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Articles 1 - 4 of 4
Full-Text Articles in Medicine and Health Sciences
Utilizing Ultra-Performance Chromatography High-Resolution Mass Spectrometry To Investigate Fatty Acid Mediated Antibiotic Tolerance, Brittni Woodall
Utilizing Ultra-Performance Chromatography High-Resolution Mass Spectrometry To Investigate Fatty Acid Mediated Antibiotic Tolerance, Brittni Woodall
Doctoral Dissertations
The lipid membrane is the first component necessary to sustain life. To maintain homeostasis, segregate cellular machinery, provide protection from the environment, and reproduce, an organism must establish a boundary in which the processes can occur. Throughout the last two decades, research has propelled our knowledge of lipid membranes much beyond original hypotheses. Once thought of to be static and uniform, the understanding of the lipid membrane has evolved to encompass a structure that is responsive, unique, and intricately constructed by the organism itself. By chance or by choice, organisms adapt the lipid membrane according to the environment for which …
Anxiety-Like Behavior In C57bl/6j Mice Is Sexually Dimorphic And Altered By Buprenorphine, Ohm Sharma
Anxiety-Like Behavior In C57bl/6j Mice Is Sexually Dimorphic And Altered By Buprenorphine, Ohm Sharma
Chancellor’s Honors Program Projects
No abstract provided.
Development Of Surface-Modified Liposomes For Drug Delivery Applications, Megan Louise Qualls
Development Of Surface-Modified Liposomes For Drug Delivery Applications, Megan Louise Qualls
Doctoral Dissertations
Liposomes are spherical vesicles composed of a lipid bilayer membrane that assembles around an internal aqueous core. This duality gives liposomes the ability to encapsulate both hydrophobic cargo within the lipid bilayer and hydrophilic cargo in the aqueous core, making them versatile molecular carriers for drug delivery. Liposome platforms have many advantages and are promising drug delivery carriers, and research is ongoing to improve their designs for continued clinical applications. Many liposome types have been developed, but further work is needed to improve surface modification, site-specific targeting, and triggered cargo release in order to further the therapeutic applications of these …
A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb
A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb
Masters Theses
One of the biggest challenges the clinical research industry currently faces is the accurate forecasting of patient enrollment (namely if and when a clinical trial will achieve full enrollment), as the stochastic behavior of enrollment can significantly contribute to delays in the development of new drugs, increases in duration and costs of clinical trials, and the over- or under- estimation of clinical supply. This study proposes a Machine Learning model using a Fully Convolutional Network (FCN) that is trained on a dataset of 100,000 patient enrollment data points including patient age, patient gender, patient disease, investigational product, study phase, blinded …