Here is display the investigations completed in the different fields such as Computer Science1, Genomics2, Biology3, Nanotechnology4, and Geographic Information System (GIS)5.
WHO’S THAT NERD? 1
Today everyone has cell phones, tablets or some kind of electronic equipment they can carry everywhere. This creates a motivation to develop an application for pre-algebra and algebra in which the user can study and practice. Through this app the user can acquire more knowledge in the area of algebra. This was developed for the Windows Phone7 using Visual Studio for Windows Phone and C# as the language for the source code. Expression Blend was used for the design of the application.
COMPARISON OF PIK3C2A AND PIK3C2B PROTEINS IN OVARIAN CANCER 2
Ovarian cancer is a disease that develops in the female reproductive area after menopause. It’s the third most common cancer in woman and it can be treated but not cured. It is still unknown what really caused this cancer but there are some factors that can make it appear such as fertility, infections, obesity and malignant transformation of epithelial cells. PIK3C2A is a protein found in the malignant epithelial cells and the high production of it is a factor of causing the cancer. The symptoms of this disease appear until the cancer is spread. The objectives of this research are to investigate the difference of the proteins PIK3C2A and PIK3C2B, and to find and contrast these proteins by means of bioinformatics tools. The programs used to accomplish this work were GeneDoc, MEGA5 and Visual Molecular Dynamics (VMD).
“YOU ARE WHERE YOU EAT” BLOODMEAL ANALYSIS OF A BOLIVIAN CHAGAS DISEASES INSECT VECTOR 3
Chagas disease is arguable the most serious infectious disease in Central and South America as well as Mexico. It is caused by the parasite, Trypanosoma cruzi, and is transmitted via an insect vector that feeds on vertebrate blood and is commonly referred has the kissing bug. There are around 11 million of people infected in Latin America and 14,000 deaths annually. Bolivia is the most affected country, where as much as 18% of the population may be infected. The community of Zurima has one of the highest infection rates in Bolivia and is mostly populated by indigenous people. Our objectives are to understand the vector feeding and habitat preference to assist vector control and reduce the disease incidence. Using bugs collected by the person hour method from >80% of the houses, DNA was extracted from the insect abdomen. The extracts contain vector and blood meal DNA. Extracted DNA was analyzed using real-time qPCR to assess feeding on human, dog and chicken.Results from the real-time qPCR, were combined them with spatially data (i.e., GPS house locations) using ESRI ArcGIS software. The results indicated that infested and non- infested houses did not differ in proximity to roads. Thirty percent of the insects had fed on dog, 69% on chickens and 1% fed on other animals. Further, infested houses had more dogs, chicken, sheep and pigs than uninfested houses. These results can be used by local health officials and community members to develop vector control strategies.
GROWTH INHIBITION EFFECT IN ESCHERICHIAL COLI (E. COLI) BY THE USE OF GOLD NANOPARTICLES 4
Nanotechnology allows us to develop high performance products. Gold Nanoparticles (Au Np’s) is used for different biomedical applications and to improve medical diagnosis. Its ability to track diseases at early stages had help to improve the medical diagnosis tools in which helps to create new forms of treating directly these diseases (e.g. Tumors, Viruses, Bacteria’s). In this research it’s going to be observed how the Gold Nanoparticles (Au Np’s) affect the growth of the bacteria E.coli using an antibiotic test named Kirby-Bauer. The E. coli bacteria can be normally found in the digestive tract of humans and animals and a person can get infected if it consumes contaminated food with feces, unpasteurized milk products and contaminated water. Initially we started preparing the Gold synthesis in which we use HAuCl4 (salt) and Trisodium Citrate (TSC) that is our Caping and Reducing agent. Once the synthesis is prepared, a characterization of the Au Np’s was made using the Ultra-Violet Vis Spectroscopy (UV-Vis) to determine their size. Later on the E.coli bacteria is culture. After few hours, a second plate was prepared with the Kirby-Bauer method in were the E.coli colonies will be tested by the Au Np’s. Finally the growth inhibition will be measure to determine the effectiveness of the Au Np’s. What we conclude is that Au Np’s didn’t affect the growth of the E.coli.
EDUCATIONAL ATTAINMENT EFFECT ON KENTUCKY OBESITY RATES 5
Obesity can be defined as abnormal fat accumulation present in a person. It is measured using the Body Mass Index (BMI), a number that defines body fatness by calculating weight, height and age. The resulting number defines if a person is Underweight, Normal, Overweight or Obese. There are several factors that contribute to obesity. Lack of physical activity, age, gender, genetics, hormonal problems, and daily routine are some of them. Obese people can suffer different chronic diseases such as Diabetes, Cancer (e.g. Pancreas, Liver) and Cardiovascular Diseases (e.g. Strokes, Hypertension, etc.). We speculated that educational attainment (that is the highest education level that an individual has completed during his life time) has an effect on obesity. Geographic Information System (GIS), which is a unique way to visually observe spatial patterns, was used to determine higher and lower regions of obesity and educational attainment. Using the software of Esri’s ArcGIS we were able to map and calculate the data by using these spatial analytical tools. In order to complete these tasks, data was obtained from the Center for Diseases Control and Prevention (CDC), World Health Organization (WHO), and the United States Census Bureau. These data was added into ArcGIS, respectively, to define witch regions of Kentucky had higher or lower obesity rates. By knowing this, we further performed a Pearson’s Product Momentum Correlation on obesity rates and educational attainment which showed a correlation. We were able to map and analyze the data from different targeted areas, and concluded that the Eastern region of Kentucky has higher Obesity Rates than the Western region. This interpretation implies that having less education results in an increased incidence of obesity.