The Ras Antagonist,Farnesylthiosalicylic Acid (FTS), Decreases Fibrosis and Improves Muscle Strength in dy2J/dy2J Mouse Model of Muscular Dystrophy

The Ras superfamily of guanosine-triphosphate (GTP)-binding proteins regulates a diverse spectrum of intracellular processes involved in inflammation and fibrosis. Farnesythiosalicylic acid (FTS) is a unique and potent Ras inhibitor which decreased inflammation and fibrosis in experimentally induced liver cirrhosis and ameliorated inflammatory processes in systemic lupus erythematosus, neuritis and nephritis animal models. FTS effect on Ras expression and activity, muscle strength and fibrosis was evaluated in the dy^2J/dy^2J mouse model of merosin deficient congenital muscular dystrophy. The dy^2J/dy^2J mice had significantly increased RAS expression and activity compared with the wild type mice. FTS treatment significantly decreased RAS expression and activity. In addition, phosphorylation of ERK, a Ras downstream protein, was significantly decreased following FTS treatment in the dy^2J/dy^2J mice. Clinically, FTS treated mice showed significant improvement in hind limb muscle strength measured by electronic grip strength meter. Significant reduction of fibrosis was demonstrated in the treated group by quantitative Sirius Red staining and lower muscle collagen content. FTS effect was associated with significantly inhibition of both MMP-2 and MMP-9 activities. We conclude that active RAS inhibition by FTS was associated with attenuated fibrosis and improved muscle strength in the dy^2J/dy^2J mouse model of congenital muscular dystrophy.     

Relating neuronal to behavioral performance: variability of optomotor responses in the blowfly

Behavioral responses of an animal vary even when they are elicited by the same stimulus. This variability is due to stochastic processes within the nervous system and to the changing internal states of the animal. To what extent does the variability of neuronal responses account for the overall variability at the behavioral level? To address this question we evaluate the neuronal variability at the output stage of the blowfly''s (Calliphora vicina) visual system by recording from motion-sensitive interneurons mediating head optomotor responses. By means of a simple modelling approach representing the sensory-motor transformation, we predict head movements on the basis of the recorded responses of motion-sensitive neurons and compare the variability of the predicted head movements with that of the observed ones. Large gain changes of optomotor head movements have previously been shown to go along with changes in the animals'' activity state. Our modelling approach substantiates that these gain changes are imposed downstream of the motion-sensitive neurons of the visual system. Moreover, since predicted head movements are clearly more reliable than those actually observed, we conclude that substantial variability is introduced downstream of the visual system.     

Winter locations of red‐throated divers from geolocation and feather isotope signatures

Migratory species have geographically separate distributions during their annual cycle, and these areas can vary between populations and individuals. This can lead to differential stress levels being experienced across a species range. Gathering information on the areas used during the annual cycle of red‐throated divers (RTDs; Gavia stellata) has become an increasingly pressing issue, as they are a species of concern when considering the effects of disturbance from offshore wind farms and the associated ship traffic. Here, we use light‐based geolocator tags, deployed during the summer breeding season, to determine the non‐breeding winter location of RTDs from breeding locations in Scotland, Finland, and Iceland. We also use δ¹⁵N and δ¹³C isotope signatures, from feather samples, to link population‐level differences in areas used in the molt period to population‐level differences in isotope signatures. We found from geolocator data that RTDs from the three different breeding locations did not overlap in their winter distributions. Differences in isotope signatures suggested this spatial separation was also evident in the molting period, when geolocation data were unavailable. We also found that of the three populations, RTDs breeding in Iceland moved the shortest distance from their breeding grounds to their wintering grounds. In contrast, RTDs breeding in Finland moved the furthest, with a westward migration from the Baltic into the southern North Sea. Overall, these results suggest that RTDs breeding in Finland are likely to encounter anthropogenic activity during the winter period, where they currently overlap with areas of future planned developments. Icelandic and Scottish birds are less likely to be affected, due to less ship activity and few or no offshore wind farms in their wintering distributions. We also demonstrate that separating the three populations isotopically is possible and suggest further work to allocate breeding individuals to wintering areas based solely on feather samples.     

