One of the best ways to diagnose breast cancer early or to predict therapeutic response is to use serum biomarkers. Unfortunately, for breast cancer, we do not have effective serological biomarkers. We hypothesized that novel candidate tumor markers for breast cancer may be secreted or shed proteins that can be detected in tissue culture supernatants of human breast cancer cell lines. A two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) strategy was utilized to identify and compare levels of extracellular and membrane-bound proteins in the conditioned media. Proteomic analysis of the media identified in excess of 600, 500 and 700 proteins in MCF-10A, BT474 and MDA-MB-468, respectively. We successfully identified the internal control proteins, kallikreins 5, 6 and 10 (ranging in concentration from 2-50 µg/L), as validated by ELISA and confidently identified HER-2/neu in BT474 cells. Sub-cellular localization was determined based on Genome Ontology (GO) for the 1,139 proteins, of which 34% were classified as extracellular and membrane-bound. Tissue specificity, functional classifications and label-free quantification were performed. The levels of eleven promising molecules were measured in biological samples to determine its discriminatory ability for control versus cases. This screen yielded activated leukocyte cell adhesion molecule (ALCAM) as a promising candidate. The levels of ALCAM, in addition to the classical breast cancer tumor markers carbohydrate antigen 15-3 (CA 15-3) and carcinoembryonic antigen (CEA) were examined in 300 serum samples by quantitative ELISA. All three biomarkers effectively separated cancer from non-cancer groups. ALCAM, with area under the curve (AUC) of 0.78 [95% CI: 0.73, 0.84] outperformed CA15-3 (AUC= 0.70 [95% CI: 0.64, 0.76]) and CEA (AUC= 0.63 [95% CI: 0.56, 0.70]). The incremental values of AUC for ALCAM over that for CA15-3 were statistically significant (Delong test, p <0.05). Serum ALCAM appears to be a new biomarker for breast cancer and may have value for disease diagnosis.

One of the best ways to diagnose breast cancer early or to predict therapeutic response is to use serum biomarkers. Unfortunately, for breast cancer, we do not have effective serological biomarkers. We hypothesized that novel candidate tumor markers for breast cancer may be secreted or shed proteins that can be detected in tissue culture supernatants of human breast cancer cell lines. A two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) strategy was utilized to identify and compare levels of extracellular and membrane-bound proteins in the conditioned media. Proteomic analysis of the media identified in excess of 600, 500 and 700 proteins in MCF-10A, BT474 and MDA-MB-468, respectively. We successfully identified the internal control proteins, kallikreins 5, 6 and 10 (ranging in concentration from 2-50 µg/L), as validated by ELISA and confidently identified HER-2/neu in BT474 cells. Sub-cellular localization was determined based on Genome Ontology (GO) for the 1,139 proteins, of which 34% were classified as extracellular and membrane-bound. Tissue specificity, functional classifications and label-free quantification were performed. The levels of eleven promising molecules were measured in biological samples to determine its discriminatory ability for control versus cases. This screen yielded activated leukocyte cell adhesion molecule (ALCAM) as a promising candidate. The levels of ALCAM, in addition to the classical breast cancer tumor markers carbohydrate antigen 15-3 (CA 15-3) and carcinoembryonic antigen (CEA) were examined in 300 serum samples by quantitative ELISA. All three biomarkers effectively separated cancer from non-cancer groups. ALCAM, with area under the curve (AUC) of 0.78 [95% CI: 0.73, 0.84] outperformed CA15-3 (AUC= 0.70 [95% CI: 0.64, 0.76]) and CEA (AUC= 0.63 [95% CI: 0.56, 0.70]). The incremental values of AUC for ALCAM over that for CA15-3 were statistically significant (Delong test, p <0.05). Serum ALCAM appears to be a new biomarker for breast cancer and may have value for disease diagnosis.

No description available.

