Dynamical density delay maps: simple, new method for visualising the behaviour of complex systems

Background. Physiologic signals, such as cardiac interbeat intervals, exhibit complex fluctuations. However, capturing important dynamical properties, including nonstationarities may not be feasible from conventional time series graphical representations. Methods. We introduce a simple-to-implement visualisation method, termed dynamical density delay mapping (``D3-Map'' technique) that provides an animated representation of a system's dynamics. The method is based on a generalization of conventional two-dimensional (2D) Poincar� plots, which are scatter plots where each data point, x(n), in a time series is plotted against the adjacent one, x(n+1). First, we divide the original time series, x(n) (n=1,..., N), into a sequence of segments (windows). Next, for each segment, a three-dimensional (3D) Poincar� surface plot of x(n), x(n+1), hx(n),x(n+1) is generated, in which the third dimension, h, represents the relative frequency of occurrence of each (x(n),x(n+1)) point. This 3D Poincar\'e surface is then chromatised by mapping the relative frequency h values onto a colour scheme. We also generate a colourised 2D contour plot from each time series segment using the same colourmap scheme as for the 3D Poincar\'e surface. Finally, the original time series graph, the colourised 3D Poincar\'e surface plot, and its projection as a colourised 2D contour map for each segment, are animated to create the full ``D3-Map.'' Results. We first exemplify the D3-Map method using the cardiac interbeat interval time series from a healthy subject during sleeping hours. The animations uncover complex dynamical changes, such as transitions between states, and the relative amount of time the system spends in each state. We also illustrate the utility of the method in detecting hidden temporal patterns in the heart rate dynamics of a patient with atrial fibrillation. The videos, as well as the source code, are made publicly available. Conclusions. Animations based on density delay maps provide a new way of visualising dynamical properties of complex systems not apparent in time series graphs or standard Poincar\'e plot representations. Trainees in a variety of fields may find the animations useful as illustrations of fundamental but challenging concepts, such as nonstationarity and multistability. For investigators, the method may facilitate data exploration

An interactome-centered protein discovery approach reveals novel components involved in mitosome function and homeostasis in giardia lamblia

Protozoan parasites of the genus Giardia are highly prevalent globally, and infect a wide range of vertebrate hosts including humans, with proliferation and pathology restricted to the small intestine. This narrow ecological specialization entailed extensive structural and functional adaptations during host-parasite co-evolution. An example is the streamlined mitosomal proteome with iron-sulphur protein maturation as the only biochemical pathway clearly associated with this organelle. Here, we applied techniques in microscopy and protein biochemistry to investigate the mitosomal membrane proteome in association to mitosome homeostasis. Live cell imaging revealed a highly immobilized array of 30–40 physically distinct mitosome organelles in trophozoites. We provide direct evidence for the single giardial dynamin-related protein as a contributor to mitosomal morphogenesis and homeostasis. To overcome inherent limitations that have hitherto severely hampered the characterization of these unique organelles we applied a novel interaction-based proteome discovery strategy using forward and reverse protein co-immunoprecipitation. This allowed generation of organelle proteome data strictly in a protein-protein interaction context. We built an initial Tom40-centered outer membrane interactome by co-immunoprecipitation experiments, identifying small GTPases, factors with dual mitosome and endoplasmic reticulum (ER) distribution, as well as novel matrix proteins. Through iterative expansion of this protein-protein interaction network, we were able to i) significantly extend this interaction-based mitosomal proteome to include other membrane-associated proteins with possible roles in mitosome morphogenesis and connection to other subcellular compartments, and ii) identify novel matrix proteins which may shed light on mitosome-associated metabolic functions other than Fe-S cluster biogenesis. Functional analysis also revealed conceptual conservation of protein translocation despite the massive divergence and reduction of protein import machinery in Giardia mitosomes

Agricultural policies exacerbate honeybee pollination service supply-demand mismatches across Europe

Declines in insect pollinators across Europe have raised concerns about the supply of pollination services to agriculture. Simultaneously, EU agricultural and biofuel policies have encouraged substantial growth in the cultivated area of insect pollinated crops across the continent. Using data from 41 European countries, this study demonstrates that the recommended number of honeybees required to provide crop pollination across Europe has risen 4.9 times as fast as honeybee stocks between 2005 and 2010. Consequently, honeybee stocks were insufficient to supply >90% of demands in 22 countries studied. These findings raise concerns about the capacity of many countries to cope with major losses of wild pollinators and highlight numerous critical gaps in current understanding of pollination service supplies and demands, pointing to a pressing need for further research into this issue

