High surface sensitivity and lateral resolution imaging make Time-of-Flight SecondaryIon Mass Spectrometry (ToF-SIMS) a unique and powerful tool for biologicalanalysis. Many of these biological systems, including drug-cell interactions, requireboth the identification and location of specific chemicals. ToF-SIMS, used in imagingmode, is making great strides towards the goal of single cell and tissue analysis. The experiments, however, result in huge volumes of data. Here advanced computationalapproaches employing sophisticated techniques to convert these data intoknowledge are introduced. This thesis aims to produce a framework for data analysis, integrating novel algorithms,image analysis and 3D visualisation. New schema outlined in this thesisaddress the issues of the immense size of 3D image stacks and the complexity containedwithin the enormous wealth of information in ToF-SIMS data. To deal with the issues of size and complexity of ToF-SIMS data, new techniquesto processing image data are investigated. Automated compression routines for ToF-SIMSimages using a peak picking routine tailored for ToF-SIMS are evaluated. Newuser friendly GUIs capable of processing and visualising very large image stacks areintroduced as part of a tool-kit designed to streamline the process of multivariateanalysis and image processing. Along with this two well known classification routines,namely AdaBoost and SVMs, are also applied to ToF-SIMS data of severalbacterial strains to test their ability to classify SIMS data accurately. This thesispresent several new approaches to data processing and interpretation of ToF-SIMSdata.

In this study, Fourier Transform Infrared Micro-Spectroscopy (FT-IRMS, or IRMS), coupled with multivariate analysis is shown to be an effective tool to further investigate the differentiation of human pluripotent stem cells and monitor the alternative affects different retinoid compounds have on the induction of differentiation. Stem cells and differentiated phenotypes being distinguished based on the spectral fingerprint recorded and not through the addition of fluorescent or magnetic biomarkers. IRMS detected differences between cell populations as early as 3 days of retinoid compound treatment. Populations of stem cells treated with different retinoid compounds could easily be distinguished from one another during the early stages of cell differentiation, demonstrating the potential of that IRMS technology as a sensitive screening technique to monitor the status of the stem cell phenotype and progression of differentiation along alternative pathways in response to different compounds. The study also investigates some of the problems with intrinsic resonant Mie scattering (RMieS), produced when recording IR spectra from single cells in air. Some single cell spectra recorded containing RMieS were not corrected properly when using the RMieS-EMSC scattering correction and typical correction parameter options; correction of such spectra using the RMieS-EMSC algorithm resulted in the production of cell spectra with odd absorption band structures after correction. This study demonstrates that alternative correction parameter options for the RMieS-EMSC correction can successfully overcome this problem. Early experimental results show that that IRMS is a sensitive technique capable of capturing discrete molecular changes of pluripotent stem cells as they are induced to differentiate, without the need for expensive and potentially damaging exogenous labels. Studies in the literature predominately use IRMS to investigate chemically fixed cells, however, this is a form of cell death and once cells are fixed they become un-viable. Critically, cell phenotype should be understood from living cells with the biochemistry being maintained after information is recorded so that single cells can retain their biological function. IR spectroscopy has the potential to record spectra from living cells when coupled with the micro-devices to provide a suitable water barrier for IR spectroscopic investigations. This study demonstrates that cell spectra can be recorded from cells in an aqueous environment, with a new processing method being described to accurately remove the water buffer contributions contained within raw single cell spectra recorded in an aqueous environment. Therefore, highlighting the potential of IRMS for the screening of living cells, potentially identifying stem cells from other cell phenotypes based on their biochemical make-up and without cellular destruction.

The analysis of mixtures is a subject that spans several different analytical techniques. In NMR, a powerful technique for this analysis is Diffusion-Ordered NMR Spectroscopy (DOSY), in which signals from different chemical species can be distinguished by their different diffusion coefficients. DOSY NMR allows an analysis of mixture components and their interactions in a non-invasive way and is proving to be an accurate and time effective method for looking at mixtures.An in-depth analysis of DOSY NMR is presented using the commercial mixture “monoacetin”. The chemically cognate species in this mixture produce complex and overlapping multiplet signals in 1H NMR that are difficult to assign and interpret. A previous analysis of this mixture used 1H NMR together with Liquid Chromatography (LC) and Gas Chromatography (GC) to identify the components present, but failed to provide complete assignments of all the signals. Here, the possibility of using DOSY as an alternative to hyphenated techniques is examined, and it is shown that a full analysis of the spectrum of “monoacetin” is possible with careful selection of experimental parameters and processing techniques, without recourse to chromatography. DOSY NMR can be ineffective when signals overlap and/or diffusion coefficients are similar. Many methods have been proposed to overcome these problems, and some of these are presented here. In order to increase resolving power, it is possible to gather further information about a mixture and incorporate this into diffusion experiments as another dimension. This creates a 3D dataset that can be analysed using a multiway method, such as PARAFAC, to extract the component spectra. This method is explored for the mixture “monoacetin” that has been partially separated by high-performance liquid chromatography. Resolution of two out of four components was achieved from poor HPLC separation; the decomposition obtained the component spectra, diffusional decay and HPLC elution profile for these components. Improved HPLC separation should result in further resolution.Diffusion coefficients of different mixture species can be manipulated by changing the matrix in which they diffuse: Matrix-Assisted DOSY (MAD). Previous techniques have involved either improving resolution in the diffusion domain or aiming to improve resolution in chemical shift. A method is presented here that simultaneously addresses both problems in a chemically-selective way, using lanthanide shift reagents. The chemically-selective binding of the LSR to mixture components can both enhance chemical shift dispersion and increase diffusion resolution in DOSY. This neatly deals with the two main drawbacks of the DOSY experiment, and is demonstrated using a mixture of an alkane, alcohol and aldehyde. The manipulation of a molecule’s electrostatic charge through pH control has been investigated, where small ions with a high charge density would be highly solvated, resulting in a change in D. The effect, however, was not measurable and so the indirect effect of pH on the interaction of charged species with the cationic micelle CTAB is presented, where an increase in resolution between of mixture of aspirin and salicylic acid is achieved.Although DOSY NMR is a powerful tool for mixture analysis, in recent years it has been used for studying molecular interactions. An example of this is presented here where species aggregate under specific conditions, a process identified by DOSY NMR.

