Electrocardiogram breathing: A study of electrocardiogram derived respiration plus multiresolution wavelet analysis of heartbeat interval variability in sleep study patients

This dissertation presents a unique research opportunity by using recordings which provide electrocardiogram (ECG) plus a reference breathing signal (RBS). ECG derived breathing (EDR) is measured and correlated against RBS. Standard deviations of multiresolution wavelet analysis coefficients (SDMW) are obtained from heart rate and classified using RBS. Prior works by others used select patients for sleep apnea scoring with EDR but no RBS. Another prior work classified select heart disease patients with SDMW but no RBS. This study used randomly chosen sleep disorder patient recordings; central and obstructive apneas, with and without heart disease.^ Implementation required creating an application because existing systems were limited in power and scope. A review survey was created to choose a development environment. The survey is presented as a learning tool and teaching resource. Development objectives were rapid development using limited resources (manpower and money). Open Source resources were used exclusively for implementation. ^ Results show: (1) Three groups of patients exist in the study. Grouping RBS correlations shows a response with either ECG interval or amplitude variation. A third group exists where neither ECG intervals nor amplitude variation correlate with breathing. (2) Previous work done by other groups analyzed SDMW. Similar results were found in this study but some subjects had higher SDMW, attributed to a large number of apneas, arousals and/or disconnects. SDMW does not need RBS to show apneic conditions exist within ECG recordings. (3) Results in this study support the assertion that autonomic nervous system variation was measured with SDMW. Measurements using RBS are not corrupted due to breathing even though respiration overlaps the same frequency band.^ Overall, this work becomes an Open Source resource which can be reused, modified and/or expanded. It might fast track additional research. In the future the system could also be used for public domain data. Prerecorded data exist in similar formats in public databases which could provide additional research opportunities. ^

Trace elemental analysis of glass by inductively coupled plasma-mass spectrometry (ICP-MS) and laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS)

This work evaluated the capabilities of inductively coupled plasma mass spectrometry (ICP-MS) for elemental analysis of trace evidence. A method was developed and validated for the analysis of glass by ICP-MS. A database of ∼700 glass samples was analyzed for elemental composition by external calibration with internal standardization (EC) ICP-MS and refractive index (RI). Additional methods were developed during the course of this work using two well-known techniques, isotope dilution (ID) and laser ablation (LA). These methods were then applied to analyze subsets of this database. ICP-MS data from 161 containers, 45 headlamps, and 458 float glasses (among them at least 143 vehicle windows) are presented and summarized. Data from the analysis of ∼190 glass samples collected from a single glass manufacturing facility over a period of 53 months at different intervals, including 97 samples collected in a 24 hour period are presented. Data from the analysis of 125 glass samples representing 36 manufacturing plants in the U.S. are also presented. ^ The three methods used, ICP-MS, ID-ICP-MS and LA-ICP-MS, were shown to be excellent methods for distinguishing between different glass samples. The database provided information about the variability of refractive index and elemental composition in glasses from diverse population types. Using the proposed methods, the database supports the hypothesis that different glass samples have different elemental profiles and a comparison between fragments from the same source results in indistinguishable profiles. ^

Analysis of Heterokaryon Formation in Fusarium oxysporum f. sp. cubense.

Fusarium oxysporum forma specialis cubense is a soilborne phytopathogen that infects banana. The true evolutionary identity of this so called species, Fusarium oxysporum, is still unknown. Many techniques have been applied in order to gain insight for the observed genetic diversity of this species. The current classification system is based on vegetative compatibility groups (VCG's). Vegetative compatibility is a self non-self recognition system in which only those belonging to a VCG can form stable heterokaryons, cells containing two distinct nuclei. Heterokaryons in turn, are formed from hypha! anastomosis, the fusion of two hyphae. Furthermore, subsequent to heterokaryon formation potential mechanisms exist which may generate genetic variability. One is through viral transfer upon hyphal anastomosis. The other mechanism is a form of mitotic recombination referred to as the parasexual cycle. Very little research has been performed to directly obser.ve the cellular events; hypha! anastomosis, heterokaryon formation, and the parasexual cycle in Fusarium oxysporum f. sp. cubense. The purpose of this research was to design and use methods which would allow for the detection of hypha! anastomosis and heterokaryon formation, as well as any characteristics surrounding this event, within and between VCG's in Foe. First, some general growth properties were recorded: the number of nuclei per hypha, the size ofthe hyphal tip cell, the size of the cell adjacent to the hypha! tip (pre-tip) cell, and the number of cells to the first branch point. Second, four methods were designed in order to assay hyphal anastomosis and heterokaryon formation: 1) pairings on membrane: phase or brightfield microscopy, 2) pairings on membrane: fluorescence microscopy, 3) spore crosses: fluorescence microscopy, and 4) double picks in fractionated MMA. All of these methods were promtsmg.

Phylogenetic analysis of within -host serially-sampled viral data

The primary goal of this dissertation is the study of patterns of viral evolution inferred from serially-sampled sequence data, i.e., sequence data obtained from strains isolated at consecutive time points from a single patient or host. RNA viral populations have an extremely high genetic variability, largely due to their astronomical population sizes within host systems, high replication rate, and short generation time. It is this aspect of their evolution that demands special attention and a different approach when studying the evolutionary relationships of serially-sampled sequence data. New methods that analyze serially-sampled data were developed shortly after a groundbreaking HIV-1 study of several patients from which viruses were isolated at recurring intervals over a period of 10 or more years. These methods assume a tree-like evolutionary model, while many RNA viruses have the capacity to exchange genetic material with one another using a process called recombination. ^ A genealogy involving recombination is best described by a network structure. A more general approach was implemented in a new computational tool, Sliding MinPD, one that is mindful of the sampling times of the input sequences and that reconstructs the viral evolutionary relationships in the form of a network structure with implicit representations of recombination events. The underlying network organization reveals unique patterns of viral evolution and could help explain the emergence of disease-associated mutants and drug-resistant strains, with implications for patient prognosis and treatment strategies. In order to comprehensively test the developed methods and to carry out comparison studies with other methods, synthetic data sets are critical. Therefore, appropriate sequence generators were also developed to simulate the evolution of serially-sampled recombinant viruses, new and more through evaluation criteria for recombination detection methods were established, and three major comparison studies were performed. The newly developed tools were also applied to "real" HIV-1 sequence data and it was shown that the results represented within an evolutionary network structure can be interpreted in biologically meaningful ways. ^