Side effects of current chemotherapeutics limit their use in cancer therapy. Although many current drugs are highly toxic and potent, the effects they have on non-cancerous tissue are unbearable for patients. Targeting these drugs may provide a means to restrict their toxic effects to only cancer tissue while leaving healthy tissue unaffected. This approach requires that the drug is only available in cancer tissue, which has been achieved here by encapsulating drugs into liposomal nano-capsules which are capable of passively accumulating in cancerous tissue via the enhanced permeability and retention effect (EPR). In addition to localisation, a threshold dose must be achieved to deliver the desired toxic effect to the target tumour tissue. Previous strategies have relied on passive 'leaching' of the drug from liposomes, however this 'leaching' does not necessarily achieve the threshold dose required. In the present work, a new generation of liposomes has been developed whereby release is solely achieved in the presence of ultrasound triggered cavitation. Instigation of such cavitation events would normally require the target tissue be exposed to high and possibly damaging ultrasound pressures. To remove the need for these high pressures, cavitation nuclei have been developed to lower the cavitation threshold of surrounding media. To allow for improved co-localisation and treatment deeper into cancer tissue, cavitation nuclei were developed to be in the nanoscale size range. Two types of novel cavitation nuclei were produced, a rough surfaced carbon nanoparticle (CNP, ~180 nm) and smooth shaped polymeric nano-cup particle (NC, ~150, 470, or 770 nm). Both types of particle are solid nanoparticles with gas entrapped on their surface which was capable of cavitating in response to ultrasound without greatly affecting the particle itself. These particles are classified as cavicatalytic nanoparticles due to their ability to reduce the cavitation threshold of their surrounding media without being destroyed themselves. Finally, an entirely nanoscale release system was developed and tested in vitro and in vivo. The drug carrier (the liposome) and effector agent (the cavicatalytic nanoparticle) were used to demonstrate ultrasound triggered drug release, specifically in response to the generation of cavitation events. These cavitation events could be non-invasively monitored and characterised, adding to the potential clinical utility of the technologies developed and described here.

Pflegerische Dienstübergaben in Einrichtungen des Gesundheitswesens stellen für die Patientensicherheit und die kontinuierliche Versorgung von Patienten zentrale, aber gefährdete Kommunikationsszenarien dar. Die Akteure übergeben dabei nicht nur relevante Detailinformationen, sondern insbesondere auch die Verantwortung über die Versorgung des einzelnen Patienten. Zu diesem Zweck verständigen sie sich auf ein gemeinsames Bild oder mentales Modell zu dem klinischen Fall und dessen Versorgung. Es sind somit neben den kommunikativen insbesondere auch kognitive Prozesse in Dienstübergaben von Bedeutung. Vor diesem Hintergrund zielt die vorliegende Arbeit darauf ab, mithilfe eines neuartigen Ansatzes in Form einer kognitiven Karte des klinischen Falls innerhalb einer erweiterten Elektronischen Patientenakte die menschliche Informationsverarbeitung in Dienstübergaben zu unterstützen. Die kognitive Karte soll sowohl die frühen kognitiven Prozesse wie Aufmerksamkeit und Wahrnehmung, als auch die nachfolgenden kognitiven Prozesse wie Entscheiden und Planen fördern. Die Arbeit beschreibt die Anforderungsanalyse, die Systementwicklung und eine erste initiale Evaluation der Gebrauchstauglichkeit und der kognitiven Unterstützung des entwickelten Prototypens zur Darstellung kognitiver Karten im Rahmen von pflegerischen Dienstübergaben.