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Magnetic microparticles have seen increasing interest in (bio)chemical processes in recent years due to their various surface functionalities, high surface-to-volume ratio, small sizes, and ease of manipulation via magnetic fields. However, conventional reactions and assays that use magnetic particles as solid supports are typically performed in multi-step procedures that require consecutive reaction and washing steps. While offering high capture efficiencies, these are batch processes that, due to the consecutive steps required, are typically time-consuming and laborious. Their incorporation into microfluidic devices has brought about benefits including finer control over the movement of particles and reagent/sample solutions, as well as the ability to place a magnet closer to the area of interest. However, most instances of on-chip magnetic particle based procedures rely on trap-and-release methodology, essentially requiring the same stepwise routine as with conventional systems. A method of reducing these inefficiencies is to perform the reaction or separation in continuous flow, thereby allowing continuous sample introduction and analysis of the process in rapid times, and with minimal reagent consumption and waste production.Two methods of performing continuous flow procedures on single particles in microfluidic devices via the application of magnetic forces were investigated: 1) the use of magnetic microparticles as mobile solid supports for performing rapid separations, reactions, and immunoassays via magnetic attraction, and 2) the use of diamagnetic repulsion forces for performing similar procedures on non-magnetic particles, with a view to the label-free processing of diamagnetic species such as polymer particles and biological cells, based on their intrinsic properties.For the magnetic attraction experiments, a study into the effect of temperature on magnetic particle deflection behaviour and separations was performed, whereupon it was found that an increased temperature of the system yielded increased deflection distances and separation resolution due to the reduced viscous drag. This was followed by several investigations into the deflection of particles through laminar flow streams containing alternating reagents and washing buffers for performing multistep reactions and assays. The setup was used to demonstrate amide bond formation and polyelectrolyte deposition in continuous flow, before being used to detect clinically relevant levels (5 and 10�g mL-1) of the inflammatory biomarker, C-reactive protein. Thus, these findings show great potential for rapid, continuous processing of particles for a number of chemical and biological applications, as well as in clinical diagnostics.For the diamagnetic repulsion studies, diamagnetic polystyrene particles were suspended in paramagnetic media and deflected away from a magnetic field in continuous flow. The effect of particle size and the magnetic susceptibility of the paramagnetic media on particle deflection were investigated using high magnetic fields, where it was found that larger particles in a medium with higher susceptibility yielded the greatest deflection. This work was extended via a proof-of-principle setup in which polystyrene particles were repelled out of a reagent stream and into a buffer stream using permanent magnets, with a view to performing continuous flow reactions through laminar flow reagent and washing buffer streams, akin to those achieved via magnetic attraction. Finally, flow focussing of polystyrene particles and label-free cells was achieved via diamagnetic repulsion forces applied by permanent magnets, demonstrating the ability to manipulate cells in continuous flow by magnetic forces based on their intrinsic properties. This work could be applied to the label-free processing of particles and cells for separations, reactions, and assays.

To construct a spectroscopic multivariate calibration model, a set of representative mixture spectra (independent variables) and the corresponding reference values for the property of interest (dependent variables) must be obtained. For a dynamic system such as a batch or semi-batch chemical reaction, creating such a data set may be very difficult or extremely time consuming. It may not be possible to create synthetic mixtures because reaction between the various reactants may occur. If the reaction proceeds via a reactive intermediate or affords a reactive product, isolated reference standards of those species may not be available. Reactions in industry are often heterogeneous and highly concentrated; sampling the batch throughout the course of the reaction for off-line analysis can be problematic and therefore introduce significant error into measured reference values. An alternative approach that combined Self-Modelling Curve Resolution (SMCR) methods and Partial Least Squares (PLS) to construct a quantitative model using only minimal reference data was implemented. The objective was to construct a quantitative calibration model to allow real-time in-situ UV/ATR measurements to be used to determine the end-point of a chlorination reaction. Difficult reaction sampling conditions and the absence of isolated reference standards for the product and reactive intermediate required the method to be developed using only a few key reference measurements.

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