High-resolution analysis of individual Drosophila melanogaster larvae uncovers individual variability in locomotion and its neurogenetic modulation.

Neuronally orchestrated muscular movement and locomotion are defining faculties of multicellular animals. Due to its simple brain and genetic accessibility, the larva of the fruit fly Drosophila melanogaster allows one to study these processes at tractable levels of complexity. However, although the faculty of locomotion clearly pertains to the individual, most studies of locomotion in larvae use measurements aggregated across animals, or animals tested one by one, an extravagance for larger-scale analyses. This prevents grasping the inter- and intra-individual variability in locomotion and its neurogenetic determinants. Here, we present the IMBA (individual maggot behaviour analyser) for analysing the behaviour of individual larvae within groups, reliably resolving individual identity across collisions. We use the IMBA to systematically describe the inter- and intra-individual variability in locomotion of wild-type animals, and how the variability is reduced by associative learning. We then report a novel locomotion phenotype of an adhesion GPCR mutant. We further investigated the modulation of locomotion across repeated activations of dopamine neurons in individual animals, and the transient backward locomotion induced by brief optogenetic activation of the brain-descending 'mooncrawler' neurons. In summary, the IMBA is an easy-to-use toolbox allowing an unprecedentedly rich view of the behaviour and its variability of individual larvae, with utility in multiple biomedical research contexts.

Insight Beyond Numbers: The Impact of Qualitative Factors on Visual Data Analysis.

As of today, data analysis focuses primarily on the findings to be made inside the data and concentrates less on how those findings relate to the domain of investigation. Contemporary visualization as a field of research shows a strong tendency to adopt this data-centrism. Despite their decisive influence on the analysis result, qualitative aspects of the analysis process such as the structure, soundness, and complexity of the applied reasoning strategy are rarely discussed explicitly. We argue that if the purpose of visualization is the provision of domain insight rather than the depiction of data analysis results, a holistic perspective requires a qualitative component to to be added to the discussion of quantitative and human factors. To support this point, we demonstrate how considerations of qualitative factors in visual analysis can be applied to obtain explanations and possible solutions for a number of practical limitations inherent to the data-centric perspective on analysis. Based on this discussion of what we call qualitative visual analysis, we develop an inside-outside principle of nested levels of context that can serve as a conceptual basis for the development of visualization systems that optimally support the emergence of insight during analysis.

Understanding a Sequence of Sequences: Visual Exploration of Categorical States in Lake Sediment Cores.

This design study focuses on the analysis of a time sequence of categorical sequences. Such data is relevant for the geoscientific research field of landscape and climate development. It results from microscopic analysis of lake sediment cores. The goal is to gain hypotheses about landscape evolution and climate conditions in the past. To this end, geoscientists identify which categorical sequences are similar in the sense that they indicate similar conditions. Categorical sequences are similar if they have similar meaning (semantic similarity) and appear in similar time periods (temporal similarity). For data sets with many different categorical sequences, the task to identify similar sequences becomes a challenge. Our contribution is a tailored visual analysis concept that effectively supports the analytical process. Our visual interface comprises coupled visualizations of semantics and temporal context for the exploration and assessment of the similarity of categorical sequences. Integrated automatic methods reduce the analytical effort substantially. They (1) extract unique sequences in the data and (2) rank sequences by a similarity measure during the search for similar sequences. We evaluated our concept by demonstrations of our prototype to a larger audience and hands-on analysis sessions for two different lakes. According to geoscientists, our approach fills an important methodological gap in the application domain.

The LloydRelaxer: An Approach to Minimize Scaling Effects for Multivariate Projections.

Star Coordinates are a popular projection technique in order to analyze and to disclose characteristic patterns of multidimensional data. Unfortunately, the shape, appearance, and distribution of such patterns are strongly affected by the given scaling of the data and can mislead the projection-based data analysis. In an extreme case, patterns might be more related to the choice of scaling than to the data themselves. Thus, we present the LloydRelaxer : a tool to minimize scaling-based effects in Star Coordinates. Our algorithm enforces a scaling configuration for which the data explains the observed patterns better than any scaling of them could do. It does so by an iterative minimizing and optimization process based on Voronoi diagrams and on the Lloyd relaxation within the projection space. We evaluate and test our approach by real benchmark multidimensional data of the UCI data repository.

