Design of a Single AAV Vector for Coexpression of TH and GCH1 to Establish Continuous DOPA Synthesis in a Rat Model of Parkinson's Disease.

Preclinical efficacy of continuous delivery of 3,4-dihydroxyphenylalanine (DOPA) with adeno-associated viral (AAV) vectors has recently been documented in animal models of Parkinson's disease (PD). So far, all studies have utilized a mix of two monocistronic vectors expressing either of the two genes, tyrosine hydroxylase (TH) and GTP cyclohydrolase-1 (GCH1), needed for DOPA production. Here, we present a novel vector design that enables efficient DOPA production from a single AAV vector in rats with complete unilateral dopamine (DA) lesions. Functional efficacy was assessed with drug-induced and spontaneous motor behavioral tests where vector-treated animals showed near complete and stable recovery within 1 month. Recovery of motor function was associated with restoration of extracellular DA levels as assessed by online microdialysis. Histological analysis showed robust transgene expression not only in the striatum but also in overlying cortical areas. In globus pallidus, we noted loss of NeuN staining, which might be due to different sensitivity in neuronal populations to transgene expression. Taken together, we present a single AAV vector design that result in efficient DOPA production and wide-spread transduction. This is a favorable starting point for continued translation toward a therapeutic application, although future studies need to carefully review target region, vector spread and dilution with this approach

A General Chemical Method to Regulate Protein Stability in the Mammalian Central Nervous System

SummaryThe ability to make specific perturbations to biological molecules in a cell or organism is a central experimental strategy in modern research biology. We have developed a general technique in which the stability of a specific protein is regulated by a cell-permeable small molecule. Mutants of the Escherichia coli dihydrofolate reductase (ecDHFR) were engineered to be degraded, and, when this destabilizing domain is fused to a protein of interest, its instability is conferred to the fused protein resulting in rapid degradation of the entire fusion protein. A small-molecule ligand trimethoprim (TMP) stabilizes the destabilizing domain in a rapid, reversible, and dose-dependent manner, and protein levels in the absence of TMP are barely detectable. The ability of TMP to cross the blood-brain barrier enables the tunable regulation of proteins expressed in the mammalian central nervous system

Novel AAV-based rat model of forebrain synucleinopathy shows extensive pathologies and progressive loss of cholinergic interneurons.

Synucleinopathies, characterized by intracellular aggregation of α-synuclein protein, share a number of features in pathology and disease progression. However, the vulnerable cell population differs significantly between the disorders, despite being caused by the same protein. While the vulnerability of dopamine cells in the substantia nigra to α-synuclein over-expression, and its link to Parkinson's disease, is well studied, animal models recapitulating the cortical degeneration in dementia with Lewy-bodies (DLB) are much less mature. The aim of this study was to develop a first rat model of widespread progressive synucleinopathy throughout the forebrain using adeno-associated viral (AAV) vector mediated gene delivery. Through bilateral injection of an AAV6 vector expressing human wild-type α-synuclein into the forebrain of neonatal rats, we were able to achieve widespread, robust α-synuclein expression with preferential expression in the frontal cortex. These animals displayed a progressive emergence of hyper-locomotion and dysregulated response to the dopaminergic agonist apomorphine. The animals receiving the α-synuclein vector displayed significant α-synuclein pathology including intra-cellular inclusion bodies, axonal pathology and elevated levels of phosphorylated α-synuclein, accompanied by significant loss of cortical neurons and a progressive reduction in both cortical and striatal ChAT positive interneurons. Furthermore, we found evidence of α-synuclein sequestered by IBA-1 positive microglia, which was coupled with a distinct change in morphology. In areas of most prominent pathology, the total α-synuclein levels were increased to, on average, two-fold, which is similar to the levels observed in patients with SNCA gene triplication, associated with cortical Lewy body pathology. This study provides a novel rat model of progressive cortical synucleinopathy, showing for the first time that cholinergic interneurons are vulnerable to α-synuclein over-expression. This animal model provides a powerful new tool for studies of neuronal degeneration in conditions of widespread cortical α-synuclein pathology, such as DLB, as well an attractive model for the exploration of novel biomarkers

Integrated economic and environmental assessment of waste policy instruments

The need for new policy instruments supporting the on-going transition from end-of-pipe waste treatment to resource management has been recognized in European policy. Instruments need to be carefully assessed before implementation to promote the desired changes and avoid problem shifting. Mathematical models may assist policy makers in such assessments. This paper presents a set of soft-linked models for assessing the economic and environmental impacts of policy instruments for both the prevention and management of waste and discusses its strengths and limitations. Consisting of (1) a macro-economic model, (2) a systems engineering model for waste management and (3) a life cycle assessment model for waste management, the set is primarily suited to assessing market-based instruments and environmental regulations. Considerable resources were needed for developing and using the set, and there are clear limits as to what can be addressed. However, if only one of the models had been used, neither the range of instruments nor the scope of impacts would have been possible to cover. Furthermore, soft-linked models allow many disciplines to contribute within one harmonized framework. Such integrated assessments may become increasingly useful for continuing the implementation of policy for sustainable governance of society’s material resources

Socioeconomic Status Is Not Related with Facial Fluctuating Asymmetry: Evidence from Latin-American Populations

