Fabrication Of Miniature Drug Screening Platform Using Low Cost Bioprinting Technology,
2010
University of Texas at El Paso
Fabrication Of Miniature Drug Screening Platform Using Low Cost Bioprinting Technology, Jorge Ivan Rodriguez
Open Access Theses & Dissertations
In the pharmaceutical industry, new chemicals and substances are being tested to find appropriate compounds or mix for treating a specific disease. The demand for screening large compound collections against and increasing number of therapeutic targets has stimulated technology development in the areas of assay automation and miniaturization. Current methods for evaluating the reactions of cells use a volume in the range of microliters. We have developed a new and low-cost deposition method to fabricate miniature drug screening platform that can realistically and inexpensively evaluate biochemical reactions up to 4 substances per trial in a picoliter-scale volume. This paper describes …
Computer-Aided Detection Of Sleep Apnea And Sleep Stage Classification Using Hrv And Eeg Signals,
2010
University of Texas at El Paso
Computer-Aided Detection Of Sleep Apnea And Sleep Stage Classification Using Hrv And Eeg Signals, Edson F. Estrada
Open Access Theses & Dissertations
Sleep is a circadian rhythm essential for human life. Many events occur in the body during this state. In the past, significant efforts have been made to provide clinicians with reliable and less intrusive tools to automatically classify the sleep stages and detect apnea events. A few systems are available in the market to accomplish this task. However, sleep specialists may not have full confidence and trust in such systems due to issues related to their accuracy, sensitivity and specificity. The main objective of this work is to explore possible relationships among sleep stages and apneic events and improve on …
Theory Of ‘Selectivity’ Of Label-Free Nanobiosensors – A Geometro-Physical Perspective,
2010
Purdue University - Main Campus
Theory Of ‘Selectivity’ Of Label-Free Nanobiosensors – A Geometro-Physical Perspective, Pradeep R. Nair, Muhammad A. Alam
Birck and NCN Publications
Modern label-free biosensors are generally far more sensitive and require orders of magnitude less incubation time compared to their classical counterparts. However, a more important characteristic regarding the viability of this technology for applications in Genomics/Proteomics is defined by the ‘Selectivity’, i.e., the ability to concurrently and uniquely detect multiple target biomolecules in the presence of interfering species. Currently, there is no theory of Selectivity that allows optimization of competing factors and there are few experiments to probe this problem systematically. In this article, we use the elementary considerations of surface exclusion, diffusion limited transport, and void distribution function to …
Synthesis And Manufacture Of Photocrosslinkable Poly(Caprolactone)-Based 3d Scaffolds For Tissue Engineering Applications,
2010
University of Texas at El Paso
Synthesis And Manufacture Of Photocrosslinkable Poly(Caprolactone)-Based 3d Scaffolds For Tissue Engineering Applications, Nathan Jonathan Castro
Open Access Theses & Dissertations
It is known that the body can efficiently repair hard tissue (bone) micro fractures by suturing the defect through the deposition of minerals resulting in an area that is stronger post-injury. Larger defects, however, generally cause more trouble since the body is incapable of repairing them. Bone defects can occur as a result of congenital abnormalities, trauma, or disease. Traditional methods for addressing these defects have involved the use of acellular cadaverous bone or autologous bone. Both contain innate problems associated with them; the former method can result in disease transmission, as well as very low integration with the host …
Prediction Of Brain Tumor Progression Using A Machine Learning Technique,
2010
Old Dominion University
Prediction Of Brain Tumor Progression Using A Machine Learning Technique, Yuzhong Shen, Debrup Banerjee, Jiang Li, Adam Chandler, Yufei Shen, Frederic D. Mckenzie, Jihong Wang, Nico Karssemeijer (Ed.), Ronald M. Summers (Ed.)
Electrical & Computer Engineering Faculty Publications
A machine learning technique is presented for assessing brain tumor progression by exploring six patients' complete MRI records scanned during their visits in the past two years. There are ten MRI series, including diffusion tensor image (DTI), for each visit. After registering all series to the corresponding DTI scan at the first visit, annotated normal and tumor regions were overlaid. Intensity value of each pixel inside the annotated regions were then extracted across all of the ten MRI series to compose a 10 dimensional vector. Each feature vector falls into one of three categories:normal, tumor, and normal but progressed to …
Prostate Cancer Region Prediction Using Maldi Mass Spectra,
2010
Old Dominion University
Prostate Cancer Region Prediction Using Maldi Mass Spectra, Ayyappa Vadlamudi, Shao-Hui Chuang, Xiaoyan Sun, Lisa Cazares, Julius Nyalwidhe, Dean Troyer, O. John Semmes, Jiang Li, Frederic D. Mckenzie
Electrical & Computer Engineering Faculty Publications
For the early detection of prostate cancer, the analysis of the Prostate-specific antigen (PSA) in serum is currently the most popular approach. However, previous studies show that 15% of men have prostate cancer even their PSA concentrations are low. MALDI Mass Spectrometry (MS) proves to be a better technology to discover molecular tools for early cancer detection. The molecular tools or peptides are termed as biomarkers. Using MALDI MS data from prostate tissue samples, prostate cancer biomarkers can be identified by searching for molecular or molecular combination that can differentiate cancer tissue regions from normal ones. Cancer tissue regions are …
