Factors associated with depressive mood at the onset of multiple sclerosis - an analysis of 781 patients of the German NationMS cohort

Background: Depression has a major impact on the disease burden of multiple sclerosis (MS). Analyses of overlapping MS and depression risk factors [smoking, vitamin D (25-OH-VD) and Epstein-Barr virus (EBV) infection] and sex, age, disease characteristics and neuroimaging features associated with depressive symptoms in early MS are scarce.Objectives: To assess an association of MS risk factors with depressive symptoms within the German NationMS cohort.Design: Cross-sectional analysis within a multicenter observational study.Methods: Baseline data of n = 781 adults with newly diagnosed clinically isolated syndrome or relapsing-remitting MS qualified for analysis. Global and region-specific magnetic resonance imaging (MRI)-volumetry parameters were available for n = 327 patients. Association of demographic factors, MS characteristics and risk factors [sex, age, smoking, disease course, presence of current relapse, expanded disability status scale (EDSS) score, fatigue (fatigue scale motor cognition), 25-OH-VD serum concentration, EBV nuclear antigen-1 IgG (EBNA1-IgG) serum levels] and depressive symptoms (Beck Depression Inventory-II, BDI-II) was tested as a primary outcome by multivariable linear regression. Non-parametric correlation and group comparison were performed for associations of MRI parameters and depressive symptoms.Results: Mean age was 34.3 years (95% confidence interval: 33.6-35.0). The female-to-male ratio was 2.3:1. At least minimal depressive symptoms (BDI-II > 8) were present in n = 256 (32.8%), 25-OH-VD deficiency (<20 ng/ml) in n = 398 (51.0%), n = 246 (31.5%) participants were smokers. Presence of current relapse [coefficient (c) = 1.48, p = 0.016], more severe fatigue (c = 0.26, p < 0.0001), lower 25-OH-VD (c = -0.03, p = 0.034) and smoking (c = 0.35, p = 0.008) were associated with higher BDI-II scores. Sex, age, disease course, EDSS, month of visit, EBNA1-IgG levels and brain volumes at baseline were not.Conclusion: Depressive symptoms need to be assessed in early MS. Patients during relapse seem especially vulnerable to depressive symptoms. Contributing factors such as fatigue, vitamin D deficiency and smoking, could specifically be targeted in future interventions and should be investigated in prospective studies

Constraint-basierte Lösungsmethoden für das Phasenproblem in der Kristallographie

The phase problem is the major problem in the field of X-ray crystallography. In the context of direct methods, that use mathematical techniques to compute an electron density map from the diffraction data without any further experiments, binary integer programming models for solving the phase problem have been de- veloped. Based on descriptions of topological properties of 2-dimensional binary pictures known from the field of discrete tomography, these models have been extended for the 3-dimensional case. As the formulations are in general not sufficient to describe the more complex properties of the shape of proteins, binary integer pro- grams have been derived for describing different additional topological properties. In general, the binary integer program for solving the phase problem, leads to a set of different optimal solutions. The additional constraints increase the quality of the solution set. The main property considered is one restricting the number of components in the resulting solution. Using graph theoretical methods and a separation algorithm, a model to describe this property has been found and implemented. Computational results have been presented and evaluated. It has been shown, that the added topological constraints increase significantly the quality of the solution set. In the last chapter, a method to find the solutions all at once based on singu- lar value decomposition and methods to find integer points in ellipsoids has been developed. In further work, the efficiency of this method for the phase problem should be evaluated and the method could be implemented and tested. In order to further increase the solutions’ quality, more additional constraints could be formulated and added. If the running time of the solving algorithm could be decreased, a refinement of the model would be possible. Bigger grids could be considered showing more de- tails of the reconstructed protein. More phase values than just four ones could be introduced. A restriction of the electron density distribution to a finite number of states instead of regarding just the two binary ones would be a possible extension. So, based on the promising results presented here, lots of further work extending and refining the developed approaches is possible.Röntgenkristallographie ist derzeit die Standardmethode zur Ermittlung der drei- dimensionalen Struktur biologischer Makromoleküle, wie z. B. von Proteinen, und liefert damit eine wichtige Basis der Strukturbiologie sowie der modernen Biotechnologie. Aus Röntgenexperimenten erhält man Beugungsmuster, aus welchen dann die Struktur des zu untersuchenden Kristalls berechnet werden soll. Diese wird durch die zugehörige Elektronendichteverteilung beschrieben. Allerdings liefert das Beugungsmuster nur die Beträge der komplexen Fourierkoeffizienten der Elektronendichte, nicht die zugehörigen Phasenwerte. Das Problem, diese Phasenwerte zu ermitteln, ist das Phasenproblem in der Röntgenkristallographie. Die Informationen, welche aus dem Röntgenexperiment gewonnen werden können, sind nicht ausreichend um dieses Phasenproblem zu lösen. Daher erhält man nicht nur eine, sondern eine Menge zulässiger Lösungen. Zusätzliche Informationen über die Elektronendichteverteilung können dann hinzugezogen werden um die Qualität dieser Lösungen zu verbessern. In dieser Arbeit wird ein ganzzahliger linearer Optimierungsansatz zur Lösung des Phasenproblems entwickelt, in dem verschiedene topologische Eigenschaften von Proteinen modelliert und als zusätzliche Informationen verwendet werden. Die wichtigste Eigenschaft, die so modelliert und für die Problemlösung hinzugezogen wird, ist die Zusammenhangseigenschaft von Proteinen. Diese sichert, dass die berechnete Struktur nicht aus mehr als einer gegebenen Anzahl zusammenhängender Komponenten besteht. Bei der Modellierung dieser Zusammenhangseigenschaft werden graphentheoretische Methoden sowie ein Separationsalgorithmus genutzt. Der Modellierungsansatz wurde implementiert und mit Daten von echten Proteinen getestet. Die Testergebnisse zeigen, dass die Qualität der Lösungen des Phasenproblems durch die Hinzunahme der topologischen Eigenschaften deutlich verbessert wird

