# BME100 f2014:Group18 L1

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# LAB 1 WRITE-UP

Mini-problem: This semester, you and your team are assisting a graduate student, Kristen, in a research lab. You are studying the effects of inflammation, but the lab is short on cash. You must determine the lowest possible dose of an inflammation inducing agent (lipopolysaccharide) to increase a newly discovered inflammatory protein (Inflammation) in the elderly. The protein is measured in blood samples using ELISA. Prior work as shown that 10mg pill of lipopolysaccharide can increase protein levels so this is a good starting point.

Assignment:
1. What are your independent and dependent variables?
a. How many groups? b. How many subjects/group?
3. How will you select your subjects?
4. What are some of the potential sources of error or biases that could affect your results and how would you control for them?

## Independent and Dependent Variables

Independent variable: lipopolysaccharide-This is the variable that is changed by decreasing the dosage input. Dependent variable: Level of inflammation- This is what we are measuring. It is the variable that will change due to the varying amount of lipopolysaccharide that we test, output

## Experimental Design

We will start with the 10mg pill, then test our way down in even increments(ie in 2 mg increments). We will have Group A-10 mg, Group B-8mg, so on and so forth until we are at Group E-2mg. We will then monitor the protein levels everyday for a month or until noticeable changes in the protein levels happen. Group A, where the subjects will be receiving the 10mg pill, will act as the control group because that is the dosage that is currently being used and can act as a base for the recorded protein levels data. Finally, we can determine the point that the pill no longer increases inflammatory protein(Inflammation).

Groups

We picked 5 groups incremented at even numbers(ie 2,4,6..) so that we could have multiple groups evenly spaced out. The groups would be evenly dispersed allowing us to accurately measure the impact of changes of lipopolysaccharide on inflammation levels. Each group will have the same sample number to provide an equal number of data from subjects regarding lipopolysaccharide effectiveness.

Age

We have determined "elderly" age to be between the ages of 60 to 100. We will select both male and female subjects with history of inflammation. We will also pick able bodied, as well as handicapped elderly people.

Number of subjects per group

We will pick 40 subjects per group. This is because we will have 10 subjects per factor. Therefore, we will have 10 subjects for male, 10 female, 10 handicapped, 10 able bodied. All 40 subjects will vary between the ages of 60 to 100 with previous inflammation history.

## Subject Selection

We will select subjects with varying inflammation issues. Also, we are selecting males and females to weed out that bias, along with picking various ages. Group A, receiving the 10mg pill will be our control in this experiment. Everything will be kept constant except the mass of the pill. Our randomization process has been determined by selecting 10 subjects per factor, resulting in a total sample size of 40 subjects per group. Participants will be selected at random out of a larger volunteer pool group.

## Sources of Error and Bias

This would included any pre-analytical errors which would occur before the lab started where the experiment's execution held a flaw. This would include but is not limited to lab results being misinterpreted and led to a choosing of a subject that did not meet the conditions of the subject group, if subjects for the groups did not have randomized traits which would then limit the testing population of the experiment, ordering the wrong test on the patient therefore ending the validity of the data found, and any monitor errors found by discrepancies within the laboratory team members which would cause inaccuracies in collecting the data. The experimental plan and data that is collect should be done so identically as to the control group, Group A, which is receiving 10mg of the medication. This way even if the data collected in invalid it will still reliably display the effects of the pills on a certain factor of the subjects' system.