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Entwicklung automatisierter Bestrahlungsprozesse zur Behandlung von Pathogenen
No full textIonisierende Strahlung wird auf vielfältige Weise in Bereichen der Industrie, Landwirtschaft, Medizin und in der Forschung eingesetzt, z.B. zur Sterilisation von Oberflächen und Medizinprodukten, Polymermodifikation, Diagnostik oder in der Entwicklung von Impfstoffen. Im Rahmen dieser Arbeit wurden Prozesse zur automatisierten Bestrahlung von flüssigen Pathogen-Proben mit niederenergetischer Elektronenstrahlung (eng. Low-Energy Electron Irradiation, LEEI) etabliert. LEEI, wie auch andere Arten der ionisierenden Strahlung, erzielt Effekte in biologischen Proben vorrangig durch Schädigung von Nukleinsäuren. Proteinstrukturen, unter anderem essentielle Antigene für eine effektive Immunantwort, bleiben größtenteils intakt. Kernstück der Arbeit ist eine Prototyp-Anlage, die sich am Fraunhofer-Institut für Zelltherapie und Immunologie befindet, die erstmalig die Bestrahlung von Flüssigkeiten in einem automatisierten, skalierbaren und produktionsgeeigneten Prozess ermöglicht. In diese Anlage können verschiedene Module integriert werden, die dünne Flüssigkeitsfilme generieren, da der Einsatz von LEEI stark durch die niedrige Eindringtiefe (<200 µm) limitiert ist. Fokus der Arbeit liegt auf der Entwicklung von Prozessen zur Inaktivierung vom Früh-Sommer-Meningoenzephalitis-Virus (FSME bzw. engl. TBEV) und dem humanen respiratorischen Synzytial-Virus (RSV), sowie zur Attenuierung (Reduktion der Virulenz eines Erregers unter erhalt der Immunogenität) zweier Endoparasiten der Gruppe Apicomplexa, Toxoplasma gondii und Cryptosporidium parvum
Data integration between clinical research and patient care: A framework for context-depending data sharing and in silico predictions
No full textThe transfer of new insights from basic or clinical research into clinical routine is usually a lengthy and time-consuming process. Conversely, there are still many barriers to directly provide and use routine data in the context of basic and clinical research. In particular, no coherent software solution is available that allows a convenient and immediate bidirectional transfer of data between concrete treatment contexts and research settings. Here, we present a generic framework that integrates health data (e.g., clinical, molecular) and computational analytics (e.g., model predictions, statistical evaluations, visualizations) into a clinical software solution which simultaneously supports both patient-specific healthcare decisions and research efforts, while also adhering to the requirements for data protection and data quality. Specifically, our work is based on a recently established generic data management concept, for which we designed and implemented a web-based software framework that integrates data analysis, visualization as well as computer simulation and model prediction with audit trail functionality and a regulation-compliant pseudonymization service. Within the front-end application, we established two tailored views: a clinical (i.e., treatment context) perspective focusing on patient-specific data visualization, analysis and outcome prediction and a research perspective focusing on the exploration of pseudonymized data. We illustrate the application of our generic framework by two use-cases from the field of haematology/oncology. Our implementation demonstrates the feasibility of an integrated generation and backward propagation of data analysis results and model predictions at an individual patient level into clinical decision-making processes while enabling seamless integration into a clinical information system or an electronic health record
Die Bedeutung spezifischer studienbedingter Anforderungen und Ressourcen für die Gesundheit und Lebenszufriedenheit von Studierenden
No full textHintergrund - Studien weisen auf einen Zusammenhang zwischen Studienbedingungen und gesundheitlichen Beeinträchtigungen von Studierenden hin. Ziel war die Untersuchung des Einflusses spezifischer studienbezogener Anforderungen und Ressourcen auf die selbsteingeschätzte Gesundheit.
