BME100 f2013:W900 Group18 L1

BME 100 Fall 2013	Home People 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 Photos Wiki Editing Help
OUR TEAM Name: Daniel McDermand Name: Nick Vale Name: Dylan Debruin Name: Matt Hanson Name: Kirstin Peters LAB 1 WRITE-UP Independent and Dependent Variables Independent Variable: The dosage of the inflammatory inducing agent (lipopolysaccharide) given to the elderly subjects. Dependent Variable: The amount of inflammatory protein (Inflammotin) found in the blood. Experimental Design The groups will be organized based on the amount of lipopolysaccharide they are receiving. The highest level of drug given will be 10mg, and the other four levels will be 1mg less of the drug each time. Level 1 - 10mg (control) Level 2 - 9mg Level 3 - 8mg Level 4 - 7mg Level 5 - 6mg There will be ten subjects per level of drug given. The groups of subjects will be assigned a level and then given daily doses of the drug for suitable period of time. (i.e. a week or a month, depending on how quickly the drug takes effect.)The patient's blood will be drawn and tested once a day using ELISA to see how the protein levels are changing from the drug. This data will then be analyzed to determine the lowest amount of drug that can be administered and still cause a change in protein levels. Matt helped write this section. Subject Selection Our subjects would include a random selection of people between the ages of 60 and 100 without any previous medical conditions or currently taking any medication. Sources of Error and Bias With any group of people, there will always be lurking variables present. For example, a subject in the experiment might believe they are a healthy individual, but in reality, are unaware of health conditions that may alter the results of this particular experiment. Although the subjects we selected for this experiment were required to be on no medication and have no previous health concerns, bias may still be present if, for example, a person believes they are healthy when they have health issues. A person may be in shape in their mind (obvious bias), but overweight or obese in reality. A person that smokes or previously smoked may be unaware of the effects, and think that there were no effects from the nicotine. Problems with the blood may also be undetectable, as iron deficiency or blood disease are often impossible to detect immediately after the problem arises, so if the subject has not had a recent medical exam, these many health concerns may be prevelant. Like any experiment, error may result from observational or instrumental influence. If the equipment is used improperly, results would be skewed and not appropriate for the specific experiment. Human error may result in inaccurate measurements, which could also skew data.