantitative traits of plants as measured on collections of genotypes across multiple environments are the outcome of processes that depend in intricate ways on genotype and environment simultaneously. For a better understanding of the genetic architecture of such traits as observed across environments, genotype-by-environment interaction should be modeled with statistical models that use explicit information on genotypes and environments. The modeling approach we propose explains genotype-by-environment interaction by differential quantitative trait locus (QTL) expression in relation to environmental variables. We analyzed grain yield and grain moisture for an experimental data set composed of 976 F(5) maize testcross progenies evaluated across 12 environments in the U.S. corn belt during 1994 and 1995. The strategy we used was based on mixed models and started with a phenotypic analysis of multi-environment data, modeling genotype-by-environment interactions and associated genetic correlations between environments, while taking into account intraenvironmental error structures. The phenotypic mixed models were then extended to QTL models via the incorporation of marker information as genotypic covariables. A majority of the detected QTL showed significant QTL-by-environment interactions (QEI). The QEI were further analyzed by including environmental covariates into the mixed model. Most QEI could be understood as differential QTL expression conditional on longitude or year, both consequences of temperature differences during critical stages of the growth.     

The extended Moran effect and large-scale synchronous fluctuations in the size of great tit and blue tit populations

1. Synchronous fluctuations of geographically separated populations are in general explained by the Moran effect, i.e. a common influence on the local population dynamics of environmental variables that are correlated in space. Empirical support for such a Moran effect has been difficult to provide, mainly due to problems separating out effects of local population dynamics, demographic stochasticity and dispersal that also influence the spatial scaling of population processes. Here we generalize the Moran effect by decomposing the spatial autocorrelation function for fluctuations in the size of great tit Parus major and blue tit Cyanistes caeruleus populations into components due to spatial correlations in the environmental noise, local differences in the strength of density regulation and the effects of demographic stochasticity. 2. Differences between localities in the strength of density dependence and nonlinearity in the density regulation had a small effect on population synchrony, whereas demographic stochasticity reduced the effects of the spatial correlation in environmental noise on the spatial correlations in population size by 21.7% and 23.3% in the great tit and blue tit, respectively. 3. Different environmental variables, such as beech mast and climate, induce a common environmental forcing on the dynamics of central European great and blue tit populations. This generates synchronous fluctuations in the size of populations located several hundred kilometres apart. 4. Although these environmental variables were autocorrelated over large areas, their contribution to the spatial synchrony in the population fluctuations differed, dependent on the spatial scaling of their effects on the local population dynamics. We also demonstrate that this effect can lead to the paradoxical result that a common environmental variable can induce spatial desynchronization of the population fluctuations. 5. This demonstrates that a proper understanding of the ecological consequences of environmental changes, especially those that occur simultaneously over large areas, will require information about the spatial scaling of their effects on local population dynamics.     

Angiogenesis is not impaired in connective tissue growth factor (CTGF) knock-out mice.

Connective tissue growth factor (CTGF) is a member of the CCN family of growth factors. CTGF is important in scarring, wound healing, and fibrosis. It has also been implicated to play a role in angiogenesis, in addition to vascular endothelial growth factor (VEGF). In the eye, angiogenesis and subsequent fibrosis are the main causes of blindness in conditions such as diabetic retinopathy. We have applied three different models of angiogenesis to homozygous CTGF(-/-) and heterozygous CTGF(+/-) mice to establish involvement of CTGF in neovascularization. CTGF(-/-) mice die around birth. Therefore, embryonic CTGF(-/-), CTGF(+/-), and CTGF(+/+) bone explants were used to study in vitro angiogenesis, and neonatal and mature CTGF(+/-) and CTGF(+/+) mice were used in models of oxygen-induced retinopathy and laser-induced choroidal neovascularization. Angiogenesis in vitro was independent of the CTGF genotype in both the presence and the absence of VEGF. Oxygen-induced vascular pathology in the retina, as determined semi-quantitatively, and laser-induced choroidal neovascularization, as determined quantitatively, were also not affected by the CTGF genotype. Our data show that downregulation of CTGF levels does not affect neovascularization, indicating distinct roles of VEGF and CTGF in angiogenesis and fibrosis in eye conditions.     

A quantitative model for linking Na+/Ca2+ exchanger to SERCA during refilling of the sarcoplasmic reticulum to sustain [Ca2+] oscillations in vascular smooth muscle

We have developed a quantitative model for the creation of cytoplasmic Ca²⁺ gradients near the inner surface of the plasma membrane (PM). In particular we simulated the refilling of the sarcoplasmic reticulum (SR) via PM–SR junctions during asynchronous [Ca²⁺]_i oscillations in smooth muscle cells of the rabbit inferior vena cava. We have combined confocal microscopy data on the [Ca²⁺]_i oscillations, force transduction data from cell contraction studies and electron microscopic images to build a basis for computational simulations that model the transport of calcium ions from Na⁺/Ca²⁺ exchangers (NCX) on the PM to sarcoplasmic/endoplasmic reticulum Ca²⁺ ATPase (SERCA) pumps on the SR as a three-dimensional random walk through the PM–SR junctional cytoplasmic spaces. Electron microscopic ultrastructural images of the smooth muscle cells were elaborated with software algorithms to produce a very clear and dimensionally accurate picture of the PM–SR junctions. From this study, we conclude that it is plausible and possible for enough Ca²⁺ to pass through the PM–SR junctions to replete the SR during the regenerative Ca²⁺ release, which underlies agonist induced asynchronous Ca²⁺ oscillations in vascular smooth muscle.     

Biomechanical warfare in ecology; negative interactions between species by habitat modification

Since the introduction of the term ecosystem engineering by Jones et al. many studies have focused on positive, facilitative interactions caused by ecosystem engineering. Much less emphasis has been placed on the role of ecosystem engineering in causing negative interactions between species. Here, we report on negative interactions between two well known ecosystem engineers occurring at the interface of salt marsh and intertidal flat (i.e. common cordgrass Spartina anglica and lugworms Arenicola marina ), via modification of their joint habitat. A field survey indicated that, although both species share a common habitat, they rarely co-occur on small spatial scales (<1 m). Experiments in the field and in mesocosms reveal that establishment of small Spartina plants is inhibited in Arenicola -dominated patches because of low sediment stability induced by the lugworms. In turn, Arenicola establishment in Spartina -dominated patches is limited by high silt content, compactness and dense rooting of the sediment caused by Spartina presence. Our results show that negative interactions by modification of the environment can result in rapid mutual exclusion, particularly if adverse effects of habitat modification are strong and if both species exhibit positive feedbacks. This illustrates the potential for negative interactions via the environment to affect community composition.     

Bidirectional Propagation of Signals and Nutrients in Fungal Networks via Specialized Hyphae

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