Methode - Studierende der Technischen Universität Dresden wurden online zu ihrer Gesundheit und ihrem Studium befragt. Bezugnehmend auf das Study Demands-Resources Modell wurden deskriptive und Zusammenhangsanalysen durchgeführt.
Ergebnisse - 1.312 Studierende wurden in die Untersuchungen einbezogen. Ca. ein Fünftel der Teilnehmenden gab eine geringe Lebenszufriedenheit und hohe Erschöpfung an. Zeitliche und geistige Anforderungen sind mit einer schlechteren Gesundheit, soziale Unterstützung und Zeitspielraum im Studium mit einer besseren Gesundheit verbunden. Dies wurde besonders bei einer Kombination von hohen Anforderungen und geringen Ressourcen deutlich.
Schlussfolgerung - Die Ergebnisse liefern Ansatzpunkte für präventive Maßnahmen zur Stärkung der studentischen Gesundheit.Background - Studies report an association between study conditions and student health outcomes. The aim was to investigate the influence of specific study-related demands and resources on self-assessed health.
Method - Students of the Technical University of Dresden were surveyed online about their health and their studies. Referring to the Study Demands-Resources Model descriptive and regression analytic methods were applied.
Results - 1,312 students were included in the analyses. About one-fifth of participants reported low life satisfaction and high exhaustion. Time and cognitive demands were associated with poorer health, social support and time margin in studies were linked to better health. This relationship was particularly evident with a combination of high demands and low resources.
Conclusion - The results provide approaches for preventive measures to strengthen the health of students
Group Contribution Method for the Residual Entropy Scaling Model for Viscosities of Branched Alkanes
No full textIn this work it is shown how the entropy scaling paradigm introduced by Rosenfeld (Phys Rev A 15:2545–2549, 1977, https://doi.org/10.1103/PhysRevA.15.2545) can be extended to calculate the viscosities of branched alkanes by group contribution methods (GCM), making the technique more predictive. Two equations of state (EoS) requiring only a few adjustable parameters (Lee–Kesler–Plöcker and PC-SAFT) were used to calculate the thermodynamic properties of linear and branched alkanes. These EOS models were combined with first-order and second-order group contribution methods to obtain the fluid-specific scaling factor allowing the scaled viscosity values to be mapped onto the generalized correlation developed by Yang et al. (J Chem Eng Data 66:1385–1398, 2021, https://doi.org/10.1021/acs.jced.0c01009) The second-order scheme offers a more accurate estimation of the fluid-specific scaling factor, and overall the method yields an AARD of 10 % versus 8.8 % when the fluid-specific scaling factor is fit directly to the experimental data. More accurate results are obtained when using the PC-SAFT EoS, and the GCM generally out-performs other estimation schemes proposed in the literature for the fluid-specific scaling factor
Stability of Singular Solutions of Nonlinear Equations with Restricted Smoothness Assumptions
No full textThis work is concerned with conditions ensuring stability of a given solution of a system of nonlinear equations with respect to large (not asymptotically thin) classes of right-hand side perturbations. Our main focus is on those solutions that are in a sense singular, and hence, their stability properties are not guaranteed by “standard” inverse function-type theorems. In the twice differentiable case, these issues have received some attention in the existing literature. Moreover, a few results in this direction are known in the case when the first derivative is merely B-differentiable. Here, we further elaborate on a similar setting, but the main attention is paid to the case of piecewise smooth equations. Specifically, we study the effect of singularity of a solution for some active smooth selection on the overall stability properties, and we provide sufficient conditions ensuring the needed stability properties in the cases when such smooth selections may exist. Finally, an application to a piecewise smooth reformulation of complementarity problems is given
Functional connectivity differences in healthy individuals with different well-being states
