Dendritic cells (DCs) are regulators of the immune system and express a class of pattern recognition receptors known as C-type lectin receptors (CLRs) to recognize and respond to carbohydrates (glycans). Dendritic cells are hypothesized to be key mediators in the immune response to implanted materials and ligation of CLRs has been shown to have diverse effects on DC phenotype ranging from tolerogenic to pro-inflammatory. Thus, designing future biomaterials and combination products that harness the potential of CLR ligation on DCs has great promise. Additionally, many of the proteins which adsorb to biomaterials when implanted are glycosylated and thus understanding this interaction would provide further insight into the host response to currently implanted materials. However, DC responses to glycans presented from non-phagocytosable surfaces has not been well characterized and optimal factors for DC phenotype modulation by surface presented glycans are unknown. Additionally, studies relating DC response to glycan structures from soluble and phagocytosable displays to that of non-phagocytosable display have not been performed. This is of critical importance to the field because of the extremely limited supply of complex glycan structures that are able to be obtained. Because of this limited supply of glycans the trend in glycomics has been toward creation of glycan microarrays to assess initial candidates of interest for further study. However, the assumption that cell response to these glycoconjugate microarrays is equivalent to soluble or phagocytosable conjugates has not been validated. Therefore, the purpose of this study was to 1) determine the optimal molecular contextual variables of glycoconjugate presentation from a non-phagocytosable surface, namely, charge, density, and glycan structure for modulating DC phenotype; and 2) determine if modality of glycoconjugate presentation, i.e. soluble, phagocytosable, or non-phagocytosable will modulate DC phenotype differentially. To determine the effect of the molecular contextual variables primary human immature DCs (iDCs) were exposed to a range of adsorbed glycoconjugates in a 384 well plate and their subsequent phenotype assessed via a novel in house produced high throughput (HTP) assay. Bovine serum albumin (BSA) was modified to have a range of glycan densities and isoelectric points to determine which of these were optimal for DC phenotype modulation. Next, several poly-mannose structures were presented to DCs to determine if DC response was structure specific. Finally, contextual variables were modeled in a multivariate general linear model to determine underlying trends in DC behavior and optimal factors for glycan presentation from non-phagocytosable surfaces. To determine the effect of the modality of glycoconjugate display on DCs, optimized glycoconjugates from 1) were adsorbed to the wells of a 384 flat well plate, delivered at varying soluble concentrations, or adsorbed to phagocytosable 1 µm beads and subsequent DC phenotype assessed via the HTP assay. The cell response to the glycoconjugates was then validated to be CLR mediated and the DC response to glycan modality was modeled in another general linear model. Results from these studies show that highly cationized high density glycoconjugates presented from non-phagocytosable flat well display modulate DC phenotype toward a pro-inflammatory phenotype to the greatest extent. Additionally, significant impacts on DC phenotype in response to adsorbed conjugates can be seen when grouping glycan structure by terminal glycan motif. Finally, DC response to glycoconjugates were found to be CLR mediated and that each modality of glycan display is significantly different, in terms of DC phenotype, from the others. These results provide indications for the future design of glycan microarray systems, biomaterials and combination products. Furthermore, this work indicates that different mechanisms are involved in binding and processing of surface bound versus soluble glycoconjugates. With further study these differences could be harnessed for use in the next generation of biomaterials.

Lignin is a major chemical component of plants and the second most abundant natural polymer after cellulose. The concerns and interests of agriculture and industry have stimulated the study of genes governing lignin content in plants in an effort to adapt plants to human purposes. Arabidopsis thaliana provides a convenient model for the study of the genes governing lignin content because of its short growth cycle, small plant size, and small completely sequenced genome. In order to identify the genes controlling lignin content in Arabidopsis accessions using Quantitative Trait Locus (QTL) analysis, a rapid micro-scale method of lignin determination is required. The acetyl bromide method has been modified to enable the rapid micro-scale determination of lignin content in Arabidopsis. Modifications included the use of a micro-ball mill, adoption of a modified rapid method of extraction, use of an ice-bath to stabilize solutions and reduction in solution volumes. The modified method was shown to be accurate and precise with values in agreement with those determined by the conventional method. The extinction coefficient for Arabidopsis lignin, dissolved using acetyl bromide, was determined to be 23.35 g-iLcm-1. This value is independent of the Arabidopsis accession, environmental growth conditions and is insensitive to syringyl/guaiacyl ratio. The modified acetyl bromide method was shown to be well correlated with the 72% sulfuric acid method once the latter had been corrected for protein contamination and acid-soluble lignin content (R² = 0.988, P < 0.0001). As determined by the newly developed acetyl bromide method and confirmed by the sulfuric acid method, lignin content in Arabidopsis was found to be a divergent property. Lignin content in Arabidopsis was found to be weekly correlated with growth rate among Arabidopsis accessions (R² = 0.48, P = 0.011). Lignin content was also found to be correlated with plant height among Arabidopsis accessions (R² = 0.491, P < 0.0001).