Mechanisms and models of somatic cell reprogramming

Whitehead Institute for Biomedical Research (Jerome and Florence Brill Graduate Student Fellowship)National Institutes of Health (U.S.) (US NIH grant RO1-CA087869)National Institutes of Health (U.S.) (US NIH grant R37-CA084198)National Science Foundation (U.S.) (NSF Graduate Research Fellowship)National Institutes of Health (U.S.) ((NIH) Kirschstein National Research Service Award,1 F32 GM099153-01A1)Vertex Pharmaceuticals Incorporated (Vertex Scholar

Increased vascular contractility in hypertension results from impaired endothelial calcium signaling

Endothelial cells line all blood vessels and are critical regulators of vascular tone. In hypertension, disruption of endothelial function alters the release of endothelial-derived vasoactive factors and results in increased vascular tone. Although the release of endothelial-derived vasodilators occurs in a Ca2+-dependent manner, little is known on how Ca2+ signaling is altered in hypertension. A key element to endothelial control of vascular tone is Ca2+ signals at specialized regions (myoendothelial projections) that connect endothelial cells and smooth muscle cells. This work describes disruption in the operation of this key Ca2+ signaling pathway in hypertension. We show that vascular reactivity to phenylephrine is increased in hypertensive (spontaneously hypertensive rat) when compared with normotensive (Wistar Kyoto) rats. Basal endothelial Ca2+ activity limits vascular contraction, but that Ca2+-dependent control is impaired in hypertension. When changes in endothelial Ca2+ levels are buffered, vascular contraction to phenylephrine increased, resulting in similar responses in normotension and hypertension. Local endothelial IP3(inositol trisphosphate)-mediated Ca2+ signals are smaller in amplitude, shorter in duration, occur less frequently, and arise from fewer sites in hypertension. Spatial control of endothelial Ca2+ signaling is also disrupted in hypertension: local Ca2+ signals occur further from myoendothelial projections in hypertension. The results demonstrate that the organization of local Ca2+ signaling circuits occurring at myoendothelial projections is disrupted in hypertension, giving rise to increased contractile responses

Alternative regression models to assess increase in childhood BMI

<p>Abstract</p> <p>Background</p> <p>Body mass index (BMI) data usually have skewed distributions, for which common statistical modeling approaches such as simple linear or logistic regression have limitations.</p> <p>Methods</p> <p>Different regression approaches to predict childhood BMI by goodness-of-fit measures and means of interpretation were compared including generalized linear models (GLMs), quantile regression and Generalized Additive Models for Location, Scale and Shape (GAMLSS). We analyzed data of 4967 children participating in the school entry health examination in Bavaria, Germany, from 2001 to 2002. TV watching, meal frequency, breastfeeding, smoking in pregnancy, maternal obesity, parental social class and weight gain in the first 2 years of life were considered as risk factors for obesity.</p> <p>Results</p> <p>GAMLSS showed a much better fit regarding the estimation of risk factors effects on transformed and untransformed BMI data than common GLMs with respect to the generalized Akaike information criterion. In comparison with GAMLSS, quantile regression allowed for additional interpretation of prespecified distribution quantiles, such as quantiles referring to overweight or obesity. The variables TV watching, maternal BMI and weight gain in the first 2 years were directly, and meal frequency was inversely significantly associated with body composition in any model type examined. In contrast, smoking in pregnancy was not directly, and breastfeeding and parental social class were not inversely significantly associated with body composition in GLM models, but in GAMLSS and partly in quantile regression models. Risk factor specific BMI percentile curves could be estimated from GAMLSS and quantile regression models.</p> <p>Conclusion</p> <p>GAMLSS and quantile regression seem to be more appropriate than common GLMs for risk factor modeling of BMI data.</p

The dual GGDEF/EAL domain enzyme PA0285 is a Pseudomonas species housekeeping phosphodiesterase regulating early attachment and biofilm architecture.

