Sequence analysis of complementary DNAs encoding C3 in the nurse shark ({\it Ginglymostoma cirratum\/})

Mammalian C3 is a pivotal complement protein, encoded for by a single gene. In some vertebrate species multiple C3 isoforms are products of different C3 genes. The goal of this study was to determine whether multiple genes encode for shark C3. A protocol was developed for the isolation of mRNA from shark blood for the isolation of C3 cDNA clones. RT-PCR amplification of mRNA, using sense (GCGEQNM) and antisense (TWLTAYV) primers encoding conserved regions of human C3, yielded 21 clones. The C3-like clones isolated shared 97% similarity with each other and 40% similarity to human C3. RACE-PCR amplification of shark liver RNA, using gene specific primers, yielded products ranging from 1800bp to 3000bp. Deduced amino acid sequence, corresponding to 408bp of the 1800bp fragment, was obtained which showed 51% similarity to human C3. These results suggest that nurse shark C3 might be encoded for by more than one gene. ^

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. ^