Currently, clustering applications use classical methods to partition a set of data (or objects) in a set of meaningful sub-classes, called clusters. A cluster is therefore a collection of objects which are “similar” among them, thus can be treated collectively as one group, and are “dissimilar” to the objects belonging to other clusters. However, there are a number of problems with clustering. Among them, as mentioned in [Datta03], dealing with large number of dimensions and large number of data items can be problematic because of computational time. In this thesis, we investigate all clustering algorithms used in [Datta03] and we present a parallel solution to minimize the computational time. We apply parallel programming techniques to the statistical algorithms as a natural extension to sequential programming technique using R. The proposed parallel model has been tested on a high throughput dataset. It is microarray data on the transcriptional profile during sporulation in budding yeast. It contains more than 6,000 genes. Our evaluation includes clustering algorithm scalability pertaining to datasets with varying dimensions, the speedup factor, and the efficiency of the parallel model over the sequential implementation. Our experiments show that the gene expression data follow the pattern predicted in [Datta03] that is Diana appears to be solid performer also the group means for each cluster coincides with that in [Datta03]. We show that our parallel model is applicable to the clustering algorithms and more useful in applications that deal with high throughput data, such as gene expression data.

The application of ultrahigh-field Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) technology to identify and quantify metabolomics data is relatively new. An important feature of the FTICR-MS metabolomics data is the high percentage of missing values. In this thesis, missing value analysis showed that the missing value percentages were up to 50% and the control treatment, NaOH.ww, had the highest missing value percentage among the treatments in the aqueous FTICRMS sets. A simulation study was done for the FTICR-MS data to compare selection methods, the Kruskal-Wallis test and the MTP and Limma functions in Bioconductor, an open source project to facilitate the analysis of high-throughput data. The study showed that MTP was sensitive to variations among treatments, while the Kruskal- Wallis test was relatively conservative in detecting variations. As a result, MTP had a much higher false positive rate than Kruskal-Wallis test. The performance of Limma for sensitivity and false positive rate was between the Kruskal-Wallis test and MTP. Data sets with missing values were also simulated to assess the performance of imputation methods. Study showed that variances among treatments diminished or disappeared after imputations, but no new differentially expressed masses were created. This gave us confidence in using imputation methods. Summary of analysis results of some of the frogSCOPE data sets was given in the last chapter as an illustration. / Graduate

Fatty acid profiling provides information on dietary intakes and an understanding of lipid metabolism. High throughput techniques such as fingertip prick (FTP) sampling has gained popularity in recent years as a simplified method for basic research, and could be further used to assess disease risk in the population, and other similar high-throughput techniques have the potential to assist in the monitoring and labeling of fatty acids in the food supply. With the advancement of high-throughput sample analysis techniques, a more complete understanding of storage stability is required as a larger volume of samples are produced with equal amounts of time to analyze them. Energy-assisted analysis techniques have the potential to help ameliorate some of these issues. Presently, FTP blood, whole blood and salmon storage stability is assessed under various storage conditions, and both microwave-assisted direct transesterification and indirect ultrasound-assisted extraction techniques are assessed. It is determined that storage of FTP blood and whole blood samples at -20°C results in significant and nearly complete highly unsaturated fatty acid (HUFA) degradation compared to all other temperatures examined. This degradation is determined to be the result of hemolysis and subsequent iron release from erythrocytes initiating fatty acid peroxidation reactions. Direct transesterification of FTP blood is reduced from as long as three hours to one minute with microwave-assisted energy and fatty acid extraction from ground flaxseed is reduced to 40 minutes from as long as 24 hours without compromising fatty acid profiles. Results of the current study provides insight into the storage stability of food sample and blood samples collected via high-throughput techniques, and provides support for the utilization of further high-throughput energy-assisted analytical methods that can help to minimize the potentially detrimental effects that long-term storage can have on fatty acid profiles.

