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Coming theses from other universities

  • Post-traumatic Stress Disorder – Assessment of current diagnostic definitions Author: Kristina Bondjers Link: Publication date: 2020-02-19 13:41

    Post-traumatic stress disorder (PTSD) is a debilitating condition that may arise after exposure to shocking, frightening, or dangerous events. Hallmark symptoms are re-experiencing, avoidance, and hyperarousal. Other common symptoms are more ancillary and overlap with other psychiatric disorders (e.g., anhedonia, interpersonal problems, and affective dysregulation). The variety of symptoms associated with PTSD allows for large differences in symptom presentation between individuals. Studies of the latent structure of PTSD (e.g., latent class analysis, confirmatory factor analysis) have been highly influential in the conceptualisation of the disorder. The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and the eleventh edition of the International Classification of Diseases (ICD-11) have taken vastly different approaches to handling the symptom variety, with DSM-5 encompassing a broad definition, and the ICD-11 instead proposing a narrow PTSD construct and introducing the new diagnosis complex PTSD (CPTSD), comprising PTSD in conjunction with ancillary symptoms.

    The principal aims of the present thesis were to examine how different symptom presentations of PTSD were associated with well-known predictors of PTSD and prospective outcome, to evaluate the dimensional structure of PTSD as it is proposed in current diagnostic nomenclature, to provide methods for assessing PTSD in the Swedish language, and to evaluate the diagnostic agreement between DSM-5 and ICD-11.

    Using latent class analysis, subgroups with differences in PTSD symptom presentation were examined and assessed regarding their predictive validity. In a sample of natural disaster survivors, subgroups differed mainly in symptom severity. In a mixed trauma sample, subgroups differed in their likelihood of fulfilling hallmark versus ancillary symptoms, and in self-reported concurrent and prospective psychological distress.

    As for the dimensional structure of DSM-5 symptomology, support was not found for the four-factor DSM-5 model, but rather for a six-factor and a seven-factor model. For ICD-11 symptomatology, the ICD-11 model was supported, both with and without a higher-order separation of PTSD and CPTSD. Two instruments for assessing PTSD were evaluated: the PTSD checklist for DSM-5 (PCL-5) and the International Trauma Interview for ICD-11 (ITI). Results indicated support for both instruments as valid and reliable tools. The diagnostic agreement between DSM-5 and ICD-11 was moderate.

    Summarised, the studies suggest that variables such as secondary stressors and event-specific exposure influence symptom expression, and that the combination of hallmark and ancillary symptoms of PTSD is associated with the long-term maintenance of psychological distress. Results support the use of the PCL-5 and the ITI as assessment tools for DSM-5 and ICD-11 PTSD. The insufficient agreement between DSM-5 and ICD-11 PTSD and CPTSD poses a challenge for future researchers and clinicians.

  • Physical funtion and body composition in ageing : the effects of physical activity and healthy diet Author: Peter Edholm Link: Publication date: 2020-02-18 09:39
  • New targeted therapies for malignant neural tumors : From systematic discovery to zebrafish models Author: Elin Almstedt Link: Publication date: 2020-02-14 09:40

    Cancers in the neural system presents a major health challenge. The most aggressive brain tumor in adults, glioblastoma, has a median survival of 15 months and few therapeutic options. High-risk neuroblastoma, a childhood tumor originating in the sympathetic nervous system, has a 5-year survival under 50%, despite extensive therapy. Molecular characterization of these tumors has had some, but so far limited, clinical impact. In neuroblastoma, patients with ALK mutated tumors can benefit from treatment with ALK inhibitors. In glioblastoma, molecular subgroups have not yet revealed any subgroup-specific gene dependencies due to tumor heterogeneity and plasticity. In this thesis, we identify novel treatment candidates for neuroblastoma and glioblastoma. 

    In paper I, we discover novel drug targets for high-risk neuroblastoma by integrating patient data, large-scale pharmacogenomic profiles, and drug-protein interaction maps. Using a novel algorithm, TargetTranslator, we identify more than 80 targets for this patient group. Activation of cannabinoid receptor 2 (CNR2) or inhibition of mitogen-activated protein kinase 8 (MAPK8) reduces tumor growth in zebrafish and mice models of neuroblastoma, establishing TargetTranslator as a useful tool for target discovery in cancer. 

    In paper II, we screen approximately 1500 compounds across 100 molecularly characterized cell lines from patients to uncover heterogeneous responses to drugs in glioblastoma. We identify several connections between pathway activities and drug response. Sensitivity to proteasome inhibition is linked to oxidative stress response and p53 activity in cells, and can be predicted using a gene signature. We also discover sigma receptors as novel drug targets for glioblastoma and find a synergistic vulnerability in targeting cholesterol homeostasis.

    In paper III, we systematically explore novel targets for glioblastoma using an siRNA screen. Downregulation of ZBTB16 decreases cell cycle-related proteins and transcripts in patient-derived glioblastoma cells. Using a zebrafish assay, we find that ZBTB16 promotes glioblastoma invasion in vivo

    In paper IV, we characterized the growth of seven patient-derived glioblastoma cell lines in orthotopic zebrafish xenografts. Using automated longitudinal imaging, we find that tumor engraftment strongly correlates with tumor initiation capacity in mice xenografts and that the heterogeneous response to proteasome inhibitors is maintained in vivo

    In summary, this thesis identifies novel targets for glioblastoma and neuroblastoma using systematic approaches. Treatment candidates are evaluated in novel zebrafish xenograft models that are developed for high-throughput glioblastoma and neuroblastoma drug evaluation. Together, this thesis provides promising evidence of new therapeutic options for malignant neural tumors.