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During the last decades, Western societies live in an environment that is characterized by passive forms of transportation, sedentary jobs and modern communication techniques. These changes have contributed to a predominantly physically inactive lifestyle in which a vast majority of our waking hours is spent in a seated position. Insufficient physical activity is a major contributor to a worse cardiometabolic health profile and the development of chronic diseases, such as type 2 diabetes mellitus and cardiovascular diseases. Despite the significant health benefits of physical activity, adherence to these physical activity guidelines is poor. In addition, it appears that even the recommended levels of physical activity do not always fully protect against cardiometabolic risk factors and the development of chronic diseases. As such, next to the time spent in physical activity, an additional factor that also appears to determine cardiometabolic health and chronic disease development is sedentary behaviour. This thesis investigated the effects of high amounts of physical activity to attenuate the detrimental effects of sedentary behaviour on cardiometabolic health. In addition, the effects of consumer wearable activity trackers to improve physical activity, sedentary behaviour and cardiometabolic health were investigated.

Covalent organic frameworks (COFs) are porous materials with high surface areas, making them interesting for a large variety of applications including energy storage, gas separation, photocatalysis, and chemical sensing. Structural variation plays an important role in tuning COF properties. Next to the type of the building block core, bonding directionality, and linking chemistry, substitution of building blocks provides another level of synthetic control. Thorough characterization and comparison of various substitution patterns is relevant for the molecular engineering of COFs via rational design. To this end, we have systematically synthesized and characterized multiple combinations of several methylated and non-methylated building blocks to obtain a series of imine-based COFs. This includes the experimental assignment of the COF structure by solid-state NMR. By comparing the properties of all COFs, the following trends were found: (1) upon methylation of the aldehyde nodes, COFs show increased Brunauer-Emmett-Teller surface areas, reduced pore collapse, blue-shifted absorbance spectra, and ∼0.2 eV increases in their optical band gaps. (2) COFs with dimethylated amine linkers show a lower porosity. (3) In tetramethylated amine linkers, the COF porosity even further decreases, the absorbance spectra are clearly red-shifted, and smaller optical band gaps are obtained. Our study shows that methyl substitution patterns on COF building blocks are a handle to control the UV absorbance of the resulting frameworks.

Model-free phasor image analysis, well established in fluorescence lifetime imaging and only recently applied to qMRI T2 data processing, is here adapted and validated for myocardial qMRI T1 mapping. Contrarily to routine mono-exponential fitting procedures, phasor enables mapping the lifetime information from all image voxels to a single plot, without resorting to any regression fitting analysis, and describing multi-exponential qMRI decays without biases due to violated modelling assumptions. In this feasibility study, we test the performance of our recently developed full-harmonics phasor method for unravelling partial-volume effects, motion or pathological tissue alteration, respectively on a numerically-simulated dataset, a healthy subject scan, and two pilot patient datasets. Our results show that phasor analysis can be used, as alternative method to fitting analysis or other model-free approaches, to identify motion artifacts or partial-volume effects at the myocardium-blood interface as characteristic deviations, or delineations of scar and remote myocardial tissue in patient data., ImPhys/Computational Imaging, ImPhys/Medical Imaging

Model-free phasor image analysis, well established in fluorescence lifetime imaging and only recently applied to qMRI T2 data processing, is here adapted and validated for myocardial qMRI T1 mapping. Contrarily to routine mono-exponential fitting procedures, phasor enables mapping the lifetime information from all image voxels to a single plot, without resorting to any regression fitting analysis, and describing multi-exponential qMRI decays without biases due to violated modelling assumptions. In this feasibility study, we test the performance of our recently developed full-harmonics phasor method for unravelling partial-volume effects, motion or pathological tissue alteration, respectively on a numerically-simulated dataset, a healthy subject scan, and two pilot patient datasets. Our results show that phasor analysis can be used, as alternative method to fitting analysis or other model-free approaches, to identify motion artifacts or partial-volume effects at the myocardium-blood interface as characteristic deviations, or delineations of scar and remote myocardial tissue in patient data.

Phasor analysis is a robust, nonfitting, method for the study of multiexponential decays in lifetime imaging data, routinely used in Fluorescence Lifetime Imaging Microscopy (FLIM) and only recently validated for Magnetic Resonance Imaging (MRI). In the established phasor approach, typically only the first Fourier harmonic is used to unravel time-domain exponential trends and their intercorrelations across image voxels. Here, we demonstrate the potential of full-harmonics (FH) phasor analysis by using all frequency-domain data points in simulations and quantitative MRI (qMRI) T2 measurements of phantoms with bulk liquids or liquid-filled porous particles and of a human brain. We show that FH analysis, while of limited advantage in FLIM due to the correlated nature of shot noise, in MRI outperforms single-harmonic phasor in unravelling multiple physical environments and partial-volume effects otherwise undiscernible. We foresee application of FH phasor to, e.g., big-data analysis in qMRI of biological or other multiphase systems, where multiparameter fitting is unfeasible.