Cardiovascular Interactions Tutorial:An Update

The Cardiovascular Interaction (CVI) simulation model was developed by Carl Rothe (1929-2016) as an interactive computer simulation in the form of a tutorial. The original tutorial was based on a five-compartment model (Venous Bed, Right Heart, Lung Bed, Left Heart, and Arterial Bed). This work examines the simulation Dr. Rothe developed based on a six-compartment model (Systemic Veins, Right Ventricle, Pulmonary Arteries, Pulmonary Veins, Left Ventricle, and Systemic Arteries). Both models were originally developed in Visual Basic. Both models have been reimplemented in C# WPF for Windows and in LabVIEW for Windows 10 and Mac OS X

Influence of the quasi-biennial oscillation on the extratropical winter stratosphere in an atmospheric general circulation model and in reanalysis data

The interannual variability of the stratospheric polar vortex during winter in both hemispheres is observed to correlate strongly with the phase of the quasi-biennial oscillation (QBO) in tropical stratospheric winds. It follows that the lack of a spontaneously generated QBO in most atmospheric general circulation models (AGCMs) adversely affects the nature of polar variability in such models. This study examines QBO–vortex coupling in an AGCM in which a QBO is spontaneously induced by resolved and parameterized waves. The QBO–vortex coupling in the AGCM compares favorably to that seen in reanalysis data [from the 40-yr ECMWF Re-Analysis (ERA-40)], provided that careful attention is given to the definition of QBO phase. A phase angle representation of the QBO is employed that is based on the two leading empirical orthogonal functions of equatorial zonal wind vertical profiles. This yields a QBO phase that serves as a proxy for the vertical structure of equatorial winds over the whole depth of the stratosphere and thus provides a means of subsampling the data to select QBO phases with similar vertical profiles of equatorial zonal wind. Using this subsampling, it is found that the QBO phase that induces the strongest polar vortex response in early winter differs from that which induces the strongest late-winter vortex response. This is true in both hemispheres and for both the AGCM and ERA-40. It follows that the strength and timing of QBO influence on the vortex may be affected by the partial seasonal synchronization of QBO phase transitions that occurs both in observations and in the model. This provides a mechanism by which changes in the strength of QBO–vortex correlations may exhibit variability on decadal time scales. In the model, such behavior occurs in the absence of external forcings or interannual variations in sea surface temperatures

Deciding Fast:Examining the Relationship between Strategic Decision Speed and Decision Quality across Multiple Environmental Contexts

Rapid innovation, shortened product life cycles and fierce competition place great pressures on top managers to make fast strategic decisions. However, a key question in strategic decision-making research is whether decision speed helps or harms decision quality, and there is a shortage of theory and evidence concerning the consequences of decision speed across different environmental contexts. We develop new theory by considering the effects of decision speed on decision quality under conditions of environmental munificence, under conditions of dynamism, and under the joint conditions of munificence and dynamism. We test our theory through analysis of multi-informant survey data drawn from top management teams and secondary databases, in 117 UK firms. Our findings demonstrate that munificence is the central generative mechanism which moderates the relationship between decision speed and decision quality, and markedly alters the previously theorized positive effects of decision speed in dynamic contexts

Genomic selection and complex trait prediction using a fast EM algorithm applied to genome-wide markers

Background: The information provided by dense genome-wide markers using high throughput technology is of considerable potential in human disease studies and livestock breeding programs. Genome-wide association studies relate individual single nucleotide polymorphisms (SNP) from dense SNP panels to individual measurements of complex traits, with the underlying assumption being that any association is caused by linkage disequilibrium (LD) between SNP and quantitative trait loci (QTL) affecting the trait. Often SNP are in genomic regions of no trait variation. Whole genome Bayesian models are an effective way of incorporating important prior information into modelling. However a full Bayesian analysis is often not feasible due to the amount of data and the computational time involved. Results: This article proposes an expectation-maximization (EM) algorithm called emBayesB which allows only a proportion of SNP to be in LD with QTL and incorporates important prior information about the distribution of SNP effects. The posterior probability of being in LD with at least one QTL is calculated for each SNP along with estimates of the hyperparameters for the mixture prior. A simulated example of genomic selection from an international workshop is used to demonstrate the features of the EM algorithm. The accuracy of prediction is comparable to a full Bayesian analysis but the EM algorithm is considerably faster. The EM algorithm was accurate in locating QTL which explained more than 1% of the total genetic variation. A computational algorithm for very large SNP panels is described. Conclusions: emBayesB is a fast and accurate EM algorithm for implementing genomic selection and predicting complex traits by mapping QTL in genome-wide dense SNP marker data. Its accuracy is similar to Bayesian methods but it takes only a fraction of the time

