Global human population growth is associated with many problems, such asrnfood and water provision, political conflicts, spread of diseases, and environmental destruction. The mitigation of these problems is mirrored in several global conventions and programs, some of which, however, are conflicting. Here, we discuss the conflicts between biodiversity conservation and disease eradication. Numerous health programs aim at eradicating pathogens, and many focus on the eradication of vectors, such as mosquitos or other parasites. As a case study, we focus on the "Pan African Tsetse and Trypanosomiasis Eradication Campaign," which aims at eradicating a pathogen (Trypanosoma) as well as its vector, the entire group of tsetse flies (Glossinidae). As the distribution of tsetse flies largely overlaps with the African hotspots of freshwater biodiversity, we argue for a strong consideration of environmental issues when applying vector control measures, especially the aerial applications of insecticides.rnFurthermore, we want to stimulate discussions on the value of speciesrnand whether full eradication of a pathogen or vector is justified at all. Finally, we call for a stronger harmonization of international conventions. Proper environmental impact assessments need to be conducted before control or eradication programs are carried out to minimize negative effects on biodiversity.

Dry tropical forests undergo massive conversion and degradation processes. This also holds true for the extensive Miombo forests that cover large parts of Southern Africa. While the largest proportional area can be found in Angola, the country still struggles with food shortages, insufficient medical and educational supplies, as well as the ongoing reconstruction of infrastructure after 27 years of civil war. Especially in rural areas, the local population is therefore still heavily dependent on the consumption of natural resources, as well as subsistence agriculture. This leads, on one hand, to large areas of Miombo forests being converted for cultivation purposes, but on the other hand, to degradation processes due to the selective use of forest resources. While forest conversion in south-central rural Angola has already been quantitatively described, information about forest degradation is not yet available. This is due to the history of conflicts and the therewith connected research difficulties, as well as the remote location of this area. We apply an annual time series approach using Landsat data in south-central Angola not only to assess the current degradation status of the Miombo forests, but also to derive past developments reaching back to times of armed conflicts. We use the Disturbance Index based on tasseled cap transformation to exclude external influences like inter-annual variation of rainfall. Based on this time series, linear regression is calculated for forest areas unaffected by conversion, but also for the pre-conversion period of those areas that were used for cultivation purposes during the observation time. Metrics derived from linear regression are used to classify the study area according to their dominant modification processes.rnWe compare our results to MODIS latent integral trends and to further products to derive information on underlying drivers. Around 13% of the Miombo forests are affected by degradation processes, especially along streets, in villages, and close to existing agriculture. However, areas in presumably remote and dense forest areas are also affected to a significant extent. A comparison with MODIS derived fire ignition data shows that they are most likely affected by recurring fires and less by selective timber extraction. We confirm that areas that are used for agriculture are more heavily disturbed by selective use beforehand than those that remain unaffected by conversion. The results can be substantiated by the MODIS latent integral trends and we also show that due to extent and location, the assessment of forest conversion is most likely not sufficient to provide good estimates for the loss of natural resources.

With the advent of high­throughput sequencing (HTS), profiling immunoglobulin (IG) repertoires has become an essential part of immunological research. The dissection of IG repertoires promises to transform our understanding of the adaptive immune system dynamics. Advances in sequencing technology now also allow the use of the Ion Torrent Personal Genome Machine (PGM) to cover the full length of IG mRNA transcripts. The applications of this bench­top scale HTS platform range from identification of new therapeutic antibodies to the deconvolution of malignant B cell tumors. In the context of this thesis, the usability of the PGM is assessed to investigate the IG heavy chain (IGH) repertoires of animal models. First, an innovate bioinformatics approach is presented to identify antigendriven IGH sequences from bulk sequenced bone marrow samples of transgenic humanized rats, expressing a human IG repertoire (OmniRatTM). We show, that these rats mount a convergent IGH CDR3 response towards measles virus hemagglutinin protein and tetanus toxoid, with high similarity to human counterparts. In the future, databases could contain all IGH CDR3 sequences with known specificity to mine IG repertoire datasets for past antigen exposures, ultimately reconstructing the immunological history of an individual. Second, a unique molecular identifier (UID) based HTS approach and network property analysis is used to characterize the CLL­like CD5+ B cell expansion of A20BKO mice overexpressing a natural short splice variant of the CYLD gene (A20BKOsCYLDBOE). We could determine, that in these mice, overexpression of sCYLD leads to unmutated subvariant of CLL (U­CLL). Furthermore, we found that this short splice variant is also seen in human CLL patients highlighting it as important target for future investigations. Third, the UID based HTS approach is improved by adapting it to the PGM sequencing technology and applying a custom­made data processing pipeline including the ImMunoGeneTics (IMGT) database error detection. Like this, we were able to obtain correct IGH sequences with over 99.5% confidence and correct CDR3 sequences with over 99.9% confidence. Taken together, the results, protocols and sample processing strategies described in this thesis will improve the usability of animal models and the Ion Torrent PGM HTS platform in the field if IG repertoire research.