Bacterial lifestyles depend on conditions encountered during colonization. The transition between planktonic and biofilm growth is dependent on the intracellular second messenger c-di-GMP. High c-di-GMP levels driven by diguanylate cyclases (DGCs) activity favor biofilm formation, while low levels were maintained by phosphodiesterases (PDE) encourage planktonic lifestyle. The activity of these enzymes can be modulated by stimuli-sensing domains such as Per-ARNT-Sim (PAS). In Pseudomonas aeruginosa, more than 40 PDE/DGC are involved in c-di-GMP homeostasis, including 16 dual proteins possessing both canonical DGC and PDE motifs, that is, GGDEF and EAL, respectively. It was reported that deletion of the EAL/GGDEF dual enzyme PA0285, one of five c-di-GMP-related enzymes conserved across all Pseudomonas species, impacts biofilms. PA0285 is anchored in the membrane and carries two PAS domains. Here, we confirm that its role is conserved in various P. aeruginosa strains and in Pseudomonas putida. Deletion of PA0285 impacts the early stage of colonization, and RNA-seq analysis suggests that expression of cupA fimbrial genes is involved. We demonstrate that the C-terminal portion of PA0285 encompassing the GGDEF and EAL domains binds GTP and c-di-GMP, respectively, but only exhibits PDE activity in vitro. However, both GGDEF and EAL domains are important for PA0285 PDE activity in vivo. Complementation of the PA0285 mutant strain with a copy of the gene encoding the C-terminal GGDEF/EAL portion in trans was not as effective as complementation with the full-length gene. This suggests the N-terminal transmembrane and PAS domains influence the PDE activity in vivo, through modulating the protein conformation

Haplotype Estimation from Fuzzy Genotypes Using Penalized Likelihood

The Composite Link Model is a generalization of the generalized linear model in which expected values of observed counts are constructed as a sum of generalized linear components. When combined with penalized likelihood, it provides a powerful and elegant way to estimate haplotype probabilities from observed genotypes. Uncertain (“fuzzy”) genotypes, like those resulting from AFLP scores, can be handled by adding an extra layer to the model. We describe the model and the estimation algorithm. We apply it to a data set of accurate human single nucleotide polymorphism (SNP) and to a data set of fuzzy tomato AFLP scores

An iterative block-shifting approach to retention time alignment that preserves the shape and area of gas chromatography-mass spectrometry peaks

<p>Abstract</p> <p>Background</p> <p>Metabolomics, petroleum and biodiesel chemistry, biomarker discovery, and other fields which rely on high-resolution profiling of complex chemical mixtures generate datasets which contain millions of detector intensity readings, each uniquely addressed along dimensions of <it>time </it>(<it>e.g.</it>, <it>retention time </it>of chemicals on a chromatographic column), a <it>spectral value </it>(<it>e.g., mass-to-charge ratio </it>of ions derived from chemicals), and the <it>analytical run number</it>. They also must rely on data preprocessing techniques. In particular, inter-run variance in the retention time of chemical species poses a significant hurdle that must be cleared before feature extraction, data reduction, and knowledge discovery can ensue. <it>Alignment methods</it>, for calibrating retention reportedly (and in our experience) can misalign matching chemicals, falsely align distinct ones, be unduly sensitive to chosen values of input parameters, and result in distortions of peak shape and area.</p> <p>Results</p> <p>We present an iterative block-shifting approach for retention-time calibration that detects chromatographic features and qualifies them by retention time, spectrum, and the effect of their inclusion on the quality of alignment itself. Mass chromatograms are aligned pairwise to one selected as a reference. In tests using a 45-run GC-MS experiment, block-shifting reduced the absolute deviation of retention by greater than 30-fold. It compared favourably to COW and XCMS with respect to alignment, and was markedly superior in preservation of peak area.</p> <p>Conclusion</p> <p>Iterative block-shifting is an attractive method to align GC-MS mass chromatograms that is also generalizable to other two-dimensional techniques such as HPLC-MS.</p

Organic Farming Improves Pollination Success in Strawberries

Pollination of insect pollinated crops has been found to be correlated to pollinator abundance and diversity. Since organic farming has the potential to mitigate negative effects of agricultural intensification on biodiversity, it may also benefit crop pollination, but direct evidence of this is scant. We evaluated the effect of organic farming on pollination of strawberry plants focusing on (1) if pollination success was higher on organic farms compared to conventional farms, and (2) if there was a time lag from conversion to organic farming until an effect was manifested. We found that pollination success and the proportion of fully pollinated berries were higher on organic compared to conventional farms and this difference was already evident 2–4 years after conversion to organic farming. Our results suggest that conversion to organic farming may rapidly increase pollination success and hence benefit the ecosystem service of crop pollination regarding both yield quantity and quality