Flexible Modeling of Epidemics with an Empirical Bayes Framework

Seasonal influenza epidemics cause consistent, considerable, widespread loss annually in terms of economic burden, morbidity, and mortality. With access to accurate and reliable forecasts of a current or upcoming influenza epidemic’s behavior, policy makers can design and implement more effective countermeasures. This past year, the Centers for Disease Control and Prevention hosted the “Predict the Influenza Season Challenge”, with the task of predicting key epidemiological measures for the 2013–2014 U.S. influenza season with the help of digital surveillance data. We developed a framework for in-season forecasts of epidemics using a semiparametric Empirical Bayes framework, and applied it to predict the weekly percentage of outpatient doctors visits for influenza-like illness, and the season onset, duration, peak time, and peak height, with and without using Google Flu Trends data. Previous work on epidemic modeling has focused on developing mechanistic models of disease behavior and applying time series tools to explain historical data. However, tailoring these models to certain types of surveillance data can be challenging, and overly complex models with many parameters can compromise forecasting ability. Our approach instead produces possibilities for the epidemic curve of the season of interest using modified versions of data from previous seasons, allowing for reasonable variations in the timing, pace, and intensity of the seasonal epidemics, as well as noise in observations. Since the framework does not make strict domain-specific assumptions, it can easily be applied to some other diseases with seasonal epidemics. This method produces a complete posterior distribution over epidemic curves, rather than, for example, solely point predictions of forecasting targets. We report prospective influenza-like-illness forecasts made for the 2013–2014 U.S. influenza season, and compare the framework’s cross-validated prediction error on historical data to that of a variety of simpler baseline predictors.     

Thermal denaturation of nucleic acids in polyacrylamide gels

A system is described for measuring thermal denaturation of nucleic acid fractions directly in polyacrylamide gels. Total nucleic acids were fractionated by disc gel electrophoresis. The buffer within the gel was then exchanged for one commonly used in denaturation studies. Thermal denaturation profiles of DNA and ribosomal RNA in the gel were determined using a specially constructed Gel Carriage to position the appropriate fraction during spectrophotometric measurements. These profiles were compared with denaturation patterns obtained by classical methods in free solution; the two methods yielded similar patterns.Thermal denaturation profiles were also obtained for chloroplast light ribosomal RNA resolved by gel electrophoresis of total plant nucleic acids. Thus, denaturation patterns of individual, minor components present in complex nucleic acid mixtures can be directly measured in gels.     

Bayesian meta-analysis for longitudinal data models using multivariate mixture priors

We propose a class of longitudinal data models with random effects that generalizes currently used models in two important ways. First, the random-effects model is a flexible mixture of multivariate normals, accommodating population heterogeneity, outliers, and nonlinearity in the regression on subject-specific covariates. Second, the model includes a hierarchical extension to allow for meta-analysis over related studies. The random-effects distributions are decomposed into one part that is common across all related studies (common measure), and one part that is specific to each study and that captures the variability intrinsic between patients within the same study. Both the common measure and the study-specific measures are parameterized as mixture-of-normals models. We carry out inference using reversible jump posterior simulation to allow a random number of terms in the mixtures. The sampler takes advantage of the small number of entertained models. The motivating application is the analysis of two studies carried out by the Cancer and Leukemia Group B (CALGB). In both studies, we record for each patient white blood cell counts (WBC) over time to characterize the toxic effects of treatment. The WBCs are modeled through a nonlinear hierarchical model that gathers the information from both studies.     

Tuberin – A New Molecular Target in Alzheimer’s Disease?

Tuberous sclerosis complex (TSC) is a common genetic disorder in which affected individuals develop mental retardation, developmental brain defects and seizures. The TSC gene products, hamartin and tuberin, form a complex, of which tuberin is assumed to be the functional component being involved in a wide variety of different cellular processes. Here we report that tuberin protein levels are decreased in the frontal cortex of patients with Alzheimer’s disease. In addition, tuberin levels are also decreased in Down syndrome brain samples positive for β-amyloid plaques and neurofibrillary tangles. Analysis of NeuN revealed that this regulation is not a consequence of differences in the amount of postmitotic neurons. This first connection of tuberin to another common disease beside TSC stimulates new approaches to investigate the molecular development and to establish new therapeutic strategies.     

