BME100 f2015:Group1 1030amL1

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Contents

OUR TEAM

Name: Matt Chrest
Name: Matt Chrest
Name: Nichole Torgerson
Name: Nichole Torgerson
Name: Lindsey O'Brien
Name: Lindsey O'Brien
Name: Jacob Aperi
Name: Jacob Aperi
Name: Michael "Otis" Clyne
Name: Michael "Otis" Clyne
Name: Alarmel Sira
Name: Alarmel Sira

LAB 1 WRITE-UP

Independent and Dependent Variables

Independent Variable: Dosage of lipopolysaccharide(LPS) administered, because we need to find a smaller dosage of LPS to be used for the lab. LPS is the varying amount in our experiment. 
Dependent Variable: Increase or decrease of Inflammotin concentration in the blood, because the level of Inflammotin is varied based on our dosage.

Experimental Design

Our Experiment will consist of 4 different groups, divided up by dosage size. Since it is known that 10mg of the drug produces inflammation, our dosages are marked down in increments of 2mg, in order to find the minimum dosage needed for inflammation. Each group's levels of the inflammatory protein will be measured before taking the pill in order to get a baseline for our subjects. Subjects' Inflammotin concentration will be measured at two hour increments for the following six hours to see how the subjects' Inflammotin levels are affected by Lipopolysaccharide. The subjects' Inflammotin levels will be measured by blood drawn at the 2 hour increments. We use 25 subjects per group in order to have a varied data set, but not a biased data set.


Groups

1. 2mg of lipopolysaccharide

2. 4mg of lipopolysaccharide

3. 6mg of lipopolysaccharide

4. 8mg of lipopolysaccharide

Age
65-85 years


Number of subjects per group
25





Subject Selection

100 people between the ages 65-85. Randomly selected individuals for randomized ages. Randomly select numbers out of a hat, then give the predetermined dose to the subject. The randomization eliminates bias of the data. Exclude subjects that could cause any possible errors according to "potential sources of error" section.





Sources of Error and Bias

Possible sources of error are factors that could interfere with Inflammotin concentration in the blood. Examples are general health factors (i.e. weight and previous illnesses), is if the subject is taking anti-inflammatory drugs and gender.

A subject's health could affect Inflammotin levels because a heavier or more ill subject could require a higher dosage of lipopolysaccharide to achieve the same increase of Inflammotin levels. A subject taking anti-inflammatory drugs might show no response to being given certain (lower) dosages lipopolysaccharide, which could significantly skew data. Males and females may have different reactions to lipopolysaccharide causing them to require different dosages of lipopolysaccharide to achieve an increase of Inflammotin.

Randomization when providing the dosages of the pills will help eliminate the outliers and reduce the skew of data.






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