Diversification of Camphorosmeae (Amaranthaceae s.l.) during the Miocene-Pliocene aridification of inland Australia

The Australian Camphorosmeae represent a monophyletic lineage that diversified to include ca. 150 spp. across 12 genera, and populate large parts of arid Australia. Tracking the origin and spread of this ancestrally salt and drought tolerant lineage provides additional evidence about the timing of the evolutionary history and phylogenetic assembly of arid habitats in Australia. Using a customized RADseq approach, sequence data for 104 species of the Australian Camphorosmeae representing all 12 genera were generated and included in phylogenetic and dating analyses. Furthermore, habitat type occurrences and preferences of species and clades were recorded. As suspected, the characters used to delimit current Australian Camphorosmeae genera do not support monophyletic groups, as phylogenetic analyses yielded 17 statistically supported clades across a large Maireana grade and crown radiation of Sclerolaena. The diversification of Australian Camphorosmeae is clearly linked to landscape changes and emerging new habitat types in arid Australia since the ancestral element likely arrived from temperate semi-arid to arid parts of continental Eurasia in the Middle Miocene. Migration was likely multidirectional and followed a west-to-east aridification. Crown group diversification was strongest during the Pliocene and likely promoted by the west-to-east expansion of Riverine Desert habitats and subsequent expansion and colonization of newly developing arid habitats. Rapid range expansion, fast habitat saturation, as well as periodic expansion, contraction and replacement of arid habitats, may have caused the rather species-poor clades of the earlier-divergent Maireana grade, compared to the continuously diversifying Sclerolaena clade

Sensitivity of simulated climate to conservation of momentum in gravity wave drag parameterization

The Canadian Middle Atmosphere Model is used to examine the sensitivity of simulated climate to conservation of momentum in gravity wave drag parameterization. Momentum conservation requires that the parameterized gravity wave momentum flux at the top of the model be zero and corresponds to the physical boundary condition of no momentum flux at the top of the atmosphere. Allowing momentum flux to escape the model domain violates momentum conservation. Here the impact of momentum conservation in two sets of model simulations is investigated. In the first set, the simulation of present-day climate for two model-lid height configurations, 0.001 and 10 hPa, which are identical below 10 hPa, is considered. The impact of momentum conservation on the climate with the model lid at 0.001 hPa is minimal, which is expected because of the small amount of gravity wave momentum flux reaching 0.001 hPa. When the lid is lowered to 10 hPa and momentum is conserved, there is only a modest impact on the climate in the Northern Hemisphere; however, the Southern Hemisphere climate is more adversely affected by the deflection of resolved waves near the model lid. When momentum is not conserved in the 10-hPa model the climate is further degraded in both hemispheres, particularly in winter at high latitudes, and the impact of momentum conservation extends all the way to the surface. In the second set of simulations, the impact of momentum conservation and model-lid height on the modeled response to ozone depletion in the Southern Hemisphere is considered, and it is found that the response can display significant sensitivity to both factors. In particular, both the lower-stratospheric polar temperature and surface responses are significantly altered when the lid is lowered, with the effect being most severe when momentum is not conserved. The implications with regard to the current round of Intergovernmental Panel on Climate Change model projections are discussed

Exploiting the noise: improving biomarkers with ensembles of data analysis methodologies.