Opiine wasps (Hymenoptera: Braconidae: Opiinae) are parasitoids of dacine fruit flies (Diptera: Tephritidae: Dacinae), the primary horticultural pests of Australia and the South Pacific. Effective use of opiines for biological control of fruit flies is limited by poor taxonomy and identification difficulties. To overcome these problems, this thesis had two aims: (i) to carry out traditional taxonomic research on the fruit fly infesting opine braconids of Australia and the South Pacific; and (ii) to transfer the results of the taxonomic research into user friendly diagnostic tools. Curated wasp material was borrowed from all major Australian museum collections holding specimens. This was supplemented by a large body of material gathered as part of a major fruit fly project in Papua New Guinea: nearly 4000 specimens were examined and identified. Each wasp species was illustrated using traditional scientific drawings, full colour photomicroscopy and scanning electron microscopy. An electronic identification key was developed using Lucid software and diagnostic images were loaded on the web-based Pest and Diseases Image Library (PaDIL). A taxonomic synopsis and distribution and host records for each of the 15 species of dacine-parasitising opiine braconids found in the South Pacific is presented. Biosteres illusorius Fischer (1971) was formally transferred to the genus Fopius and a new species, Fopius ferrari Carmichael and Wharton (2005), was described. Other species dealt with were Diachasmimorpha hageni (Fullaway, 1952), D. kraussii (Fullaway, 1951), D. longicaudata (Ashmead, 1905), D. tryoni (Cameron, 1911), Fopius arisanus (Sonan, 1932), F. deeralensis (Fullaway, 1950), F. schlingeri Wharton (1999), Opius froggatti Fullaway (195), Psyttalia fijiensis (Fullaway, 1936), P. muesebecki (Fischer, 1963), P. novaguineensis (Szépliget, 1900i) and Utetes perkinsi (Fullaway, 1950). This taxonomic component of the thesis has been formally published in the scientific literature. An interactive diagnostics package (“OpiineID”) was developed, the centre of which is a Lucid based multi-access key. Because the diagnostics package is computer based, without the space limitations of the journal publication, there is no pictorial limit in OpiineID and so it is comprehensively illustrated with SEM photographs, full colour photographs, line drawings and fully rendered illustrations. The identification key is only one small component of OpiineID and the key is supported by fact sheets with morphological descriptions, host associations, geographical information and images. Each species contained within the OpiineID package has also been uploaded onto the PaDIL website (www.padil.gov.au). Because the identification of fruit fly parasitoids is largely of concern to fruit fly workers, rather than braconid specialists, this thesis deals directly with an area of growing importance to many areas of pure and applied biology; the nexus between taxonomy and diagnostics. The Discussion chapter focuses on this area, particularly the opportunities offered by new communication and information tools as new ways delivering the outputs of taxonomic science.

No description available.

The influence of observations on the outcome of an analysis is of importance in statistical data analysis. A practical and well-established approach to influence analysis is case deletion. However, it has its draw-backs when subsets of observations are jointly influential and offset each other's influence. Another approach is local influence proposed by Cook (1986).The local influence methodology of Cook (1986) is based on the curvature of the likelihood displacement surface formed by model/data perturbations. Wu and Luo (1993a, 1993b) further developed the idea and proposed the study of the perturbation-formed surface of a variable by evaluating the curvature of the surface in addition to its maximum slope. This thesis utilizes the local influence approach to develop influence diagnostic methods for four different topics.Firstly, we proposed a stepwise confirmatory procedure for the detection of multiple outliers in two-way contingency tables. The procedure begins with the identification of a reliable set of candidate outliers by evaluating the derivatives of the perturbation-formed surface of the Pearson goodness-of-fit statistic. An adding-back iterative algorithm is then applied to the candidate set to assess their relative discordancy. Using two real data sets, the proposed procedure is shown to be less susceptible to both masking and swamping problems than residual based measures. In a Monte Carlo study, the local influence diagnostics are also found to outperform standard residual-based methods in terms of efficiency and other criteria.Transformations of covariates are commonly applied in regression analysis. When a parametric transformation family is used, the maximum likelihood estimate of the transformation parameter is often sensitive to minor perturbations of the data. Diagnostics based on the local influence approach are derived to assess the influence ++ / of observations on the covariate transformation parameter in generalized linear models. Three numerical examples are presented to illustrate the usefulness of the proposed diagnostics. The need for transformation is also addressed in addition to assessing influence on the transformation parameter.A common method of choosing the link function in generalized linear models is to specify a parametric link family indexed by unknown parameters. The maximum likelihood estimates of such link parameters, however, often depend on one or several extreme observations. Diagnostics based on the local influence approach are derived to assess the sensitivity of the parametric link analysis. Two examples demonstrate that the proposed diagnostics can identify jointly influential observations on the link even when masking is present. The application of the diagnostics can also assist us in revising the link parameter and hence the form of the model.The portmanteau statistic is commonly used for testing goodness-of-fit of time series models. However, this lack of fit test may depend on one or several atypical observations in the series. We investigate the sensitivity of the portmanteau statistic in the presence of additive outliers. Diagnostics based on the local influence approach are developed to assess both local and global influence. Three practical examples demonstrate the usefulness of the proposed diagnostics.

Thesis (Ph. D.)--University of Wisconsin, 1967. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliography.