Background: We evaluated depression and social isolation assessed at time of waitlisting as predictors of survival in heart transplant (HTx) recipients. Methods and Results: Between 2005 and 2006, 318 adult HTx candidates were enrolled in the Waiting for a New Heart Study, and 164 received transplantation. Patients were followed until February 2013. Psychosocial characteristics were assessed by questionnaires. Eurotransplant provided medical data at waitlisting, transplantation dates, and donor characteristics; hospitals reported medical data at HTx and date of death after HTx. During a median follow‐up of 70 months (<1"93 months post‐HTx), 56 (38%) of 148 transplanted patients with complete data died. Depression scores were unrelated to social isolation, and neither correlated with disease severity. Higher depression scores increased the risk of dying (hazard ratio=1.07, 95% confidence interval, 1.01, 1.15, P=0.032), which was moderated by social isolation scores (significant interaction term; hazard ratio = 0.985, 95% confidence interval, 0.973, 0.998; P=0.022). These findings were maintained in multivariate models controlling for covariates (P values 0.020"0.039). Actuarial 1‐year/5‐year survival was best for patients with low depression who were not socially isolated at waitlisting (86% after 1 year, 79% after 5 years). Survival of those who were either depressed, or socially isolated or both, was lower, especially 5 years posttransplant (56%, 60%, and 62%, respectively). Conclusions: Low depression in conjunction with social integration at time of waitlisting is related to enhanced chances for survival after HTx. Both factors should be considered for inclusion in standardized assessments and interventions for HTx candidates. We evaluated depression and social isolation assessed at time of waitlisting as predictors of survival in heart transplant (HTx) recipients.\r\n\r\nMethods and Results: Between 2005 and 2006, 318 adult HTx candidates were enrolled in the Waiting for a New Heart Study, and 164 received transplantation. Patients were followed until February 2013. Psychosocial characteristics were assessed by questionnaires. Eurotransplant provided medical data at waitlisting, transplantation dates, and donor characteristics; hospitals reported medical data at HTx and date of death after HTx. During a median follow‐up of 70 months (<1"93 months post‐HTx), 56 (38%) of 148 transplanted patients with complete data died. Depression scores were unrelated to social isolation, and neither correlated with disease severity. Higher depression scores increased the risk of dying (hazard ratio=1.07, 95% confidence interval, 1.01, 1.15, P=0.032), which was moderated by social isolation scores (significant interaction term; hazard ratio = 0.985, 95% confidence interval, 0.973, 0.998; P=0.022). These findings were maintained in multivariate models controlling for covariates (P values 0.020"0.039). Actuarial 1‐year/5‐year survival was best for patients with low depression who were not socially isolated at waitlisting (86% after 1 year, 79% after 5 years). Survival of those who were either depressed, or socially isolated or both, was lower, especially 5 years posttransplant (56%, 60%, and 62%, respectively).

Die Arbeit untersucht den Zusammenhang zwischen dem sprachlichen Zeichen und den Begriffen. Das Lexikon mit seinen Bedeutungsdefinitionen ist der augenscheinlichste Schnittpunkt zwischen dem Sprach- und dem Begriffssystem. Die Bedeutungsdefinition wird dabei als ein empirisches Datum betrachtet, das formal beschrieben werden kann. Die Bedeutungsanalyse überführt die Bedeutungsdefinition in eine komplexe Ordnungsstruktur. Die Methode wurde aus verschiedenen Begriffstheorien entwickelt, hauptsächlich aus Raili Kauppis Begriffstheorie und der Formalen Begriffsanalyse. Im Ergebnis erhält man aus den Bedeutungen eines Lexikons ein komplexes System von ein- bis n-stelligen Begriffen. Dieses Begriffssystem unterscheidet sich von den bekannten Semantischen Netzen durch einen völligen Verzicht auf von außen auf das System projizierte Relationen, wie den sogenannten semantischen Relationen. Die einzigen Relationen in diesem System sind begrifflich.