Optimal Sets of Projections of High-Dimensional Data.

Finding good projections of n-dimensional datasets into a 2D visualization domain is one of the most important problems in Information Visualization. Users are interested in getting maximal insight into the data by exploring a minimal number of projections. However, if the number is too small or improper projections are used, then important data patterns might be overlooked. We propose a data-driven approach to find minimal sets of projections that uniquely show certain data patterns. For this we introduce a dissimilarity measure of data projections that discards affine transformations of projections and prevents repetitions of the same data patterns. Based on this, we provide complete data tours of at most n/2 projections. Furthermore, we propose optimal paths of projection matrices for an interactive data exploration. We illustrate our technique with a set of state-of-the-art real high-dimensional benchmark datasets.

Blood Flow Clustering and Applications in Virtual Stenting of Intracranial Aneurysms.

Understanding the hemodynamics of blood flow in vascular pathologies such as intracranial aneurysms is essential for both their diagnosis and treatment. Computational fluid dynamics (CFD) simulations of blood flow based on patient-individual data are performed to better understand aneurysm initiation and progression and more recently, for predicting treatment success. In virtual stenting, a flow-diverting mesh tube (stent) is modeled inside the reconstructed vasculature and integrated in the simulation. We focus on steady-state simulation and the resulting complex multiparameter data. The blood flow pattern captured therein is assumed to be related to the success of stenting. It is often visualized by a dense and cluttered set of streamlines.We present a fully automatic approach for reducing visual clutter and exposing characteristic flow structures by clustering streamlines and computing cluster representatives. While individual clustering techniques have been applied before to streamlines in 3D flow fields, we contribute a general quantitative and a domain-specific qualitative evaluation of three state-of-the-art techniques. We show that clustering based on streamline geometry as well as on domain-specific streamline attributes contributes to comparing and evaluating different virtual stenting strategies. With our work, we aim at supporting CFD engineers and interventional neuroradiologists.

Orthographic star coordinates.

Star coordinates is a popular projection technique from an nD data space to a 2D/3D visualization domain. It is defined by setting n coordinate axes in the visualization domain. Since it generally defines an affine projection, strong distortions can occur: an nD sphere can be mapped to an ellipse of arbitrary size and aspect ratio. We propose to restrict star coordinates to orthographic projections which map an nD sphere of radius r to a 2D circle of radius r. We achieve this by formulating conditions for the coordinate axes to define orthographic projections, and by running a repeated non-linear optimization in the background of every modification of the coordinate axes. This way, we define a number of orthographic interaction concepts as well as orthographic data tour sequences: a scatterplot tour, a principle component tour, and a grand tour. All concepts are illustrated and evaluated with synthetic and real data.

Results in the long-term course after stapled transanal rectal resection (STARR).

PURPOSE: Stapled transanal rectal resection (STARR) has recently been recommended for patients with obstructed defecation caused by rectocele and rectal wall intussusception. Our study investigates the long-term results and predictive factors for outcome. METHODS: Between November 2002 and February 2007, 80 patients (69 females) were operated on using the STARR procedure and included in the following study. Symptoms were defined according to the ROME II criteria. Preoperative assessment included clinical examination, colonoscopy, video defecography, and dynamic MRI. Preoperatively and during follow-up visits, we evaluated the Cleveland Constipation Score (CCS) to rate the severity of outlet obstruction and the Wexner Incontinence Score to rate anal incontinence. Patients were asked to judge the outcome of the operation as improved or poor/dissatisfied. We performed a univariate analysis for 11 patient- and disease-related factors to detect an association with outcome. RESULTS: The median follow-up was 39 months (range 20-78). Major postoperative complications (one staple line insufficiency, one urosepsis, one prolonged urinary dysfunction with indwelling catheter) were found in 3.8%. The result after STARR procedure was a success in the long-term follow-up in 62 patients (77.5%), although the improvement did not persist in 15 patients (18.7%). The mean value of the CCS decreased significantly from 9.3 before surgery to 4.6 after 2 years and increased again slightly to 6.5 after 4-6 years. The Median Wexner Incontinence Score was 3.3 at baseline, but rose significantly to 6.0. However, a third of patients who reported deteriorated continence developed the symptoms 1-4 years after surgery. Of the factors investigated for the prediction of outcome, we could only identify the number of pelvic floor changes in defecography or dynamic MRI as being associated with the success of the operation. CONCLUSION: Our study indicates that STARR is a safe procedure. A significant improvement of symptoms is to be expected, but this improvement may deteriorate with time. Patients' satisfaction is also associated with the occurrence of urge to defecate or incontinence. It remains difficult to predict outcome.

