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Background: Neurofibrillary tangles (NFTs) is one of the two ‘hallmarks’ of Alzheimer’s disease (AD). The main constitute of these tangles are known as the paired helical filaments (PHFs), which are essentially abnormal aggregate of microtubule associated protein Tau. It has been known for many years that the hyper-phosphorylation of protein Tau is a persistent feature in NFTs. However, whether hyper-phosphorylation of Tau is a cause or an effect to aggregation remains elusive. Mass spectrometry can now serve as an alternative to immunoblotting analysis for post translational modifications (PTM) study. Results: We developed a mass spectrometry method targeting on Tau protein for phosphorylation study. For a decent MS characterisation run, HEK 293 cells confluent in 5-10 plates (50 cm2) are required to be fed to the sample processing procedure. Typically, it takes 4-6 days to prepare the cells into MS samples. The targeting approach was able to discover peptides less intense by two orders of magnitude than that spotted using the general discovery method. The application of the targeted method on the soluble Tau recovered from HEK 293 cells allowed the solid discovery of three additional Tau phosphopeptide (only one phosphopeptide was discovered previously). Furthermore, for the development of the MS targeted method and high purity MS sample preparation, an efficient recombinant Tau protein production (in E.coli) protocol and a purification workflow for phosphorylated and untagged soluble/functional Tau protein (from HEK 293 cell line) was developed respectively. Conclusion: The Tau protein targeted MS method allows solid identification of additional phosphopeptides at two orders of magnitude lower peak intensity. The compatible purification protocol for soluble Tau could be applied to mammalian cells and tissue that expresses wild type and untagged Tau protein.

The simultaneous solution of the optimal process variables and optimal processing materials for a separation system is considered in this work. The processing materials (or molecules) may include, amongst others, reaction medium solvents, catalysts and mass separating agents. In this thesis, the processing materials to be designed are restricted to pure component solvents that act as mass separating agents. The design of fluid-fluid separation systems at steady state is considered in this work. In the first part of the thesis, the process topology is fixed and the process variables are continuous whereas the molecular variables, used to describe the solvent, are discrete. The computer aided molecular and process design problem (CAMPD) is a challenging mixed integer nonlinear programming problem (MINLP). A deterministic optimization algorithm tailored to the CAMPD of separation systems is proposed. Novel tests are embedded within an iterative MINLP solution framework. The tests may eliminate infeasible regions of both the molecular and process domain. The algorithm is applied to a case study of separation of carbon dioxide and methane. In the second part of the thesis, the scenario where the process variables are both continuous and discrete is considered. Chemical process synthesis is the activity of determining the optimal process units and their connectivity in a process. Process synthesis is a highly combinatorial problem which is challenging, even with fixed material decisions. A formulation for process synthesis problems is presented which addresses numerical singularities that are encountered when a process unit is not selected. The computer aided molecular and process synthesis (CAMPS) problem is considered next where the degrees of freedom include material and process synthesis decisions. An algorithm for CAMPS is developed by extending the CAMPD algorithm. A CAMPS case study of separation of butanol and water is modelled using the process synthesis formulation developed in this thesis. The tests can eliminate infeasible portions of the molecular domain and both continuous and discrete process domains. Both the CAMPD and CAMPS algorithms proposed here avert evaluations of infeasible primal problems and enhance convergence to solutions of challenging design problems.