The expression of facial asymmetries has been recurrently related with poverty and/or disadvantaged socioeconomic status. Departing from the developmental instability theory, previous approaches attempted to test the statistical relationship between the stress experienced by individuals grown in poor conditions and an increase in facial and corporal asymmetry. Here we aim to further evaluate such hypothesis on a large sample of admixed Latin Americans individuals by exploring if low socioeconomic status individuals tend to exhibit greater facial fluctuating asymmetry values. To do so, we implement Procrustes analysis of variance and Hierarchical Linear Modelling (HLM) to estimate potential associations between facial fluctuating asymmetry values and socioeconomic status. We report significant relationships between facial fluctuating asymmetry values and age, sex, and genetic ancestry, while socioeconomic status failed to exhibit any strong statistical relationship with facial asymmetry. These results are persistent after the effect of heterozygosity (a proxy for genetic ancestry) is controlled in the model. Our results indicate that, at least on the studied sample, there is no relationship between socioeconomic stress (as intended as low socioeconomic status) and facial asymmetries

Repairing the brain : Gene therapy

In vivo gene therapy for neurodegenerative disorders has turned out to be a formidable challenge. It is a field not much older than twenty years, but we were many who would have predicted a much easier path towards the clinic using this treatment modality. For Parkinson's disease patients, this has meant a frustrating wait, seeing many promising therapies being forgotten after a few pre-clinical proof-of-concept studies. The reasons for this are both scientific and economical. However, this is slowly but surely changing and over the next two decades we will see a very exciting development in this field. In a foreseeable future, gene therapy will be a very natural component of many clinical therapies, not least in Parkinson's disease

Expression of Multiple Functional RNAs or Proteins from One Viral Vector.

In this chapter, we will cover the available design choices for enabling expression of two functional protein or RNA sequences from a single viral vector. Such vectors are very useful in the neuroscience-related field of neuronal control and modulation, e.g., using optogenetics or DREADDs, but are also desirable in applications of CRISPR/Cas9 in situ genome editing and more refined therapeutic approaches. Each approach to achieving this combined expression has its own strengths and limitations, which makes them more or less suitable for different applications. In this chapter, we describe the available alternatives and provide tips on how they can be implemented

Gene therapy by enzyme replacement for Parkinson’s disease Optimization of continuous DOPA delivery and development of a candidate vector for clinical application

The introduction of L-DOPA pharmacotherapy revolutionized the treatment of Parkinson’s disease close to fifty years ago. Before the discovery of dopamine as a neurotransmitter and its involvement in the disease, these patients had very little aid from medication and were bound to a life without movement. The dopamine neurons in the midbrain are a key player in the circuitry that is responsible for the initiation and control of movement. When the loss of dopamine neurons and especially their projection into the forebrain, becomes severe, the patients start to experience rigidity, postural instability and a gradual loss of the ability to move. L-DOPA is converted in the brain into dopamine and is very efficient at providing symptomatic relief. Unfortunately, within five to ten years, most patients start to experience side-effects, mainly the emergence of involuntary movements, so called dyskinesias. With time, the dose of L-DOPA needed to induce dyskinesias decreases to such an extent that the therapeutic window could be completely lost. These side-effects are thought to develop due to the intermittent, pulsatile delivery method of the drug. In this thesis, I have worked on a new method of providing a continuous DOPA production in the brain using adeno-associated viral vector mediated gene therapy. By providing the genes tyrosine hydroxylase and GTP cyclohydrolase 1 which code for the two enzymes required for DOPA production, we have been able to prevent the emergence of dyskinesias but also to provide symptomatic relief far more efficiently than the peripheral L-DOPA administration in research animals. A second goal of the thesis has been to pave the way to a clinical trial of these viral vectors for application in Parkinson’s disease. Towards this goal, I have investigated the role of the serotonergic system for the efficacy of the therapy and explored the usefulness of this treatment in advanced stage disease. Moreover, I have designed a novel viral vector construct that can mediate the expression of both genes from a single vector, and studied its effect in both rodents and monkeys. Based on the experimental studies presented in this thesis, I conclude that DOPA replacement by gene therapy has a true potential as a treatment for Parkinson’s disease patients at all stages of the disease and that the next step towards a clinical trial should be initiated

Automatic evaluation of breast density in mammographic images

The goal of this master thesis is to develop a computerized method for automatic estimation of the mammographic density of mammographic images from 5 different types of mammography units.   Mammographic density is a measurement of the amount of fibroglandular tissue in a breast. This is the single most attributable risk factor for breast cancer; an accurate measurement of the mammographic density can increase the accuracy of cancer prediction in mammography. Today it is commonly estimated through visual inspection by a radiologist, which is subjective and results in inter-reader variation.   The developed method estimates the density as a ratio of #pixels-containing-dense-tissue over #pixels-containing-any-breast-tissue and also according to the BI-RADS density categories. To achieve this, each mammographic image is: corrected for breast thickness and normalized such that some global threshold can separate dense and non-dense tissue. iteratively thresholded until a good threshold is found.  This process is monitored and automatically stopped by a classifier which is trained on sample segmentations using features based on different image intensity characteristics in specified image regions. filtered to remove noise such as blood vessels from the segmentation. Finally, the ratio of dense tissue is calculated and a BI-RADS density class is assigned based on a calibrated scale (after averaging the ratings of both craniocaudal images for each patient). The calibration is based on resulting density ratio estimations of over 1300 training samples against ratings by radiologists of the same images.   The method was tested on craniocaudal images (not included in the training process) acquired with different mammography units of 703 patients which had also been rated by radiologists according to the BI-RADS density classes. The agreement with the radiologist rating in terms of Cohen’s weighted kappa is substantial (0.73). In 68% of the cases the agreement is exact, only in 1.2% of the cases the disagreement is more than 1 class