BME100 f2013:W1200 Group6 L1

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Owwnotebook icon.png BME 100 Fall 2013 Home
Lab Write-Up 1 | Lab Write-Up 2 | Lab Write-Up 3
Lab Write-Up 4 | Lab Write-Up 5 | Lab Write-Up 6
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Name: Nayobe Bivins
Name: Tracy Lopez
Name: Jenny Chen
Name: Nick Kilpatrick
Name: Alexander Bugarin


Independent and Dependent Variables

The independent variable in this experiment is the dosage of the inflammation inducing agent (lipopolysaccharide) given to each group.
The dependent variable in this experiment is the amount of the inflammatory protein (Inflammotin) found in the blood samples.

Experimental Design

The test will consist of ten groups, each with a different mg dosage of lipopolysaccharide, and one control group. The control group will receive no lipopolysaccharide. Starting at one, each sequential group will have one plus mg of lipopolysaccharide.

Number of subjects per group
Each group will have 100 individuals.
In each group there will be 50 females and 50 males. The groups will vary in ages from 60 - 90 years of age with random selection of participants.

Experimental Procedures
Subjects will receive a dose of inflammation inducing agent (lipopolysaccharide) daily following a strict schedule.
Blood samples will be taken from each subject 6 hours after dose using ELISA.
Subjects will take their assigned dosage at 2pm each day for six weeks.
Subjects will not be told what their dosage is.

Subject Selection

Age ranges of each group
Gender/ethnicity distribution
Health record/history

Sources of Error and Bias

• Unknown previous medical symptoms which could be controlled by screening the medical history of all participants prior to conducting the experiment. Similarly, medications taken before/during the experiment could interact with the inflammation inducing agent (lipopolysaccharide). So we will ask our subjects to stop taking their medications.

• Laboratory equipment malfunction or contaminated materials/samples. These could be avoided if we double-check our equipment prior to conducting the experiment and practice being a good observant.

• Vast differences in age groups between experimental groups. By looking at the age distribution before beginning, adjustments can be made if necessary.