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Total synthesis of analogs of lavendamycinEbrahimian, G. Reza January 2003 (has links)
There is no abstract available for this thesis. / Department of Chemistry
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Synthesis and Characterization of Organotin Polyamine Esters from DiglycineUnknown Date (has links)
This research is part of a long-term project aimed at elucidating important structural
features, of both ligands and metals, that are needed to produce effective anti-cancer agents.
The specific goal is the synthesis of organotin polymers containing amino acids, in this
case the diamino acid diglycine. The desired materials were synthesized with percent yields
ranging from 32-99%. The products were synthesized employing the interfacial
polymerization technique. The polymers were then characterized utilizing the following
physical characterization techniques: light scattering photometry (LS), Infrared
spectroscopy (IR), nuclear magnetic resonance spectroscopy (NMR), and matrix assisted
laser desorption mass spectroscopy (MALDI). Physical characterization showed evidence
of formation of desired adducts in addition to data that was consistent with the formation
of materials containing multiple repeat units. The materials were then analyzed for
biological activity. The synthesized materials displayed the ability to inhibit tested cancer
cell lines. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection
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Biological characterization of coibamide A, a marine natural product from a Panamanian cyanobacteriumHau, Andrew M. 08 January 2014 (has links)
Coibamide A is a methyl-stabilized cyclic depsipeptide with a lariat side chain that was isolated from a marine cyanobacterium as part of an International Cooperative Biodiversity Groups program based in Panama. Previous testing of this potent and selective growth-inhibitory agent in the National Cancer Institute (NCI) in vitro 60 human cell line panel revealed a "COMPARE-negative" profile indicative of a unique mechanism of action. Presented herein is a collection of studies characterizing the mechanism of action of coibamide A and cataloguing the cytotoxicities of putative coibamide A and related structures from efforts at its total synthesis. We report that coibamide A induces apoptotic and non-apoptotic cell death in human U87-MG and NCI-SF-295 glioblastoma cells, respectively, which can occur independently of a rapid and sustained mTOR-independent autophagic response. Loss of cell viability from coibamide A exposure was concentration-dependent and time-sensitive, characterized by extensive cytoplasmic vacuolization and an absence of apoptotic morphology and DNA fragmentation prior to cell rounding and detachment from the substratum. Coibamide A also induces a cytostatic effect mediated by a G1 phase specific cell cycle arrest and inhibits glioma cell invasion but not migration. Lastly, structure activity relationships suggest that linearization, loss of N-methylation and disjoining of the cyclic and side chain structures of coibamide A are not well-tolerated modifications to retain activity. / Graduation date: 2013 / Access restricted to the OSU Community at author's request from Jan. 8, 2013 - Jan. 8, 2014
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Studies of the antitumor activity of [alpha]-TEA in human breast cancer cellsWang, Pei 28 August 2008 (has links)
Not available / text
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Effects of gene selection and data sampling on prediction of breast cancer treatmentsUnknown Date (has links)
In recent years more and more researchers have begun to use data mining and
machine learning tools to analyze gene microarray data. In this thesis we have collected a
selection of datasets revolving around prediction of patient response in the specific area
of breast cancer treatment. The datasets collected in this paper are all obtained from gene
chips, which have become the industry standard in measurement of gene expression. In
this thesis we will discuss the methods and procedures used in the studies to analyze the
datasets and their effects on treatment prediction with a particular interest in the selection
of genes for predicting patient response. We will also analyze the datasets on our own in
a uniform manner to determine the validity of these datasets in terms of learning potential
and provide strategies for future work which explore how to best identify gene signatures. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection
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