My thesis aims at identifying both genetic and environmental causes of major depressive disorder (MDD), using a large case-control study: 6,000 Chinese women with recurrent MDD and 6,000 controls. One of the major challenges for conducting genetic research on MDD is disease heterogeneity. The first question addressed is how different MDD is from highly comorbid anxiety disorders. I examine how anxiety disorders predict clinical features of depression and the degree of heterogeneity in their predictive pattern. The second question addressed is whether clinically defined MDD is a single disorder, or whether it consists of multiple subtypes. Results are then compared with and interpreted in the context of Western studies. Furthermore, latent class analysis and factor analysis results are also used in association analysis to explore more genetically homogeneous subtypes. Genetic data were derived using a novel strategy, low pass whole genome sequence analysis. Using genotypes imputed from the sequence data, I show that a cluster of single nucleotide polymorphisms (SNPs) is significantly associated with a binary disease phenotype including only cases with = 4 episodes of MDD, suggesting that recurrence might be an indication of genetic predisposition. The third issue examined is the contribution of rare variants to disease susceptibility. Again using sparse sequence data, I identified exonic sequence variants and performed gene-based analysis by comparing the number of variants between cases and controls in every gene. Furthermore I performed gene enrichment test by combining P values of SNP association tests at different minor allele frequency ranges. Overall, I did not find convincing evidence that rare variants aggregately contribute to disease susceptibility. However, the gene-based analysis resulted in an unexpected finding: cases have an excess of variants in all thirteen-protein coding mitochondrial genes, which was due to copy number differences in the mitochondrial genome. Both human phenotypic data as well as mice experimental data show that the increase in the mitochondrial copy number in cases is due to chronic stress.

Neurodegeneration is a progressive loss of neuron function or structure, including death of neurons, and occurs at many different levels of neuronal circuitry. In this thesis I discuss Parkinson’s Disease (PD), the second most common neurodegenerative disease (NDD). PD is a devastating progressive NDD often with delayed diagnosis due to detection methods that depend on the appearance of visible motor symptoms. By the time cardinal symptoms manifest, 60 to 80 percent or more of the dopamine-producing cells in the substantia nigra are irreversibly lost. Although there is currently no cure, earlier detection would be highly beneficial to manage treatment and track disease progression. However, today’s clinical diagnosis methods are limited to subjective evaluations and observation. Onset, symptoms and progression significantly vary from patient to patient across stages and subtypes that exceed the scope of a standardized diagnosis. The goal of this thesis is to provide the basis of a more general approach to study the brain, investigating early detection method for NDD with focus on PD. It details the preliminary development, testing and validation of tools and methods to objectively quantify and extrapolate motor and non-motor features of PD from behavioral and cognitive output during everyday life. Measures of interest are categorized within three domains: the motor system, cognitive function, and brain activity. This thesis describes the initial development of non-intrusive tools and methods to obtain high-resolution movement and speech data from everyday life and feasibility analysis of facial feature extraction and EEG for future integration. I tested and validated a body sensor system and wavelet analysis to measure complex movements and object interaction in everyday living situations. The sensor system was also tested for differentiating between healthy and impaired movements. Engineering and design criteria of the sensor system were tested for usability during everyday life. Cognitive processing was quantified during everyday living tasks with varying loaded conditions to test methods for measuring cognitive function. Everyday speech was analyzed for motor and non-motor correlations related to the severity of the disease. A neural oscillation detection (NOD) algorithm was tested in pain patients and facial expression was analyzed to measure both motor and non-motor aspects of PD. Results showed that the wearable sensor system can measure complex movements during everyday living tasks and demonstrates sensitivity to detect physiological differences between patients and controls. Preliminary engineering design supports clothing integration and development of a smartphone sensor platform for everyday use. Early results from loaded conditions suggest that attentional processing is most affected by cognitive demands and could be developed as a method to detect cognitive decline. Analysis of speech symptoms demonstrates a need to collect higher resolution spontaneous speech from everyday living to measure speech motor and non-motor speech features such as language content. Facial expression classifiers and the NOD algorithm indicated feasibility for future integration with additional validation in PD patients. Thus this thesis describes the initial development of tools and methods towards a more general approach to detecting PD. Measuring speech and movement during everyday life could provide a link between motor and cognitive domains to characterize the earliest detectable features of PD. The approach represents a departure from the current state of detection methods that use single data entities (e.g.one-off imaging procedures), which cannot be easily integrated with other data streams, are time consuming and economically costly. The long-term vision is to develop a non-invasive system to measure and integrate behavioral and cognitive features enabling early detection and progression tracking of degenerative disease.

