BME100 f2015:Group13 1030amL1

From OpenWetWare
Jump to: navigation, search
Owwnotebook icon.png BME 100 Fall 2015 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
Course Logistics For Instructors
Wiki Editing Help
BME494 Asu logo.png


Name: Kaylee Antill
Name: Drew Worman
Name: Jonah Brosemann
Name: Tanner Ivey
Name: Bramuel Simiyu
Name: Christopher Chen


Independent and Dependent Variables

Independent Variable: Dose of Lipopolysaccharide (LPS)

◦Reasoning:This is the independent variable, because we are testing the effects of different doses of LPS on the levels of inflammotin, a newly found inflammatory protein, in elderly people. In other words, it is the variable that we are actually directly changing by ourselves.

Dependent Variable: Amount of Inflammotin

◦Reasoning: This is the dependent variable because we are it is affected by the changing of LPS dosages and is the measurement we are actually making at the end of the experiment.

Experimental Design


•Group 1: 0 mg LPS (control/placebo)

•Group 2: 2.5 mg LPS

•Group 3: 5 mg LPS

•Group 4: 7.5 mg LPS

•Group 5: 10 mg LPS

◦Reasoning: Because the budget for carrying out the experiment is low, we decided on dosage intervals of 2.5 mg. This results in five groups covering an adequate variety of doses of LPS, while hopefully conserving funds that can be used to solve problems that might arise during the conducting of the experiment. The 0 mg LPS group gives us an idea of the ordinary inflammotin levels in the elderly, while the 10 mg group is the baseline dose for testing the minimum amount of LPS needed to raise inflammotin levels.

Must be between 65-75 years old

◦Reasoning: The minimum age requirement for applying to Medicare is 65 years of age and the life expectancy is 78.8 years in the United States. We initially considered an age range of 65 to 80 based on this data. However, taking into consideration our limited funds and the greater possibility of health problems at higher ages, we established an upper age limit of 75. This smaller range serves to decrease the minimum required group size (since there is probably less variation in subjects age 65-75 compared to 65-80) and reduce the chances of health issues in the subjects that could affect results and data collection.

Number of subjects per group
15 randomly selected people of different ages and genders

◦Reasoning: As the age range of our subjects is 10 years, we needed fairly sizable groups to adequately represent this range in each group. We also decided to randomize groups without specifically dividing subjects by traits such as gender. As we are not certain about how such traits might influence the effects of LPS, we decided that a high degree of randomization would be most likely to create similar groups without our biases involved.

Subject Selection

The subject must be between 65 and 75 years of age as that is our established range for "elderly." They must go through a medical examination and health background check to screen for possible health issues/complications that could affect the administration of LPS or collection of data (potential subjects would be excluded, for example, if they had a serious chronic illness, inflammation problems, or blood-related diseases). By screening for potential health issues before conducting the experiment, many potential sources of error could be eliminated. To reduce the possibility of bias on our part, the subjects cannot be anyone that any of us know personally. Our broad initial inclusion criteria (simply being 65-75 years old) allows for a large degree of randomization in our groups, while health checks help to prevent problems that could arise later in the experiment due to the condition of our subjects.

Sources of Error and Bias

•Medication that subjects are already taking- Elderly subjects are likely to be taking a variety of different medications already. Some medications could interfere or react in unpredictable ways with the LPS we are administering.

•Diet-Diet plays an important role in the overall health of the subjects, and the health of the subjects could have an impact on factors we are trying to measure (inflammotin levels taken from blood samples).

•Activity level- As determined by questions such as "Can these people still get up and move around?" or "Do they rely on someone else to care for them?" Once again, this could indicate the overall healthiness of the subjects, which could affect the ability to collect results or the reaction of the subject's body to LPS.

•Allergies-If a subject has an allergic reaction to the LPS it could cause put their life at risk or result in complications in measurement and inaccurate data.

•Mistakes recording data- Errors made during the experiment (incorrect administration of LPS dosages, measurements being slightly off, etc.) and errors made during data collection could skew results.

•Ethnicity- Factors such as ethnicity could affect how the subject's body reacts to LPS. If these differences are significant, then having too much/too little of certain ethnic groups would result in a less than ideal sample group.

•Abusive Habits (e.g. use of alcohol, tobacco)- Abusive habits can have a debilitating effect on the subject's circulatory system. As we are measuring protein levels based on blood samples, this could cause measurement issues.

Controls for sources of error: Issues such as medication usage, diet, activity level, allergies, and abusive habits would be screened for before actually conducting the experiment. A health background check and medical examination would be given to each prospective subject and some could be rejected from being part of our groups if it was determined that their health level could cause errors in our results. We would try to prevent issues arising from factors such as a lack of ethnic balance in our group through simply randomizing groups instead of specifically placing people into certain groups based on ethnicity. Such randomization would give the greatest chance of having homogeneous test groups without introducing our own biases into group composition.