Visar resultat 1 - 5 av 118 avhandlingar innehållade ordet metabolomics.
Sammanfattning : Amyotrophic lateral sclerosis (ALS), also known as Charcot’s disease, motor neuron disease (MND) and Lou Gehrig’s disease, is a deadly, adult-onset neurodegenerative disorder characterized by progressive loss of upper and lower motor neurons, resulting in evolving paresis of the linked muscles. ALS is defined by classical features of the disease, but may present as a wide spectrum of phenotypes. LÄS MER
2. Mapping the consequenses of physical exercise and nutrition on human health : A predictive metabolomics approach
Sammanfattning : Human health is a complex and wide-ranging subject far beyond nutrition and physical exercise. Still, these factors have a huge impact on global health by their ability to prevent diseases and thus promote health. LÄS MER
3. Selectivity in NMR and LC-MS Metabolomics : The Importance of Sample Preparation and Separation, and how to Measure Selectivity in LC-MS Metabolomics
Sammanfattning : Until now, most metabolomics protocols have been optimized towards high sample throughput and high metabolite coverage, parameters considered to be highly important for identifying influenced biological pathways and to generate as many potential biomarkers as possible. From an analytical point of view this can be troubling, as neither sample throughput nor the number of signals relates to actual quality of the detected signals/metabolites. LÄS MER
Sammanfattning : In this thesis, I evaluated the impact of pre-centrifugation sample management on the plasma metabolome, providing verification for the protocol used in a study where I applied metabolomics to better understand the role of body composition in fracture occurrence using a large population-based cohort. In paper 1, I applied untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics analysis to plasma samples (n = 471) from healthy donors to predict and evaluate the effect of pre-centrifugation temperature and delay time on metabolomics data using a combination of random forest and generalized linear models. LÄS MER
Sammanfattning : The WHO classification of brain tumors is based on histological features and the aggressiveness of the tumor is classified from grade I to IV, where grade IV is the most aggressive. Today, the correlation between prognosis and tumor grade is the most important component in tumor classification. LÄS MER