Until recently, multiple SPME fibres could not be automatically evaluated in a single sequence without manual intervention. This drawback had been a critical issue until recently, particularly during the analysis of numerous on-site samples. Recently, GERSTEL® has developed and commercialized a Multi-Fibre Exchanger (MFX) system designed to overcome this drawback. In this research, a critical evaluation of the MFX performance in terms of storage stability and long term operation is presented. It was established in the course of our research that the MFX can operate continuously and precisely for over 200 extraction/injection cycles. However, when the effect of residence time of commercial fibres on the MFX tray was evaluated, the results have shown that amongst the evaluated fibre coatings, carboxen/polydimethylsiloxane (CAR/PDMS) was the only coating capable of efficient storage on the MFX tray for up to 24 hours after field sampling without suffering significant loss of analytes. Additionally, the MFX system capability for high-throughput analysis was demonstrated by the unattended desorption of multiple fibres after on-site sampling of two different systems, indoor air and biogenic emissions. Subsequently, a protocol based on a new, fast, reproducible, reusable and completely automated method that enables quick assessment of SPME coatings was developed. The protocol consists of an innovative in-vial standard generator containing vacuum pump oil doped with McReynolds probes and subsequently mixed with a polystyrene-divinylbenzene resin. According to our results, the protocol has proven to be a useful tool for the quick assessment of inter-fibre reproducibility prior to their application in on-site analysis. The implications of such protocols include, but are not limited to: time-saving, assurance of reliable and reproducible data, and a dependable guide for novice users of the technique. Finally, an innovative, reusable and readily deployable pen-like diffusive sampler for needle traps (PDS-NT) is proposed. Results have shown that the new PDS-NT is effective for air analysis of benzene, toluene, and o-xylene (BTX). In addition, no statistically significant effects of pen geometry on the uptake of analytes were found.

The colony formation assay (CFA) is the gold standard for measuring cytotoxic effects on cells. To increase efficiency, the CFA was converted to a 96-well format using an automated colony counting algorithm. The 96-well CFA was validated using ionizing radiation (IR) on the FaDu and A549 cancer cell lines. Its ability to evaluate combination therapies was investigated using cisplatin and IR. The 96-well CFA was transferred to a robotic platform for evaluation as a high-throughput screen (HTS) readout for the discovery of novel anti-cancer compounds, and radiosensitizers. Screening yielded eight putative anti-cancer hits, and five putative radiosensitizing hits. Secondary screening confirmed 6/8 anti-cancer compounds, and 0/5 radiosensitizing compounds. Thus, the 96-well CFA can be adopted as an alternative assay to the 6-well CFA in the evaluation of cytotoxicity in vitro, providing a possible readout to be utilized in HTS for discovering anti-cancer compounds, but with limited applicability in discovering radiosensitizers.

Lignin is a major chemical component of plants and the second most abundant natural polymer after cellulose. The concerns and interests of agriculture and industry have stimulated the study of genes governing lignin content in plants in an effort to adapt plants to human purposes. Arabidopsis thaliana provides a convenient model for the study of the genes governing lignin content because of its short growth cycle, small plant size, and small completely sequenced genome. In order to identify the genes controlling lignin content in Arabidopsis accessions using Quantitative Trait Locus (QTL) analysis, a rapid micro-scale method of lignin determination is required. The acetyl bromide method has been modified to enable the rapid micro-scale determination of lignin content in Arabidopsis. Modifications included the use of a micro-ball mill, adoption of a modified rapid method of extraction, use of an ice-bath to stabilize solutions and reduction in solution volumes. The modified method was shown to be accurate and precise with values in agreement with those determined by the conventional method. The extinction coefficient for Arabidopsis lignin, dissolved using acetyl bromide, was determined to be 23.35 g-iLcm-1. This value is independent of the Arabidopsis accession, environmental growth conditions and is insensitive to syringyl/guaiacyl ratio. The modified acetyl bromide method was shown to be well correlated with the 72% sulfuric acid method once the latter had been corrected for protein contamination and acid-soluble lignin content (R² = 0.988, P < 0.0001). As determined by the newly developed acetyl bromide method and confirmed by the sulfuric acid method, lignin content in Arabidopsis was found to be a divergent property. Lignin content in Arabidopsis was found to be weekly correlated with growth rate among Arabidopsis accessions (R² = 0.48, P = 0.011). Lignin content was also found to be correlated with plant height among Arabidopsis accessions (R² = 0.491, P < 0.0001).

Zugl.: Hamburg, Techn. Univ., Diss., 2008

Thesis (Ph. D.)--Ohio State University, 2008. / Title from first page of PDF file. Includes bibliographical references (p. 210-232).