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In this thesis, the problem of predicting the full dose distribution from a partially modeled dose calculation is addressed. Two solutions were studied: a vanilla Hierarchically Densely Connected U-net (HDUnet) and a Conditional Generative Adversarial Network (CGAN) with HDUnet as a generator. The CGAN approach is a 3D version of Pix2Pix [1] for Image to Image translation which we name Dose2Dose. The research question that this project tackled is whether the Dose2Dose can learn more effective dose transformations than the vanilla HDUnet. To answer this, the models were trained using dose calculations of phantom slabs generated for the problem in pairs of inputs (doses without magnetic field) and targets (doses with magnetic field). Once trained, the models were evaluated and compared in various aspects. The evidence gathered suggests that the vanilla HDUnet model can learn to generate better dose predictions than the generative model. However, in terms of the resulting dose distributions, the samples generated from the Dose2Dose are as likely to belong to the target dose calculation distribution as those of the vanilla HDUnet. The results contain errors of considerable magnitude, and do not accomplish clinical suitability tests. / I denna avhandling har problemet med att förutsäga full dosfördelning från en delvis modellerad dosberäkning tagits upp. Två lösningar studerades: ett vanilla HDUnet och ett betingat generativt nätverk (CGAN) med HDUnet som generator. CGAN -metoden var en 3D-version av Pix2Pix [1] för översättning av bild till bild med namnet Dose2Dose. Forskningsfrågan som detta projekt tog upp var om Dose2Dose kan lära sig mer effektiva dostransformationer än vanilla HDUnet. För att svara på detta tränades modellerna med hjälp av parvisa dosberäkningar, i indata (doser utan magnetfält) och mål (doser med magnetfält).. När de var tränade utvärderades modellerna och jämfördes i olika aspekter. De samlade bevisen tyder på att Vanilla HDUnet -modellen kan lära sig att generera bättre dosförutsägelser än den generativa modellen. När det gäller de resulterande dosfördelningarna är emellertid de prover som genererats från Dose2Dose lika sannolikt att tillhöra måldosberäkningsfördelningen som de för vanilla HDUnet. Resultaten innehåller stora storleksfel och uppfyller inte kraven för klinisk tillämpbarhet.

GATA1 and KLF1 are transcription factors that regulate genes which are important for the development of erythroid cells. The GATA1 transcriptional co-factor FOG1 has been shown to be essential in a wide range of GATA1 dependent cellular functions. Here we tried to understand the diverse mechanisms by which GATA1 and KLF1 recognize their binding sites, how the GATA1 recognition mechanisms are affected by complexation with either FOG1 or KLF1 and how the GATA1 recognition mechanisms affect the transcriptional regulation of the erythroid differentiation. We profiled the DNA binding specificities/affinities of a GATA1 fragment (mGATA1NC), that contains only the two DNA binding domains (N-terminal and C-terminal Zn finger), and the DNA binding specificities/affinities of a KLF1 fragment (mKLF1257-358), that contains the three DNA binding domains, using a novel methodology that combines EMSA with high throughput sequencing (EMSA-seq (Wong et al., 2011a)). We also profiled the DNA binding specificities of the C-terminal Zn finger of GATA1 alone (mGATA1C), the wt-mGATA1, the wt-mGATA1/wt-mFOG1 complex and the mGATA1NC/mKLF1257-358 complex. At first, we confirmed that the N-terminal Zn finger of GATA1 has a strong preference for the “GATC” motif, whereas the C-terminal Zn finger of GATA1 has a strong preference for the “GATA” motif. Next, we found that in the mGATA1NC, both DNA binding domains can bind simultaneously a wide range of different positional combinations of the co-occurring “GATA” and “GATC” motifs, on the same DNA sequence. The wt-mGATA1 did not show the ability to bind in the same co-occurring motifs implying an effect of the non-DNA binding domains of the protein in the regulation of its DNA binding specificities. On the contrary, complexation of wt-mGATA1 