No full textWell-being (WB) is defined as a healthy state of mind and body. It is a state in which an individual is able to contribute to its society, able to work productively and overcome the normal stress of life. WB is a multi-dimensional concept and covers different aspects, including life satisfaction and quality of life. Little is known as to whether there are differences in connectivity patterns between healthy individuals with different WB states. We evaluated the WB state of healthy individuals with no prior diagnosis of any psychological disorder using the “General habitual WB questionnaire”, covering mental, physical and social domains. Subjects with mean age 25±4 years were divided into two groups, high WB state (n = 18) and low WB state (n = 14). We investigated and compared the groups for their resting state (rs-fMRI) functional connectivity (FC) patterns using DPARSF compiled with SPM12 toolbox. WB specific seeds were chosen for FC analysis. In the high WB group we found significantly increased connectivity between bilateral angular gyrus and frontal regions comprising the orbitofrontal cortex (OFC), right frontal superior gyrus and left precuneus. The low-WB group showed increased connectivity between the bilateral amygdala and the occipital lobe and the right anterior OFC. To conclude connectivity results with a quantitative approach, suggest differences in cognitive and decision-making processing between people with varying WB states. The high-WB group when compared to low-WB group had higher cognitive processing and decision making based on their internal mental processes and self-referential processing, whereas connectivity between amygdala and OFC relates to decreased attentional processing and promotes effective emotional regulation that may be a lead to rumination
Journal of Neuro Oncology : Diagnostic and therapeutic implications of IDH mutations in gliomas following the 2021 World Health Organization classification of CNS tumors
No full textThe discovery of mutations in the IDH1 and IDH2 genes in gliomas has significantly impacted the classification and treatment of these tumors [1, 2]. While histological grading has traditionally been used to predict prognosis in gliomas, it is now evident that IDH mutation status provides a more accurate indicator of a patient’s clinical course. In recognition of this, the WHO 2016 classification of CNS tumors has defined IDH-mutant gliomas as a distinct entity, marking a paradigm shift in tumor categorization [3]. However, despite the significant impact of IDH mutation status on prognosis, the post-treatment clinical course of IDH-mutant gliomas remains highly variable [4, 5]. To gain a better understanding of the biological and clinical factors contributing to this variability, researchers have identified other recurrent molecular abnormalities and altered intracellular signaling pathways in IDH-mutant gliomas [6, 7]. The 2021 WHO classification has incorporated some of these molecular markers to better characterize IDH-mutant astrocytoma and oligodendroglioma and predict treatment response [8]. The integration of molecular and clinical data has paved the way for the development of new diagnostic tools and therapeutic strategies targeting oncogenic signaling pathways for the treatment of IDH-mutant patients...[from the Guest Editorial
Repeat turnover meets stable chromosomes: repetitive DNA sequences mark speciation and gene pool boundaries in sugar beet and wild beets
No full textSugar beet and its wild relatives share a base chromosome number of nine and similar chromosome morphologies. Yet, interspecific breeding is impeded by chromosome and sequence divergence that is still not
fully understood. Since repetitive DNAs are among the fastest evolving parts of the genome, we investigated, if repeatome innovations and losses are linked to chromosomal differentiation and speciation. We
traced genome and chromosome-wide evolution across 13 beet species comprising all sections of the genera Beta and Patellifolia. For this, we combined short and long read sequencing, flow cytometry, and cytogenetics to build a comprehensive framework that spans the complete scale from DNA to chromosome to genome. Genome sizes and repeat profiles reflect the separation into three gene pools with contrasting evolutionary patterns. Among all repeats, satellite DNAs harbor most genomic variability, leading to fundamentally different centromere architectures, ranging from chromosomal uniformity in Beta and Patellifolia to the formation of patchwork chromosomes in Corollinae/Nanae. We show that repetitive DNAs are causal for the genome expansions and contractions across the beet genera, providing insights into the genomic underpinnings of beet speciation. Satellite DNAs in particular vary considerably between beet genomes, leading to the evolution of distinct chromosomal setups in the three gene pools, likely contributing to the barriers in beet breeding. Thus, with their isokaryotypic chromosome sets, beet genomes present an ideal system for studying the link between repeats, genomic variability, and chromosomal differentiation and provide a theoretical fundament for understanding barriers in any crop breeding effort