Geometric Constraints for the Phase Problem in X-Ray Crystallography

X-ray crystallography is one of the main methods to establish the three-dimensional structure of biological macromolecules. In an X-ray experiment, one can measure only the magnitudes of the complex Fourier coefficients of the electron density distribution under study, but not their phases. The problem of recovering the lost phases is called the phase problem. Buildingon earlier work byLunin/Urzhumtsev/Bockmayr, we extendtheir constraint-based approach to the phase problem by adding further 0-1 linear programming constraints. These constraints describe geometric properties of proteins and increase the quality of the solutions. The approach has been implemented using SCIP and CPLEX, first computational results are presented here.

The relationship between differences in students’ computer and information literacy and response times: an analysis of IEA-ICILS data

Heldt M, Massek C, Drossel K, Eickelmann B. The relationship between differences in students’ computer and information literacy and response times: an analysis of IEA-ICILS data. Large-scale Assessments in Education. 2020;8(1): 12.#### Background Due to the increasing use of information and communication technology, computer-related skills are important for all students in order to participate in the digital age (Fraillon, J., Ainley, J., Schulz, W., Friedman, T. & Duckworth, D. (2019). Preparing for life in a digital world: IEA International Computer and Information Literacy Study 2018 International Report. Amsterdam: International Association for the Evaluation of Educational Achievement (IEA). Retrieved from https://www.iea.nl/sites/default/files/2019-11/ICILS%202019%20Digital%20final%2004112019.pdf). Educational systems play a key role in the mediation of these skills (Eickelmann. Second Handbook of Information Technology in Primary and Secondary Education. Cham: Springer, 2018). However, previous studies have shown differences in students’ computer and information literacy (CIL). Although various approaches have been used to explain these differences, process data, such as response times, have never been taken into consideration. Based on data from the IEA-study ICILS 2013 of the Czech Republic, Denmark and Germany, this secondary analysis examines to what extent response times can be used as an explanatory approach for differences in CIL also within different groups of students according to student background characteristics (gender, socioeconomic background and immigrant background). #### Methods First, two processing profiles using a latent profile analysis (Oberski 2016) based on response times are determined—a fast and a slow processing profile. To detect how these profiles are related to students’ CIL, also in conjunction with students’ background characteristics (socioeconomic and immigrant background), descriptive statistics are used. #### Results The results show that in the Czech Republic and Germany, students belonging to the fast processing profile have on average significantly higher CIL than students allocated to the slow processing profile. In Denmark, there are no significant differences. Concerning the student background characteristics in the Czech Republic, there are significant negative time-on-task effects for all groups except for students with an immigrant background and students with a high parental occupational status. There are no significant differences in Denmark. For Germany, a significant negative time-on-task effect can be found among girls. However, the other examined indicators for Germany are ambiguous. #### Conclusions The results show that process data can be used to explain differences in students’ CIL: In the Czech Republic and Germany, there is a correlation between response times and CIL (significant negative time-on-task effect). Further analysis should also consider other aspects of CIL (e.g. reading literacy). What becomes clear, however, is that when interpreting and explaining differences in competence, data should also be included that relates to the completion process during testing