Physical Sciences and Mathematics Commons^™

Bioenergetics: Experimental Demonstration Of Excess Protons And Related Features, Haitham A. Saeed

Chemistry & Biochemistry Theses & Dissertations

Over the last 50 years, ever since the Nobel-prize work of Peter Mitchell’s Chemiosmotic theory, the question whether bioenergetics energy transduction occurs through localized or delocalized protons has been a controversial issue among scientists. Recently, a proton-electrostatics localization hypothesis was formulated which may provide a new and clear understanding of localized and delocalized proton-coupling energy transduction in many biological systems. The aim of this dissertation was to test this new hypothesis.

To demonstrate the fundamental behavior of localized protons in a pure water-membrane-water system in relation to the newly derived pmf equation, excess protons and excess hydroxyl anions were generated …

Synthesis And Mechanistic Investigations Of Transition Metal Complexes And Ligands For Chemotherapeutic Applications, Jimmie Lee Bullock Jr.

Chemistry & Biochemistry Theses & Dissertations

Transition metal complexes have played a critical role in antitumor therapy with many complexes incorporating platinum, ruthenium, and lanthanum having been investigated in preclinical and clinical trials. The best known transition metal therapeutic is cisplatin, which is utilized in nearly 50% of all cancer therapies, despite its significant toxic side effects. The toxic side effects of current FDA approved platinum-based chemotherapeutics are often overlooked due to the “special status” granted to these drugs due to their ability to fight, what is often considered an incurable disease with life expectancies often measured in months. Oncology drug development has therefore now focused …

Deep Models For Brain Em Image Segmentation: Novel Insights And Improved Performance, Ahmed Fakhry, Hanchuan Peng, Shuiwang Ji

Computer Science Faculty Publications

Motivation: Accurate segmentation of brain electron microscopy (EM) images is a critical step in dense circuit reconstruction. Although deep neural networks (DNNs) have been widely used in a number of applications in computer vision, most of these models that proved to be effective on image classification tasks cannot be applied directly to EM image segmentation, due to the different objectives of these tasks. As a result, it is desirable to develop an optimized architecture that uses the full power of DNNs and tailored specifically for EM image segmentation.

Results: In this work, we proposed a novel design of DNNs for …