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AIM: To investigate the expression of E-cadherin, a major host cell receptor for Listeria monocytogenes (LM) internalin A, in the ruminant nervous system and its putative role in brainstem invasion and intracerebral spread of LM in the natural disease. METHODS: Immunohistochemistry and double immunofluorescence was performed on brains, cranial nerves and ganglia of ruminants with and without natural LM rhombencephalitis using antibodies against E-cadherin, protein gene product 9.5, myelin-associated glycoprotein and LM. RESULTS: In the ruminant brain, E-cadherin is expressed in choroid plexus epithelium, meningothelium and restricted neuropil areas of the medulla, but not in the endothelium. In cranial nerves and ganglia, E-cadherin is expressed in satellite cells and myelinating Schwann cells. Expression does not differ between ruminants with or without listeriosis and does not overlap with the presence of microabscesses in the medulla. LM is observed in phagocytes, axons, Schwann cells, satellite cells and ganglionic neurones. CONCLUSION: Our results support the view that the specific ligand-receptor interaction between LM and host E-cadherin is involved in the neuropathogenesis of ruminant listeriosis. They suggest that oral epithelium and Schwann cells expressing E-cadherin provide a port of entry for free bacteria offering a site of primary intracellular replication, from where the bacterium may invade the axonal compartment by cell-to-cell spread. As E-cadherin expression in the ruminant central nervous system is weak, only very locally restricted and not related to the presence of microabscesses, it is likely that further intracerebral spread is independent of E-cadherin and relies primarily on axonal spread.

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Recent optimizations of NMR spectroscopy have focused their attention on innovations in new hardware, such as novel probes and higher field strengths. Only recently has the potential to enhance the sensitivity of NMR through data acquisition strategies been investigated. This thesis has focused on the practice of enhancing the signal-to-noise ratio (SNR) of NMR using non-uniform sampling (NUS). After first establishing the concept and exact theory of compounding sensitivity enhancements in multiple non-uniformly sampled indirect dimensions, a new result was derived that NUS enhances both SNR and resolution at any given signal evolution time. In contrast, uniform sampling alternately optimizes SNR (t < 1.26T2) or resolution (t~3T2), each at the expense of the other. Experiments were designed and conducted on a plant natural product to explore this behavior of NUS in which the SNR and resolution continue to improve as acquisition time increases. Possible absolute sensitivity improvements of 1.5 and 1.9 are possible in each indirect dimension for matched and 2x biased exponentially decaying sampling densities, respectively, at an acquisition time of ¿T2. Recommendations for breaking into the linear regime of maximum entropy (MaxEnt) are proposed. Furthermore, examination into a novel sinusoidal sampling density resulted in improved line shapes in MaxEnt reconstructions of NUS data and comparable enhancement to a matched exponential sampling density. The Absolute Sample Sensitivity derived and demonstrated here for NUS holds great promise in expanding the adoption of non-uniform sampling.

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Transient Diode Laser Absorption Spectroscopy (TDLAS) was used to perform vibrational state population studies of the CO2 product from the hyperthermal reaction between C2H4 and O(3P) at room temperature using O3 as the O-atom precursor. Photodissociation of O3 using a frequency quadrupled Q-switch Nd:YAG laser pulse at 266 nm produced O(3P) atoms at high velocities which subsequently reacted with C2H4, producing several primary and secondary products including CO2. The CO2 product was detected using high-resolution TDLAS under five unique sets of reaction conditions. The vibrational distribution of the CO2 product did not follow a Boltzmann distribution at all five sets of conditions. The experiments showed a distribution in which there was a surprisingly high population in the (1000) (symmetric stretching) state compared with the other states probed, all of which contained bend excitation. In general, the CO2 population in the (1000) state was about 15-20% more populated than the Boltzmann distribution predicts. A possible explanation for this result may lie in the mechanism of CO2 evolution from the C2H4 + O(3P) reaction.

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When different markers are responsive to different aspects of a disease, combination of multiple markers could provide a better screening test for early detection. It is also resonable to assume that the risk of disease changes smoothly as the biomarker values change and the change in risk is monotone with respect to each biomarker. In this paper, we propose a boundary constrained tensor-product B-spline method to estimate the risk of disease by maximizing a penalized likelihood. To choose the optimal amount of smoothing, two scores are proposed which are extensions of the GCV score (O'Sullivan et al. (1986)) and the GACV score (Ziang and Wahba (1996)) to incorporate linear constraints. Simulation studies are carried out to investigate the performance of the proposed estimator and the selection scores. In addidtion, sensitivities and specificities based ona pproximate leave-one-out estimates are proposed to generate more realisitc ROC curves. Data from a pancreatic cancer study is used for illustration.