Features in Continuous Parallel Coordinates.

Continuous Parallel Coordinates (CPC) are a contemporary visualization technique in order to combine several scalar fields, given over a common domain. They facilitate a continuous view for parallel coordinates by considering a smooth scalar field instead of a finite number of straight lines. We show that there are feature curves in CPC which appear to be the dominant structures of a CPC. We present methods to extract and classify them and demonstrate their usefulness to enhance the visualization of CPCs. In particular, we show that these feature curves are related to discontinuities in Continuous Scatterplots (CSP). We show this by exploiting a curve-curve duality between parallel and Cartesian coordinates, which is a generalization of the well-known point-line duality. Furthermore, we illustrate the theoretical considerations. Concluding, we discuss relations and aspects of the CPC's/CSP's features concerning the data analysis.

Discontinuities in continuous scatter plots.

The concept of continuous scatterplot (CSP) is a modern visualization technique. The idea is to define a scalar density value based on the map between an n-dimensional spatial domain and an m-dimensional data domain, which describe the CSP space. Usually the data domain is two-dimensional to visually convey the underlying, density coded, data. In this paper we investigate kinds of map-based discontinuities, especially for the practical cases n = m = 2 and n = 3 | m = 2, and we depict relations between them and attributes of the resulting CSP itself. Additionally, we show that discontinuities build critical line structures, and we introduce algorithms to detect them. Further, we introduce a discontinuity-based visualization approach—called contribution map (CM)—which establishes a relationship between the CSP's data domain and the number of connected components in the spatial domain. We show that CMs enhance the CSP-based linking & brushing interaction. Finally, we apply our approaches to a number of synthetic as well as real data sets.

Surgical trauma affects the proinflammatory status after cardiac surgery to a higher degree than cardiopulmonary bypass.

OBJECTIVES: Cytokines contribute to the development of the systemic inflammatory response syndrome or multiple-organ failure frequently observed after cardiopulmonary bypass-supported cardiac surgery. To quantify the contribution of bypass-induced versus trauma-induced inflammatory response after coronary artery bypass grafting, we examined plasma cytokine levels in 120 patients with coronary artery disease who were treated with or without cardiopulmonary bypass-assisted procedures. METHODS: Patients were treated in accordance with one of the following protocols: (1) elective percutaneous coronary intervention without cardiopulmonary bypass (n = 69), (2) cardiopulmonary bypass-supported percutaneous coronary intervention (cardiopulmonary bypass-percutaneous coronary intervention; n = 10), and (3) cardiopulmonary bypass-supported coronary artery bypass grafting (cardiopulmonary bypass-coronary artery bypass grafting; n = 41). Cytokine levels (picograms/milliliter) were measured by enzyme-linked immunosorbent assay from plasma samples obtained at various time points. RESULTS: Interleukin-6 was measured in blood samples from all 3 patient populations. The maximum interleukin-6 level was 13.6 +/- 22.3 pg/mL in the percutaneous coronary intervention group, 170.4 +/- 165.4 pg/mL in the cardiopulmonary bypass-percutaneous coronary intervention group, and 640.3 +/- 285.7 pg/mL in the cardiopulmonary bypass-coronary artery bypass grafting group. Interleukin-6 levels were significantly different, and the 95% confidence intervals did not overlap. In the cardiopulmonary bypass-percutaneous coronary intervention group, bypass duration correlated well with interleukin-6 production ( r = 0.915; P < .001), whereas these parameters did not correlate in patients who underwent cardiopulmonary bypass-coronary artery bypass grafting ( r = 0.307; P = .054). CONCLUSIONS: These findings support the suggestion that surgical trauma and cardiopulmonary bypass contribute to the inflammatory response after cardiac surgery, although trauma may contribute to a higher degree.