Finding and tracking multi-density clusters in an online dynamic data stream

The file attached to this record is the author's final peer reviewed version.Change is one of the biggest challenges in dynamic stream mining. From a data-mining perspective, adapting and tracking change is desirable in order to understand how and why change has occurred. Clustering, a form of unsupervised learning, can be used to identify the underlying patterns in a stream. Density-based clustering identifies clusters as areas of high density separated by areas of low density. This paper proposes a Multi-Density Stream Clustering (MDSC) algorithm to address these two problems; the multi-density problem and the problem of discovering and tracking changes in a dynamic stream. MDSC consists of two on-line components; discovered, labelled clusters and an outlier buffer. Incoming points are assigned to a live cluster or passed to the outlier buffer. New clusters are discovered in the buffer using an ant-inspired swarm intelligence approach. The newly discovered cluster is uniquely labelled and added to the set of live clusters. Processed data is subject to an ageing function and will disappear when it is no longer relevant. MDSC is shown to perform favourably to state-of-the-art peer stream-clustering algorithms on a range of real and synthetic data-streams. Experimental results suggest that MDSC can discover qualitatively useful patterns while being scalable and robust to noise

Protein aggregation and calcium dysregulation are hallmarks of familial Parkinson's disease in midbrain dopaminergic neurons

Mutations in the SNCA gene cause autosomal dominant Parkinson’s disease (PD), with loss of dopaminergic neurons in the substantia nigra, and aggregation of α-synuclein. The sequence of molecular events that proceed from an SNCA mutation during development, to end-stage pathology is unknown. Utilising human-induced pluripotent stem cells (hiPSCs), we resolved the temporal sequence of SNCA-induced pathophysiological events in order to discover early, and likely causative, events. Our small molecule-based protocol generates highly enriched midbrain dopaminergic (mDA) neurons: molecular identity was confirmed using single-cell RNA sequencing and proteomics, and functional identity was established through dopamine synthesis, and measures of electrophysiological activity. At the earliest stage of differentiation, prior to maturation to mDA neurons, we demonstrate the formation of small β-sheet-rich oligomeric aggregates, in SNCA-mutant cultures. Aggregation persists and progresses, ultimately resulting in the accumulation of phosphorylated α-synuclein aggregates. Impaired intracellular calcium signalling, increased basal calcium, and impairments in mitochondrial calcium handling occurred early at day 34–41 post differentiation. Once midbrain identity fully developed, at day 48–62 post differentiation, SNCA-mutant neurons exhibited mitochondrial dysfunction, oxidative stress, lysosomal swelling and increased autophagy. Ultimately these multiple cellular stresses lead to abnormal excitability, altered neuronal activity, and cell death. Our differentiation paradigm generates an efficient model for studying disease mechanisms in PD and highlights that protein misfolding to generate intraneuronal oligomers is one of the earliest critical events driving disease in human neurons, rather than a late-stage hallmark of the disease

Biochemical characterisation of Parkinson's disease models

Parkinson’s disease (PD) is the second most common neurodegenerative disorder. The exact molecular mechanism of disease remains unclear. Several factors are proposed to play part including, but not limited to, decreased activity of mitochondrial complex I and lysosomal glucocerebrosidase enzymes and disrupted cellular antioxidant defence and lysosomal acidification. In addition, there is growing support for a role of organelle crosstalk between mitochondria and lysosome, the disruption of which is proposed to play part in PD pathology. The nature and consequence of this crosstalk remains unclear. The SH-SY5Y neuronal cell line model is commonly used to investigate PD mechanisms and potential therapeutics. However, functional analysis of the suitability of the cell line in its proliferative state or the necessity for differentiation remains unclear. Furthermore, iPSC-derived dopaminergic neurons are another commonly used model for PD and related diseases however, validating their functional dopamine metabolism is important to determine disease mechanism and test potential therapeutics. In this thesis, a host of biochemical tools, including HPLC measurement of neurotransmitter metabolites and enzyme activity assays, were used to elucidate the aforementioned ambiguities. The findings demonstrate that although there are similarities between proliferative and differentiated phenotypes of SH-SY5Y cells, there are also significant differences. Notably, the rate of dopamine turnover and the activity of lysosomal glucocerebrosidase were significantly higher in differentiated SH-SY5Y cells. In contrast, mitochondrial electron transport chain complexes’ activities were similar between the two phenotypes, despite a significant difference in mitochondrial content. Therefore, care should be taken when choosing either phenotype as a PD model. In addition, 4the findings demonstrate that inhibition of either mitochondrial complex I or lysosomal glucocerebrosidase affect both the ratio of pro-cathepsin D/cathepsin D protein expression and enzyme activity. Cathepsin D is one of the most ubiquitous lysosomal enzymes, the state of which can be used as reflection of the degree of lysosomal acidification. This shines a light on the potential involvement of both lysosomal glucocerebrosidase and mitochondrial complex I in maintenance of lysosomal acidification. This could be a consequence of a more dynamic crosstalk between mitochondria and lysosomes than previously thought. Moreover, the work presented provides a method for validation of the dysfunctional dopamine metabolism in iPSC derived dopaminergic neuronal disease models for aromatic amino acid decarboxylase deficiency and PD patients carrying mutations in PINK1. In addition, it provides a proof of concept for the effectiveness of both lentivirus-based gene therapy and levodopa treatment to restore dopamine metabolism in aromatic amino acid decarboxylase deficiency