BME100 s2015:Group3 9amL1

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Owwnotebook icon.png BME 100 Spring 2015 Home
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Emily Santora
Christina Salas
Steven Mills
Austyn Howard


Independent and Dependent Variables

The independent variable would be the dosage, measure in milligrams, of the inflammatory drug (lipopolysaccharide), because this variable is purposefully changed during the experiment. The dependent variable would be the protein levels, measured using blood samples, because the protein levels are affected by the change in lipopolysaccharide dosage.

Experimental Design


Three groups of ten will be tested to determine the lowest possible dose of lipopolysaccharide to increase a newly discovered inflammatory protein found in the elderly. Each group will consist of 5 males and 5 females. Subjects of group 1 will be given a placebo to measure natural levels of Inflammotin, this will be the control group. Group 2 will be given 5 mg of lipopolysaccharide and group 3 will be given 10 mg of lipopolysaccharide.


Ages 60-85

Number of subjects per group

10 subjects per group to provide variability for testing date, but no more than 10 test subjects due to insufficient funds for research.

Subject Selection

- Elderly home volunteers with no underlining health conditions.

- Volunteers who are not taking anti-inflammatory medications.

- Ages 60-85 years old.

Sources of Error and Bias

We have five sources of error. Diet, prior medication, and genetics.

  1. Diet
    • We can minimize this variables impact on the experiment by picking our own diet that will not raise or lower the protein lipopolysaccharide in the test groups, nor will it inhibit the absorption of the medication into the bloodstream.
  2. Prior Medication
    • We can survey our target groups to see what medications they take and whether or not the medications will effect the overall outcome of the experiment.
  3. Genetics
    • We can select our study groups based on the amount of protein in their bloodstream measured using ELISA. The less protein that is found naturally in the person's bloodstream, the more likely they will be chosen as a candidate.
  4. Medical Conditions
    • We can again survey the target population to see what medical conditions they have and then we will see if the conditions will interfere at all in the experimentation process.
  5. Gender
    • We can prevent this source of error by having an equal amount of males and females in the test groups.
  6. Human Error
    • Incorrect dossing
      • Double check the formulas, and check the potency of the medication.
    • Test subjects not taking the medication at the prescribed time
      • Have the person take the medication under the supervision of a lab worker.
    • Error in data collection
      • Double check the data, and make sure that the data collected is accurate.