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

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

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

Emergent Orthotopic Liver Transplantation for Hemorrhage from a Giant Cavernous Hepatic Hemangioma: Case Report and Review

IntroductionCavernous hemangiomas represent the most common benign primary hepatic neoplasm, often being incidentally detected. Although the majority of hepatic hemangiomas remain asymptomatic, symptomatic hepatic hemangiomas can present with abdominal pain, hemorrhage, biliary compression, or a consumptive coagulopathy. The optimal surgical management of symptomatic hepatic hemangiomas remains controversial, with resection, enucleation, and both deceased donor and living donor liver transplantation having been reported.Case reportWe report the case of a patient found to have a unique syndrome of multiorgan cavernous hemangiomatosis involving the liver, lung, omentum, and spleen without cutaneous involvement. Sixteen years following her initial diagnosis, the patient suffered from intra-abdominal hemorrhage due to her giant cavernous hepatic hemangioma. Evidence of continued bleeding, in the setting of Kasabach-Merritt Syndrome and worsening abdominal compartment syndrome, prompted MELD exemption listing. The patient subsequently underwent emergent liver transplantation without complication.ConclusionAlthough cavernous hemangiomas represent the most common benign primary hepatic neoplasm, hepatic hemangioma rupture remains a rare presentation in these patients. Management at a center with expertise in liver transplantation is warranted for those patients presenting with worsening DIC or hemorrhage, given the potential for rapid clinical decompensation

Contribution of Pollinator-Mediated Crops to Nutrients in the Human Food Supply

The contribution of nutrients from animal pollinated world crops has not previously been evaluated as a biophysical measure for the value of pollination services. This study evaluates the nutritional composition of animal-pollinated world crops. We calculated pollinator dependent and independent proportions of different nutrients of world crops, employing FAO data for crop production, USDA data for nutritional composition, and pollinator dependency data according to Klein et al. (2007). Crop plants that depend fully or partially on animal pollinators contain more than 90% of vitamin C, the whole quantity of Lycopene and almost the full quantity of the antioxidants β-cryptoxanthin and β-tocopherol, the majority of the lipid, vitamin A and related carotenoids, calcium and fluoride, and a large portion of folic acid. Ongoing pollinator decline may thus exacerbate current difficulties of providing a nutritionally adequate diet for the global human population

The IRYSS-COPD appropriateness study: objectives, methodology, and description of the prospective cohort

<p>Abstract</p> <p>Background</p> <p>Patients with chronic obstructive pulmonary disease (COPD) often experience exacerbations of the disease that require hospitalization. Current guidelines offer little guidance for identifying patients whose clinical situation is appropriate for admission to the hospital, and properly developed and validated severity scores for COPD exacerbations are lacking. To address these important gaps in clinical care, we created the IRYSS-COPD Appropriateness Study.</p> <p>Methods/Design</p> <p>The RAND/UCLA Appropriateness Methodology was used to identify appropriate and inappropriate scenarios for hospital admission for patients experiencing COPD exacerbations. These scenarios were then applied to a prospective cohort of patients attending the emergency departments (ED) of 16 participating hospitals. Information was recorded during the time the patient was evaluated in the ED, at the time a decision was made to admit the patient to the hospital or discharge home, and during follow-up after admission or discharge home. While complete data were generally available at the time of ED admission, data were often missing at the time of decision making. Predefined assumptions were used to impute much of the missing data.</p> <p>Discussion</p> <p>The IRYSS-COPD Appropriateness Study will validate the appropriateness criteria developed by the RAND/UCLA Appropriateness Methodology and thus better delineate the requirements for admission or discharge of patients experiencing exacerbations of COPD. The study will also provide a better understanding of the determinants of outcomes of COPD exacerbations, and evaluate the equity and variability in access and outcomes in these patients.</p

Fast MCMC sampling for hidden markov models to determine copy number variations

<p>Abstract</p> <p>Background</p> <p>Hidden Markov Models (HMM) are often used for analyzing Comparative Genomic Hybridization (CGH) data to identify chromosomal aberrations or copy number variations by segmenting observation sequences. For efficiency reasons the parameters of a HMM are often estimated with maximum likelihood and a segmentation is obtained with the Viterbi algorithm. This introduces considerable uncertainty in the segmentation, which can be avoided with Bayesian approaches integrating out parameters using Markov Chain Monte Carlo (MCMC) sampling. While the advantages of Bayesian approaches have been clearly demonstrated, the likelihood based approaches are still preferred in practice for their lower running times; datasets coming from high-density arrays and next generation sequencing amplify these problems.</p> <p>Results</p> <p>We propose an approximate sampling technique, inspired by compression of discrete sequences in HMM computations and by <it>kd</it>-trees to leverage spatial relations between data points in typical data sets, to speed up the MCMC sampling.</p> <p>Conclusions</p> <p>We test our approximate sampling method on simulated and biological ArrayCGH datasets and high-density SNP arrays, and demonstrate a speed-up of 10 to 60 respectively 90 while achieving competitive results with the state-of-the art Bayesian approaches.</p> <p><it>Availability: </it>An implementation of our method will be made available as part of the open source GHMM library from <url>http://ghmm.org</url>.</p