Multiparameter flow cytometric analysis of C -reactive protein binding to human-derived cell lines and peripheral blood monocytes

C-reactive protein (CRP), a normally occurring human plasma protein may become elevated as much as 1,000 fold during disease states involving acute inflammation or tissue damage. Through its binding to phosphorylcholine in the presence of calcium, CRP has been shown to potentiate the activation of complement, stimulate phagocytosis and opsonize certain microorganisms. Utilizing a flow cytometric functional ligand binding assay I have demonstrated that a monocyte population in human peripheral blood and specific human-derived myelomonocytic cell lines reproducibly bind an evolutionarily conserved conformational pentraxin epitope on human CRP through a mechanism that does not involve its ligand, phosphorylcholine. ^ A variety of cell lines at different stages of differentiation were examined. The monocytic cell line, THP-1, bound the most CRP followed by U937 and KG-1a cells. The HL-60 cell line was induced towards either the granulocyte or monocyte pathway with DMSO or PMA, respectively. Untreated HL-60 cells or DMSO-treated cells did not bind CRP while cells treated with PMA showed increased binding of CRP, similar to U-937 cells. T cell and B-cell derived lines were negative. ^ Inhibition studies with Limulin and human SAP demonstrated that the binding site is a conserved pentraxin epitope. The calcium requirement necessary for binding to occur indicated that the cells recognize a conformational form of CRP. Phosphorylcholine did not inhibit the reaction therefore the possibility that CRP had bound to damaged membranes with exposed PC sites was discounted. ^ A study of 81 normal donors using flow cytometry demonstrated that a majority of peripheral blood monocytes (67.9 ± 1.3, mean ± sem) bound CRP. The percentage of binding was normally distributed and not affected by gender, age or ethnicity. Whole blood obtained from donors representing a variety of disease states showed a significant reduction in the level of CRP bound by monocytes in those donors classified with infection, inflammation or cancer. This reduction in monocyte populations binding CRP did not correlate with the concentration of plasma CRP. ^ The ability of monocytes to specifically bind CRP combined with the binding reactivity of the protein itself to a variety of phosphorylcholine containing substances may represent an important bridge between innate and adaptive immunity. ^

Automated detection of hematological abnormalities through classification of flow cytometric data patterns

Flow Cytometry analyzers have become trusted companions due to their ability to perform fast and accurate analyses of human blood. The aim of these analyses is to determine the possible existence of abnormalities in the blood that have been correlated with serious disease states, such as infectious mononucleosis, leukemia, and various cancers. Though these analyzers provide important feedback, it is always desired to improve the accuracy of the results. This is evidenced by the occurrences of misclassifications reported by some users of these devices. It is advantageous to provide a pattern interpretation framework that is able to provide better classification ability than is currently available. Toward this end, the purpose of this dissertation was to establish a feature extraction and pattern classification framework capable of providing improved accuracy for detecting specific hematological abnormalities in flow cytometric blood data. ^ This involved extracting a unique and powerful set of shift-invariant statistical features from the multi-dimensional flow cytometry data and then using these features as inputs to a pattern classification engine composed of an artificial neural network (ANN). The contribution of this method consisted of developing a descriptor matrix that can be used to reliably assess if a donor’s blood pattern exhibits a clinically abnormal level of variant lymphocytes, which are blood cells that are potentially indicative of disorders such as leukemia and infectious mononucleosis. ^ This study showed that the set of shift-and-rotation-invariant statistical features extracted from the eigensystem of the flow cytometric data pattern performs better than other commonly-used features in this type of disease detection, exhibiting an accuracy of 80.7%, a sensitivity of 72.3%, and a specificity of 89.2%. This performance represents a major improvement for this type of hematological classifier, which has historically been plagued by poor performance, with accuracies as low as 60% in some cases. This research ultimately shows that an improved feature space was developed that can deliver improved performance for the detection of variant lymphocytes in human blood, thus providing significant utility in the realm of suspect flagging algorithms for the detection of blood-related diseases.^

Statistical analysis and optimal classification of blood cell populations using Gaussian distributions

This dissertation develops a new figure of merit to measure the similarity (or dissimilarity) of Gaussian distributions through a novel concept that relates the Fisher distance to the percentage of data overlap. The derivations are expanded to provide a generalized mathematical platform for determining an optimal separating boundary of Gaussian distributions in multiple dimensions. Real-world data used for implementation and in carrying out feasibility studies were provided by Beckman-Coulter. It is noted that although the data used is flow cytometric in nature, the mathematics are general in their derivation to include other types of data as long as their statistical behavior approximate Gaussian distributions. ^ Because this new figure of merit is heavily based on the statistical nature of the data, a new filtering technique is introduced to accommodate for the accumulation process involved with histogram data. When data is accumulated into a frequency histogram, the data is inherently smoothed in a linear fashion, since an averaging effect is taking place as the histogram is generated. This new filtering scheme addresses data that is accumulated in the uneven resolution of the channels of the frequency histogram. ^ The qualitative interpretation of flow cytometric data is currently a time consuming and imprecise method for evaluating histogram data. This method offers a broader spectrum of capabilities in the analysis of histograms, since the figure of merit derived in this dissertation integrates within its mathematics both a measure of similarity and the percentage of overlap between the distributions under analysis. ^

