University of Konstanz

About: University of Konstanz is a education organization based out in Konstanz, Baden-Württemberg, Germany. It is known for research contribution in the topics: Population & Visualization. The organization has 12115 authors who have published 27401 publications receiving 951162 citations. The organization is also known as: University of Constance & Universität Konstanz.

Fermentation of Trihydroxybenzenes by Pelobacter acidigallici gen. nov. sp. nov., a New Strictly Anaerobic, Non-Sporeforming Bacterium

Abstract: Five strains of rod-shaped, Gram-negative, non-sporing, strictly anaerobic bacteria were isolated from limnic and marine mud samples with gallic acid or phloroglucinol as sole substrate. All strains grew in defined mineral media without any growth factors; marine isolates required salt concentrations higher than 1% for growth, two freshwater strains only thrived in freshwater medium. Gallic acid, pyrogallol, 2,4,6-trihydroxybenzoic acid, and phloroglucinol were the only substrates utilized and were fermented stoichiometrically to 3 mol acetate (and 1 mol CO2) per mol with a growth yield of 10g cell dry weight per mol of substrate. Neither sulfate, sulfur, nor nitrate were reduced. The DNA base ratio was 51.8% guanine plus cytosine. A marine isolate, Ma Gal 2, is described as type strain of a new genus and species, Pelobacter acidigallici gen. nov. sp. nov., in the family Bacteroidaceae. In coculture with Acetobacterium woodii, the new isolates converted also syringic acid completely to acetate. Cocultures with Methanosarcina barkeri converted the respective substrates completely to methane and carbon dioxide.

SAF-Box, a Conserved Protein Domain That Specifically Recognizes Scaffold Attachment Region DNA

Abstract: SARs (scaffold attachment regions) are candidate DNA elements for partitioning eukaryotic genomes into independent chromatin loops by attaching DNA to proteins of a nuclear scaffold or matrix. The interaction of SARs with the nuclear scaffold is evolutionarily conserved and appears to be due to specific DNA binding proteins that recognize SARs by a mechanism not yet understood. We describe a novel, evolutionarily conserved protein domain that specifically binds to SARs but is not related to SAR binding motifs of other proteins. This domain was first identified in human scaffold attachment factor A (SAF-A) and was thus designated SAF-Box. The SAF-Box is present in many different proteins ranging from yeast to human in origin and appears to be structurally related to a homeodomain. We show here that SAF-Boxes from four different origins, as well as a synthetic SAF-Box peptide, bind to natural and artificial SARs with high specificity. Specific SAR binding of the novel domain is achieved by an unusual mass binding mode, is sensitive to distamycin but not to chromomycin, and displays a clear preference for long DNA fragments. This is the first characterization of a specific SAR binding domain that is conserved throughout evolution and has DNA binding properties that closely resemble that of the unfractionated nuclear scaffold.

Type and timing of adverse childhood experiences differentially affect severity of PTSD, dissociative and depressive symptoms in adult inpatients

Abstract: A dose-dependent effect of Adverse Childhood Experiences (ACE) on the course and severity of psychiatric disorders has been frequently reported. Recent evidence indicates additional impact of type and timing of distinct ACE on symptom severity experienced in adulthood, in support of stress-sensitive periods in (brain) development. The present study seeks to clarify the impact of ACE on symptoms that are often comorbid across various diagnostic groups: symptoms of posttraumatic stress disorder (PTSD), shutdown dissociation and depression. A key aim was to determine and compare the importance of dose-dependent versus type and timing specific prediction of ACE on symptom levels. Exposure to ten types of maltreatment up to age 18 were retrospectively assessed in N = 129 psychiatric inpatients using the Maltreatment and Abuse Chronology of Exposure (MACE). Symptoms of PTSD, shutdown dissociation, and depression were related to type and timing of ACE. The predictive power of peak types and timings was compared to that of global MACE measures of duration, multiplicity and overall severity. A dose-dependent effect (MACE duration, multiplicity and overall severity) on severity of all symptoms confirmed earlier findings. Conditioned random forest regression verified that PTSD symptoms were best predicted by overall ACE severity, whereas type and timing specific effects showed stronger prediction for symptoms of dissociation and depression. In particular, physical neglect at age 5 and emotional neglect at ages 4–5 were related to increased symptoms of dissociation, whereas the emotional neglect at age 8–9 enhanced symptoms of depression. In support of the sensitive period of exposure model, present results indicate augmented vulnerability by type x timing of ACE, in particular emphasizing pre-school (age 4–5) and pre-adolescent (8–9) periods as sensitive for the impact of physical and emotional neglect. PTSD, the most severe stress-related disorder, varies with the amount of adverse experiences irrespective of age of experience. Considering type and timing of ACE improves understanding of vulnerability, and should inform diagnostics of psychopathology like PTSD, dissociation and depression in adult psychiatric patients.

Selecting good views of high-dimensional data using class consistency

Abstract: Many visualization techniques involve mapping high-dimensional data spaces to lower-dimensional views. Unfortunately, mapping a high-dimensional data space into a scatterplot involves a loss of information; or, even worse, it can give a misleading picture of valuable structure in higher dimensions. In this paper, we propose class consistency as a measure of the quality of the mapping. Class consistency enforces the constraint that classes of n-D data are shown clearly in 2-D scatterplots. We propose two quantitative measures of class consistency, one based on the distance to the class's center of gravity, and another based on the entropies of the spatial distributions of classes. We performed an experiment where users choose good views, and show that class consistency has good precision and recall. We also evaluate both consistency measures over a range of data sets and show that these measures are efficient and robust.