BME100 f2014:Group1 L1

BME 100 Fall 2014	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: Hawley Helmbrecht Name: Sarah Fakhoury Role(s) Name: Prerna Gupta Role(s) Name: Jonathan Riecker Name: Michael Pineda Role(s) Name: Timothy Black LAB 1 WRITE-UP Independent and Dependent Variables Independent: 10 mg, 8 mg, 5 mg Lipopolysaccharide dosage ◦To induce inflammotin to be released, 10 mg is the dosage known to be effective. In order to determine the lowest possible dosage, 10 mg is applied, then decreasing the dosage to determine the lowest possible dosage still capable of increasing inflammotin Dependent: Amount of Inflammotin (Inflammatory Protein) ◦To determine amount of inflammotin being released at each dosage level, in order to find the lowest possible dosage still capable of increasing inflammotin Experimental Design Groups Four groups: -Control Group -Not on the LPS Three groups of randomized elderly ages One group receives 10 mg, another 8 mg, another 5 mg Age The subjects will be of elderly age (65+ years old). Number of subjects per group There will be 16 subjects in each group. Subject Selection The 4 groups being tested should be 65 years or older to be considered “elderly”. The test subjects should be a mix of nationalities and ethnicities. The 16 people in each group will be chosen at random. Each person will be given a number. However, the females would be given an even and the males would be given an odd. Each group will have 8 even numbers and 8 odd numbers picked randomly. Sources of Error and Bias Some possible sources of error could have been caused by patients' preexisting health conditions and variety of lifestyles, which may skew a controlled lab experiment, and the impossibility to control every aspect of the patients' lives may cause unexpected variables and effects. Controls for error can be established in order to reduce the impact and amount of errors present throughout the experiment. In order to ensure that the patients do not have preexisting conditions that may affect results, every elderly person taking the lipopolysaccharide should have their medical history pre-examined. It would also be beneficial for the test subjects to be given routine medical tests before they are chosen as a subject in the experiment. Every person has a different lifestyle which can affect the results of an experiment and it is impossible for a researcher or doctor to monitor and control every second of a person’s life. To counterbalance these existing variables, doctors should make sure that each patient takes their prescribed pills regularly and does not skip a pill or frequently vary the time at which the pill is ingested. To limit the number of variables that occur from the patients' lives without heavily intervening in the natural course of the patients’ days, doctors should ensure that each patient receives the same treatment in the exact same controlled method and that there should be some kind of unobtrusive monitoring device to analyze how the drug is effecting the patient. Along with sources of error, there are also many sources of bias that can cause unreliability within the experiment. Some examples of problematic bias are selection bias, measure bias, and intervention bias. Selection bias occurs by the method the groups were selected and can result in groups becoming an inaccurate representation of the actual population of interest. In order to overcome selection bias, the groups must be effectively randomized and should incorporate representative members of both genders and a variance in ethnicities/nationalities. Measure bias can cause inaccuracies in the measurements taken in the experiment and can be caused by a faulty medical device. All medical devices should be checked for accuracy so that there are no accidental discrepancies within the experiment. Intervention bias is caused when too much medical or research intervention occurs in the patients’ lives, causing the experiment to no longer represent the effect of the drug in a natural setting. Intervention bias can be overcome by avoiding excessive medical device intervention, unless absolutely necessary to perform procedures, obtain results, or administer drugs and by allowing the people within the testing groups continue their lives as naturally and normally as possible.