Anticancer activity of 4-N gemcitabine analogues

Gemcitabine (2', 2'-difluoro-2'-deoxycytidine or dFdC) has become a standard chemotherapeutic agent in the treatment of several cellular and solid tumor- related malignancies. Gemcitabine's anti-cancer activity has been attributed to its inhibitory effects on the cell's DNA synthetic machinery resulting in the induction of cell arrest and apoptosis. Despite its broad application, treatment capacity with this drug is limited due to complicated administration schedules stemming from low bioavailability and tumor resistance associated with its rampant intracellular enzymatic inactivation. The aim of this study is to characterize the anti-cancer activity of novel designed and synthesized gemcitabine analogues, that were modified with long alkyl chains at the 4-amino group of the cytosine ring. This study proposes the use of these alternative derivatives of gemcitabine that not only uphold current drug standards for potency, but additionally confer chemical stability against enzymatic inactivation. During screening conducted to identifY prospective gem-analogue candidates, I observed the potent anticancer properties ofthree 4-N modified compounds on MCF-7 breast adenocarcinoma cells. Experiments described here with these compounds referred to as LCO, LCAO, and Gvaldo, evaluate their cytotoxicity on MCF-7 cells at the concentrations of 25flM and 2.5flM, and assess their inhibitory effects on DNA synthesis and cell cycle progression using sulphorhodamine B and bromodeoxyuridine assays as well as flow cytometric analyses, respectively. Among the compounds tested, LCO was shown to be most active inhibitor of DNA synthesis (a=.05; p<.OOl) as reflected as a distinct GO/Gl versus S-phase arrest in the 25flM and 2.5flM treatments, respectively. Together, these experiments provide preliminary evidence for the clinical application of LCO-like gemcitabine derivatives as a novel treatment for breast cancer.

Human Synaptic Plasticity Gene Expression Profile and Dendritic Spine Density Changes in HIV-Infected Human CNS Cells: Role in HIV-Associated Neurocognitive Disorders (HAND)

HIV-associated neurocognitive disorders (HAND) is characterized by development of cognitive, behavioral and motor abnormalities, and occur in approximately 50% of HIV infected individuals. Our current understanding of HAND emanates mainly from HIV-1 subtype B (clade B), which is prevalent in USA and Western countries. However very little information is available on neuropathogenesis of HIV-1 subtype C (clade C) that exists in Sub-Saharan Africa and Asia. Therefore, studies to identify specific neuropathogenic mechanisms associated with HAND are worth pursuing to dissect the mechanisms underlying this modulation and to prevent HAND particularly in clade B infection. In this study, we have investigated 84 key human synaptic plasticity genes differential expression profile in clade B and clade C infected primary human astrocytes by using RT2 Profile PCR Array human Synaptic Plasticity kit. Among these, 31 and 21 synaptic genes were significantly (≥3 fold) down-regulated and 5 genes were significantly (≥3 fold) up-regulated in clade B and clade C infected cells, respectively compared to the uninfected control astrocytes. In flow-cytometry analysis, down-regulation of postsynaptic density and dendrite spine morphology regulatory proteins (ARC, NMDAR1 and GRM1) was confirmed in both clade B and C infected primary human astrocytes and SK-N-MC neuroblastoma cells. Further, spine density and dendrite morphology changes by confocal microscopic analysis indicates significantly decreased spine density, loss of spines and decreased dendrite diameter, total dendrite and spine area in clade B infected SK-N-MC neuroblastoma cells compared to uninfected and clade C infected cells. We have also observed that, in clade B infected astrocytes, induction of apoptosis was significantly higher than in the clade C infected astrocytes. In conclusion, this study suggests that down-regulation of synaptic plasticity genes, decreased dendritic spine density and induction of apoptosis in astrocytes may contribute to the severe neuropathogenesis in clade B infection.

Two-bit pattern analysis for quantitative information flow

Protecting confidential information from improper disclosure is a fundamental security goal. While encryption and access control are important tools for ensuring confidentiality, they cannot prevent an authorized system from leaking confidential information to its publicly observable outputs, whether inadvertently or maliciously. Hence, secure information flow aims to provide end-to-end control of information flow. Unfortunately, the traditionally-adopted policy of noninterference, which forbids all improper leakage, is often too restrictive. Theories of quantitative information flow address this issue by quantifying the amount of confidential information leaked by a system, with the goal of showing that it is intuitively "small" enough to be tolerated. Given such a theory, it is crucial to develop automated techniques for calculating the leakage in a system. ^ This dissertation is concerned with program analysis for calculating the maximum leakage, or capacity, of confidential information in the context of deterministic systems and under three proposed entropy measures of information leakage: Shannon entropy leakage, min-entropy leakage, and g-leakage. In this context, it turns out that calculating the maximum leakage of a program reduces to counting the number of possible outputs that it can produce. ^ The new approach introduced in this dissertation is to determine two-bit patterns, the relationships among pairs of bits in the output; for instance we might determine that two bits must be unequal. By counting the number of solutions to the two-bit patterns, we obtain an upper bound on the number of possible outputs. Hence, the maximum leakage can be bounded. We first describe a straightforward computation of the two-bit patterns using an automated prover. We then show a more efficient implementation that uses an implication graph to represent the two- bit patterns. It efficiently constructs the graph through the use of an automated prover, random executions, STP counterexamples, and deductive closure. The effectiveness of our techniques, both in terms of efficiency and accuracy, is shown through a number of case studies found in recent literature. ^