1. Jay Maier Central Catholic High School

2. Type 1 Diabetes Immune system kills Beta cells that make insulin. Synthetic insulin is used to allow cells to gain access to glucose. It is difficult to know how much insulin is needed to cover a given amount of food. This insulin requirement varies with time of day, exercise, etc. It would be extremely useful to have a tool for discovering a patients metabolic state.

3. Raman Spectroscopy Technique used to study chemical bonds in a sample. 1. Laser is fired at a sample on a reflective slide. 2. Lens collects reflected light. 3. Wavelengths close to laser are filtered out. 4. Intensity of reflected light is plotted on a graph.

4. Purpose To investigate possible variations in Raman spectroscopic peak intensities among diabetics. To provide groundwork for future studies on this topic. To eventually develop a tool that could detect a patient’s insulin requirement

5. Null and Alternative Hypothesis Null- That no significant variations in Raman Spectroscopic peak intensities will be found between patients with insulin dependent diabetes mellitus (Type 1 Diabetes) and a control group over the course of the day. Alternative- That significant variations will be found between the diabetic patient and the control group over the course of a day.

6. Materials Glucometer (Blood Glucose Meter) Glucometer test strips Lancet gun Lancets Falcon II Raman Microscope Reflective slides Alcohol swabs Type 1 Diabetic test subject Non-diabetic control subject

7. 9. Zoom in to 50x, keeping the view on a clear area of saliva. 10. Close machine door and set to Dispersive Spectroscopy mode. 11. Under hardware, turn on laser and open shutter. 12. Under Raman Spectroscopy, set exposure time to 1 second, with 1 average. 13. Click “Live”, and make sure the graph looks moderately like the one below. 14. Set exposure time to 30 seconds, with 3 averages, and click “Snap”. 15. Save snapshot and repeat process until all samples have been tested. Procedures 1. Wash out mouth with water. 2. Check capillary blood sugar (CBS) 3. Once fresh saliva is generated, transfer saliva from mouth to reflective slide. 4. Mark slide with CBS, time of day, activity level, and control/test subject. 5. Repeat until sufficient data set is obtained. 6. Place slide on table of Falcon II Raman Microscope. 7. Set machine on Bright field Reflectance. 8. Use video camera to position slide so that a clear area of saliva is in view.

8. Data Analysis 1. To analyze data, a series of nine peaks were chosen from mean data graph by height. 2. Intensity values of these peaks were found for both the control and the diabetic at three times of the day: morning, afternoon, and evening. 3. P-values were obtained from each pair of diabetic and control sets, at each peak at different times of day.

9. Peak Intensity: Control Vs. Diabetic (Morning) Peak Wavelength (cm⁻¹) Intensity P= 0.39 P= 0.007 P= 0.003 P= 0.7 P= 0.59 P= 0.52 P= 0.52 P= 0.002 P= 0.18

10. Peak Intensity Control Vs. Diabetic (Afternoon) Peak Wavelength P= 0.11 P= 0.91 P= 0.87 P= 0.52 P= 0.57 P= 0.6 P= 0.5 P=0.3 P= 0.9 Intensity

11. Peak Intensity Control Vs. Diabetic (Evening) Intensity Peak Wavelength P= 0.9 P= 0.16 P= 0.37 P= 0.34 P= 0.27 P= 0.3 P= 0.35 P= 0.14 P= 0.24

12. Conclusions The null hypothesis was rejected because in the morning, significant variations were found between the control and diabetic subjects in peaks at 994cm⁻¹, 1039cm⁻¹, and 3057cm⁻¹.

13. Limitations and Extensions Only one subject from each group was tested. Water from the sink was used to wash out subject’s mouth. Multiple readings could be taken from each saliva sample. This experiment could be expanded by using a wider range of subjects, both diabetic and control. Other variables could be analyzed such as activity level or CBS.

14. References http://www.dmsjournal.com/content/2/1/48 http://en.wikipedia.org/wiki/Raman_spectroscopy http://www.springerlink.com/content/j74464ug725q3 038/ http://www.springerlink.com/content/j74464ug725q3 038/ http://en.wikipedia.org/wiki/List_of_elements