BackgroundThe advent of personalized medicine requires robust, reproducible biomarkers that indicate which treatment will maximize therapeutic benefit while minimizing side effects and costs. Numerous molecular signatures have been developed over the past decade to fill this need, but their validation and up-take into clinical settings has been poor. Here, we investigate the technical reasons underlying reported failures in biomarker validation for non-small cell lung cancer (NSCLC).MethodsWe evaluated two published prognostic multi-gene biomarkers for NSCLC in an independent 442-patient dataset. We then systematically assessed how technical factors influenced validation success.ResultsBoth biomarkers validated successfully (biomarker #1: hazard ratio (HR) 1.63, 95% confidence interval (CI) 1.21 to 2.19, P = 0.001; biomarker #2: HR 1.42, 95% CI 1.03 to 1.96, P = 0.030). Further, despite being underpowered for stage-specific analyses, both biomarkers successfully stratified stage II patients and biomarker #1 also stratified stage IB patients. We then systematically evaluated reasons for reported validation failures and find they can be directly attributed to technical challenges in data analysis. By examining 24 separate pre-processing techniques we show that minor alterations in pre-processing can change a successful prognostic biomarker (HR 1.85, 95% CI 1.37 to 2.50, P < 0.001) into one indistinguishable from random chance (HR 1.15, 95% CI 0.86 to 1.54, P = 0.348). Finally, we develop a new method, based on ensembles of analysis methodologies, to exploit this technical variability to improve biomarker robustness and to provide an independent confidence metric.ConclusionsBiomarkers comprise a fundamental component of personalized medicine. We first validated two NSCLC prognostic biomarkers in an independent patient cohort. Power analyses demonstrate that even this large, 442-patient cohort is under-powered for stage-specific analyses. We then use these results to discover an unexpected sensitivity of validation to subtle data analysis decisions. Finally, we develop a novel algorithmic approach to exploit this sensitivity to improve biomarker robustness

Functional brain networks involved in gaze and emotional processing

Eye-gaze direction plays a fundamental role in the perception of facial features and particularly the processing of emotional facial expressions. Yet, the neural underpinnings of the integration of eye gaze and emotional facial cues are not well understood. The primary aim of this study was to delineate the functional networks that subserve the recognition of emotional expressions as a function of eye gaze. Participants were asked to identify happy, angry, or neutral faces, displayed with direct or averted gaze, while their neural responses were measured with fMRI. The results showed that recognition of happy expressions, irrespective of eye-gaze direction, engaged the critical nodes of the default mode network. Recognition of angry faces, on the other hand, was gaze-dependent, engaging the critical nodes of the salience network when presented with direct gaze, but fronto-parietal areas when presented with averted gaze. Functional connectivity analysis further showed gaze-dependent engagement of a large-scale network connected to bilateral amygdala during the recognition of angry expressions. This study provides important insights into the functional connectivity between the amygdala and other critical social-cognitive brain nodes, which are essential in processing of ambiguous, potentially threatening social signals. These findings have implications for psychiatric disorders, such as post-traumatic stress disorder, which are characterized by aberrant limbic connectivity

Pubertal timing and breast density in young women: a prospective cohort study.

BACKGROUND:Earlier age at onset of pubertal events and longer intervals between them (tempo) have been associated with increased breast cancer risk. It is unknown whether the timing and tempo of puberty are associated with adult breast density, which could mediate the increased risk. METHODS:From 1988 to 1997, girls participating in the Dietary Intervention Study in Children (DISC) were clinically assessed annually between ages 8 and 17 years for Tanner stages of breast development (thelarche) and pubic hair (pubarche), and onset of menses (menarche) was self-reported. In 2006-2008, 182 participants then aged 25-29 years had their percent dense breast volume (%DBV) measured by magnetic resonance imaging. Multivariable, linear mixed-effects regression models adjusted for reproductive factors, demographics, and body size were used to evaluate associations of age and tempo of puberty events with %DBV. RESULTS:The mean (standard deviation) and range of %DBV were 27.6 (20.5) and 0.2-86.1. Age at thelarche was negatively associated with %DBV (p trend = 0.04), while pubertal tempo between thelarche and menarche was positively associated with %DBV (p trend = 0.007). %DBV was 40% higher in women whose thelarche-to-menarche tempo was 2.9 years or longer (geometric mean (95%CI) = 21.8% (18.2-26.2%)) compared to women whose thelarche-to-menarche tempo was less than 1.6 years (geometric mean (95%CI) = 15.6% (13.9-17.5%)). CONCLUSIONS:Our results suggest that a slower pubertal tempo, i.e., greater number of months between thelarche and menarche, is associated with higher percent breast density in young women. Future research should examine whether breast density mediates the association between slower tempo and increased breast cancer risk