Nucleic acid (NA) purification from clinical samples is commonly achieved using silica solid phase extraction in the presence of a chaotropic salt. Versions of these protocols have been adapted for point of care (POC) diagnostic devices in miniaturized platforms. Most such protocols require a high net amount of input NA, which is often achieved by adding exogenous carrier NA to the clinical sample. As a result, for samples containing less than 1 μg of total NA, NA recovery is low in the absence of carrier NA. Clinical samples used in POC diagnostics may contain very low NA concentrations (~1 ng/ml), which result in NA-limited interactions with the solid phase that are outside the dynamic range of POC diagnostics. This work is a study of DNA-silica interactions in the DNA-limiting regime to gain fundamental understanding of the mechanisms at play in order to increase the dynamic range and sensitivity of miniaturized NA based POC diagnostics. DNA adsorption and recovery from silica surfaces for concentrations less than 1 μg/ml are studied. A protocol was designed and developed to systematically quantify the adsorption of DNA onto a silica surface and the amount of DNA recovered by elution at very low concentrations. Various adsorption conditions were examined including a range of pH, different chaotropes, and DNA concentrations down to 2.5 pg/ml. DNA recovery was further optimized for low concentration samples by varying elution buffers. DNA-silica adsorption was enhanced by low pH and was further improved by the presence of a chaotrope. Different adsorption conditions had little effect on DNA recovery using low salt, high pH elution buffers, but DNA recovery did exceed 40% when adsorbed initially with 5 M guanidinium thiocyanate at pH 5.2. Recovery was enhanced by eluting with 95 °C formamide or 1 M NaOH, supporting the hypothesis that DNA-silica interactions are dominated by hydrophobic forces and hydrogen bonding. While heated formamide and NaOH are non-ideal elution buffers for practical POC devices, these results are important for engineering a set of optimized reagents and conditions that could maximize DNA recovery from a microfluidic POC silica system. / 2017-06-21T00:00:00Z

Cytokines are small-molecule signaling proteins involved in cell-cell regulation. The detection of low-abundance cytokines is challenging since the currently available techniques are limited by sensitivity and are time-consuming. Nanopore sensing is an emerging technique in nanotechnology that is catalyzing key breakthroughs in many areas, including the analysis and study of proteins at the single-molecule level. Solid-state nanopore sensing has the advantage of analyzing small copy numbers of biomolecules, such as DNA, with high throughput. However, protein detection using nanopores is still in in infancy because the mechanisms of native protein translocation inside the solid-state nanopore are highly complicated. The goal of this project is to develop a novel solid-state nanopore device for identification and quantification of cancer cytokines directly from cell culture. Vascular endothelial growth factor (VEGF) is chosen as a model cytokine due to its high abundance in cancerous tissue, and its well-characterized molecular structure. Firstly, we used a nanopore sensor to monitor individual VEGF proteins in solution while simultaneously obtaining tertiary and quaternary structural information. Next, we used the translocation signature to identify VEGF secreted directly from the culture media of the breast cancer cell line. A series of DNA and RNA aptamers was screened to selectively bind to secreted VEGF, enhancing the detection rate and creating a unique translocation signature for easy protein discrimination. Finally, we integrated the nanopore with a hard microfluidic device designed to facilitate the on-chip sample preparation prior to nanopore sensing. This nanopore-microfluidic device may allow scientists and clinicians to directly detect biomarkers secreted from a small population of cultured cells, which would revolutionize cancer diagnostics and prognostics. / 2020-10-22T00:00:00Z

Ultrasound imaging plays an important role in biomedical diagnostics due its safety, noninvasive nature, and low cost. Conventional ultrasound systems typically form an image frame by scanning the region of interest line-by-line, using a focused beam during transmission and dynamic focusing during reception. Alternatively, the region of interest can be insonified at once using a plane wave, which allows for ultrafast data acquisition rates but reduces the resulting image quality. The latter can be improved by means of coherent plane-wave compounding (CPWC), whereby multiple plane waves are emitted at different angles to obtain multiple image datasets that are subsequently combined to enhance the final compounded image. We present two novel Fourier-domain techniques for CPWC image reconstruction from raw linear-array sensor data. In particular, we show how to modify two classic algorithms used for geophysical data processing, namely Stolt's and slant-stack depth migration under zero-offset constant-velocity assumptions, so that their new versions become applicable to plane-wave ultrasound data processing. To demonstrate the merits and limitations of our approach, we provide qualitative and quantitative comparisons with other Fourier-domain methods reported in the ultrasound literature. Our evaluation results are based on the image resolution, contrast, and similarity metrics obtained for several public-domain experimental benchmark datasets. We also describe another novel Fourier-domain method for CPWC image reconstruction that can be used in situations where the speed of sound varies with depth in a layered propagation medium. Our technique builds on Gazdag's phase-shift migration algorithm that has been modified to handle plane-wave ultrasound data processing. Our simulation results show that the proposed method is capable of accurately imaging point targets in a three-layer medium, mimicking tissue-bone-tissue ultrasound propagation. / Graduate