with the wt-mFOG1 partially restored its ability to bind in a now limited range of different positional combinations of the co-occurring “GATA” and “GATC” motifs, on the same DNA sequence. Similar observations were made for other pairs of GATA1 N-terminal and C-terminal Zn finger specific motifs. We then projected the GATA1 DNA binding specificities/affinities in vivo and we classified the GATA1 ChIP-seq peaks in low, medium or high affinity based on the number of the GATA1 motifs. We noticed that high affinity GATA1 ChIP-seq peaks tend to appear in regions with low nucleosome occupancy. We also noticed that GATA1 ChIP-seq peaks in the enhancer regions are usually high affinity whereas GATA1 ChIP-seq peaks in the proximal promoter regions are usually low affinity. Additionally, we observed that high affinity GATA1 ChIP-seq peaks are usually found in regions with increased levels of H3K4me2 and are associated with a higher decrease in the H3K4me3 levels on the TSS of the nearby genes. None of these GATA1 related in vivo observations were found for the KLF1 ChIP-seq positions. These findings significantly advance our understanding of the DNA binding properties of GATA1, KLF1 and their complexes and give an insight on the importance of the GATA1 DNA binding affinities in the regulation of the erythroid transcriptional program. Overall the work establishes an experimental and analytical framework to investigate how transcriptional co-factors can change the DNA binding specificities of specific transcription factors and how integration of the transcription factor DNA binding affinities with in vivo data can give novel insights into the transcriptional regulation.

In addition to a central circadian clock in the suprachiasmatic nucleus (SCN), zebrafish (Danio rerio) have local clock systems in their peripheral tissues. These peripheral tissues express a complement of clock genes that can be synchronized with the 24 h light/dark cycle and thus may be entrained by light. To date, teleost multiple tissue (tmt) opsin identified from Fugu rubripes and Danio rerio is the only opsin that has been proposed as a candidate to mediate this cellular photoentrainment (Moutsaki et al., 2003). Here we report the discovery of a multigene family of tmt opsins found not only in the teleost fishes, but in vertebrates,including amphibians, birds, reptiles, and some mammals. Phylogenetic analysis demonstrated that this gene family consists of three main classes, tmtI, tmtII and tmtIII, with each duplicating further to give two paralogues in the zebrafish genome. Their predicted amino acid sequences contain most of the characteristic features for the function of a photopigment opsin, as well as seven transmembrane segments indicative of a G protein coupled receptor (GPCR) superfamily. Significantly, reverse transcription polymerase chain reaction (RT-PCR) reveals that the tmt opsin genes in zebrafish are both temporally and spatially regulated. To investigate if these tmt photopigments mediate light-activated currents in cells, each opsin was expressed in vitro and the responses characterised by calcium imaging, whole-cell patch clamp electrophysiology, UV-Vis spectrophotometric analysis, and bioluminescence reporter assay. Collectively, these data suggest that some of the opsin photoproteins signal via Gi-type G protein pathway. Interestingly, the spectral analysis obtained shows that most tmt opsins tested are UV-sensitive when reconstituted in vitro with 11-cis and all-trans retinal, indicating an intrinsic bistable dynamics. Using site directed mutagenesis on one of the tmt opsins, tmt10, the potential spectral tuning sites involved in UV detection were tested. As part of this study, tmt opsin cDNAs were isolated from three populations of Mexican tetra (Astyanax mexicanus): surface, Pachon and Steinhardt. This allowed for a direct comparison between the tmt opsins present in the dark adapted species (cavefish) versus those of the light adapted species (zebrafish). It is hoped that the findings from this project will contribute to our understanding of non-visual light detection in fish and the evolution of their non-image forming photoreception.