BME100 f2014:Group2 L1

BME 100 Fall 2014	Home People Lab Write-Up 1 | Lab Write-Up 2 | Lab Write-Up 3 Lab Write-Up 4 | Lab Write-Up 5 | Lab Write-Up 6 Course Logistics For Instructors Photos Wiki Editing Help
OUR TEAM LAB 1 WRITE-UP Independent Variable The independent variable is the amount of lipopolysaccharide, because the dosage of lipopolysaccharide must be changed to determine inflammotin production in elderly. Dependent Variable The dependent variable is the amount of inflammotin, because the amount of inflammotin produced in elderly is being measured by the experiment. Experimental Design Groups There will be four groups: one group will consist of healthy elderly volunteers, the second group will consist of unhealthy elderly volunteers, and the two other groups will be the control groups. The reasoning for this is to determine whether health is a factor in the amount of infammotin produced by a certain dosage of lipopolysaccharide. The exclusively healthy and unhealthy groups will receive a dosage of 2 mg, 4 mg, 6 mg, 8 mg, and 10 mg of lipopolysaccharide in that order. The reasoning for this is that evidence shows that a 10mg of lipopolysaccharide can increase protein levels, so increasing up to 10 mg will test how low of a dosage will produce inflammotin. The control group receives a dosage of 10 mg to produce a data set where the expected outcome is known. The healthy group will consist of twenty-eight elderly people, half male and half female. The unhealthy group will consist of twenty-eight elderly people, half male and half female. The reasoning for this is twenty-eight is a large enough group to allow for discrepancies in the data and minimize error, but a small enough group to keep costs down. Testing both males and females allows to test for the differences between genders. Both control groups will consist of twenty-eight elderly people. There will be two control groups, one healthy and one unhealthy, with twenty individuals each, ten male and ten female. There will be two control groups, one healthy and one unhealthy, with twenty individuals each, ten male and ten female. The control group provides a data set that gives expected values for the experiment. Subject Selection Elderly people in the age groups of sixty to eighty will be selected randomly. The test subjects will be chosen randomly from different geographic areas, to prevent testing of people from just one background. For the unhealthy group, people will be selected with a variety of illnesses, to prevent testing the effect lipopolysaccharide has in inflammotin production in just a few particular illnesses. Randomly selecting the age, location, and race of the individuals tested will prevent experimental bias. The inclusion criteria for the healthy group is individuals between the age of sixty to eighty. The exclusion criteria for the healthy group is the individuals must not have a diagnosed medical condition. The inclusion criteria for the unhealthy group is individuals between the age of sixty to eighty with a diagnosed medical condition. The exclusion criteria for the unhealthy group is individuals that are healthy. For providing sufficient data to compare against the healthy and unhealthy group, there will be two control groups of 20 for both healthy and unhealthy, ten male and ten female all at age seventy since that is the average of our test group range. They will be given the 10mg dosage of lipopolysaccharide as the control amount, because prior studies have proven this dosage increases protein levels. Sources of Error and Bias One potential source of error would be if the test subject did not wait for enough time to pass in between dosage acceptance, or waited too long. Another source of error is the test subject not taking the correct amount of lipopolysaccharide.In order to prevent both of these errors the test subjects will be monitored and required to come into the lab to receive their next dosage. A third possible source for error is an error in the ELISA testing. Errors in ELISA testing can be prevented by using duplicates for all substances and making note of large differences in the results of the identical substances. Another way to prevent error in ELISA testing is to test multiple dilutions of every sample.