Epithelial cells as phagocytes: apoptotic epithelial cells are engulfed by mammary alveolar epithelial cells and repress inflammatory mediator release

Clearance of apoptotic cells is critical to tissue homeostasis and resolution of inflammatory lesions. Macrophages are known to remove dying cells and release anti-inflammatory mediators in response; however, many cells traditionally thought of as poor phagocytes can mediate this function as well. In the lactating mammary gland following weaning, alveolar epithelial cell death is massive, yet the gland involutes rapidly, attaining its prepregnancy state in a matter of days. We found histologic evidence of apoptotic cell phagocytosis by viable mammary epithelial cells (MEC) in the involuting mouse mammary gland. Cultured MEC were able to engulf apoptotic cells in vitro, utilizing many of the same receptors used by macrophages, including the phosphatidylserine receptor (PSR), CD36, the vitronectin receptor alpha(v)beta3, and CD91. In addition, MEC, like macrophages, produced TGFbeta in response to stimulation of the PSR by apoptotic cells or the anti-PSR ab 217G8E9, and downregulated endotoxin-stimulated proinflammatory cytokine production. These data support the hypothesis that amateur phagocytes play a significant role in apoptotic cell clearance and its regulation of inflammation.     

Root-synthesized cytokinin in Arabidopsis is distributed in the shoot by the transpiration stream

To clarify how root-synthesized cytokinins (CKs) are transported to young shoot organs, CK distribution patterns were analysed in free-CK-responsive ARR5::GUS transformants of Arabidopsis thaliana (L.) Heynh. together with free plus bound CKs using specific CK monoclonal antibodies. Plants were subjected to two different growth conditions, completely protected from any air movement, or exposed to gentle wind 3 h before harvesting. In wind-protected plants the strongest ARR5::GUS expression was found in the root cap statocytes, spreading upwards in the vascular cylinder. This pattern in roots was congruent with that found by CK immunolocalization. Shoots of wind-protected plants displayed either no or only low ARR5::GUS expression in the stem vascular bundles, nodal ramifications, and the bases of flower buds; shoot vascular bundles showed patterns of acropetally decreasing staining and the apical parts of buds and leaves were free from ARR5::GUS expression. In wind-exposed plants ARR5::GUS expression was considerably increased in shoots, also in basal-to-apical decreasing gradients. Immunolabelled shoots showed differential staining, with the strongest label in the vascular bundles of stems, leaves, and buds. The fact of the apparent absence of free CK in the buds of wind-protected plants and the typical upward decreasing gradients of free and conjugated CKs suggest that the bulk of the CK is synthesized in the root cap, exported through the xylem and accumulates at sites of highest transpiration where cuticles do not yet exist or do not protect against water loss.     

The scaffolding A/Tpd3 subunit and high phosphatase activity are dispensable for Cdc55 function in the Saccharomyces cerevisiae spindle checkpoint and in cytokinesis

Protein serine/threonine phosphatase 2A (PP2A) is a multifunctional enzyme whose trimeric form consists of a scaffolding A subunit, a catalytic C subunit, and one of several regulatory B subunits (B, B', and B'). The adenovirus E4orf4 protein associates with PP2A by directly binding the B or B' subunits. An interaction with an active PP2A containing the B subunit, or its homologue in yeast, Cdc55, is required for E4orf4-induced apoptosis in mammalian cells and for induction of growth arrest in Saccharomyces cerevisiae. In this work, Cdc55 was randomly mutagenized by low-fidelity PCR amplification, and Cdc55 mutants that lost the ability to transduce the E4orf4 toxic signal in yeast were selected. The mutations obtained by this protocol inhibited the association of Cdc55 with E4orf4, or with the PP2A-AC subunits, or both. Functional analysis revealed that a mutant that does not bind Tpd3, the yeast A subunit, as well as wild type Cdc55 in a tpd3Delta background, can form a heterodimer with the catalytic subunit. This association requires C subunit carboxyl methylation. The residual phosphatase activity associated with Cdc55 in the absence of Tpd3 is sufficient to maintain a partially active spindle checkpoint and to prevent cytokinesis defects.