BME100 f2014:Group27 L1

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Our Team (Group 27)

Lab Report 1: Inflammation

Independent and Dependent Variables

The independent variable is the amount of inflammation inducing agent (lipopolysaccharide). The dependent variable is the the amount of inflammatory protein (inflammotin). The lipopolysaccharide dosage is being varied, and this variation will affect the amount of inflammotin in the patient (the inflammotin is dependent on the amount of lipopolysaccharide). Thus, the lipopolysaccharide is the independent variable, and the inflammotin the dependent variable.

Experimental Design

Overview

Group 1 will be prescribed a control with 0 mg of lipopolysaccharide. Group 2 will be prescribed a 2 mg dosage, group 3 a 4 mg dosage, group 4 a 6 mg dosage, group 5 a 8 mg dosage, and group 6 a 10 mg dosage. The patients will take their dosages for the prescribed amount of time. At the end of the prescription period, which would be 4 weeks, we will use an ELISA test to measure the amount of inflammotin in each patient's blood.

Groups

We will have 6 different groups. Our first group will be the control; they will be given 0 mg of the inflammation agent to provide a base which we can use to compare the other groups to. The second group will be given 2 mg, the third group will be given a 4 mg dosage, the fourth a 6 mg dosage, and the fifth an 8 mg dosage. The sixth group will be given a 10 mg dosage which will act as a baseline as 10 mg dosage is the lowest known dosage to effectively produce more inflammotin in the body. These small increases in dosage will help determine the minimum amount of the agent that is required before diminishing returns occurs.

We will have 10 subjects per group for a total of 60 subjects. Each group will consist of 5 males and 5 females to help determine the effect of lipopolysaccharide on each gender.

Subject Selection

We would go to 6 different primary care physicians, and from each request 10 subjects: 5 males, 5 females, and all 60 years or older. This would give us our total of 60 subjects. The age requirement would help give us the most accurate results possible for the targeted consumers of this drug (elderly patients).


Sources of Error and Bias

Possible biases include the discrepancy between the kind of people who agree to this study, leading to a less diverse experimental pool. Similarly, a physician's bias may come into play if they recommend the study to certain "favorite" patients and deny others. Ideally, we would be able to personally ask the patient's participation to take away any bias that another person--the doctor--could add to the process. Additionally, a patient may overtake or undertake their dosage of the drug, leading to poor experimental results. To eliminate the bias that people who agree to this study will be fairly similar, the question could instead be a blind study so that not everyone is scared off. This also means that bias is also eliminated among the patient because now they are unaware of the intended results. With the issue of the doctor playing favorites we would request to handpick our patients/subjects to guarantee a wide range of people and randomization. This would lead to better results, because now we have a base of patients who were picked without bias. To control the issue that a patient may undertake or overtake their dosage they will be monitored to make sure they abide by the structure of the experiment.