Faculty Bibliography

Drosophila melanogaster is a powerful model organism for dissecting the molecular mechanisms that regulate sleep, and numerous studies in the fly have identified genes that impact sleep-wake cycles. Conditional genetic analysis is essential to distinguish the mechanisms by which these genes impact sleep: some genes might exert their effects developmentally, for instance by directing the assembly of neuronal circuits that regulate sleep; other genes may regulate sleep in adulthood; and yet other genes might influence sleep by both developmental and adult mechanisms. Here we have assessed two ligand-inducible expression systems, Geneswitch and the Q-system, for conditional and neuronally restricted manipulations of sleep in Drosophila While adult-specific induction of a neuronally expressed Geneswitch transgene (elav-GS) is compatible with studies of sleep as shown previously, developmental induction of elav-GS strongly and nonspecifically perturbs sleep in adults. The alterations of sleep in elav-GS animals occur at low doses of Geneswitch agonist and in the presence of transgenes unrelated to sleep, such as UAS-CD8-GFP Furthermore, developmental elav-GS induction is toxic and reduces brood size, indicating multiple adverse effects of neuronal Geneswitch activation. In contrast, the transgenes and ligand of the Q-system do not significantly impact sleep-wake cycles when used for constitutive, developmental, or adult-specific neuronal induction. The nonspecific effects of developmental elav-GS activation on sleep indicate that such manipulations require cautious interpretation, and suggest that the Q-system or other strategies may be more suitable for conditional genetic analysis of sleep and other behaviors in Drosophila.

The mucopolysaccharidoses (MPS) comprise a heterogeneous family of rare, genetic lysosomal storage disorders that result in severe morbidity and reduced life expectancy. Emerging treatments for several of these disorders have triggered the search for clinically relevant biomarkers and clinical markers associated with treatment efficacy in populations and individuals. However, biomedical measures do not tell the whole story when characterizing a complex chronic disorder such as MPS. Health-related quality of life (HRQoL) tools that utilize patient reported outcomes to address patient parameters such as symptoms (pain, fatigue, psychological health), functioning (activity and limitations), or quality of life, have been used to supplement traditional biomedical endpoints. Many of these HRQoL tools have demonstrated that quality of life is negatively impacted in patients with MPS. There is both the opportunity and need to formally standardize and validate HRQoL tools for the different MPS disorders.

Magnetic resonance imaging (MRI) has become an unrivalled medical diagnostic technique able to map tissue anatomy and physiology non-invasively. MRI measurements are meticulously engineered to control experimental conditions across the sample. However, residual radiofrequency (RF) field inhomogeneities are often unavoidable, leading to artefacts that degrade the diagnostic and scientific value of the images. Here we show that, paradoxically, these artefacts can be eliminated by deliberately interweaving freely varying heterogeneous RF fields into a magnetic resonance fingerprinting data-acquisition process. Observations made based on simulations are experimentally confirmed at 7 Tesla (T), and the clinical implications of this new paradigm are illustrated with in vivo measurements near an orthopaedic implant at 3T. These results show that it is possible to perform quantitative multiparametric imaging with heterogeneous RF fields, and to liberate MRI from the traditional struggle for control over the RF field uniformity.