BME100 f2016:Group11 W1030AM L6

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Contents

Banana Nation

Andrea Grio
Andrea Grio
Sonya Baran
Sonya Baran
Joshua Hsu
Joshua Hsu
Jake Perrine
Jake Perrine
Saul Vidrios
Saul Vidrios

gPCR

LAB 6 WRITE-UP

Bayesian Statistics

Overview of the Original Diagnosis System

Our class used 15 teams, each consisting of 6 students, each diagnosed 30 patients. Three samples were taken from every patient, in an attempt to reduce error, and tested within the PCR machine. The patient's samples were compared to two control groups: one containing the SNP disease and one without it. The software used to compare thee samples, ImageJ, had controls in order to reduce the error within the diagnostic process. It included samples of purified water and a sample with an excess of SYBR Green. We also took 3 pictures for use in ImageJ's analysis software in order to ensure accuracy.

The PCR test results came back as either positive, negative, or inconclusive. Our class had a total of 78 PCRs taken, where 23 were tested positively, 47 were negative, 4 were inconclusive, and 4 came back blank. When applying this to the 30 patients, 7 were positive, 16 were negative, 3 were inconclusive, and 4 were left blank. Errors that occurred throughout the class may have included failure to transfer ever droplet of the samples into the PCR tubes, or incorrect use of ImageJ.

What Bayes Statistics Imply about This Diagnostic Approach


Calculation 1 measured the probability of getting a positive test conclusion given a positive PCR reaction. The analysis of calculation 1 showed that less than 50% of the time the test would give an appropriate result for the positive PCR reaction. This is not extremely reliable since the test is only correctly showing up half the time. Calculation 2 measured the probability of getting a negative test conclusion given a negative PCR reaction. After analysis, the probability of receiving the right conclusion was very high. The negative PCR test is reliable since the test is going to be correct almost 100% of the time.


Calculation 3 was measuring the probability of developing the disease given a positive test result. With analysis, the value came out to a little under 50%. This is very unreliable since it is going to be incorrect half of the time. Half of patients who receive a positive test conclusion will not develop the disease. Not developing the disease is a good thing but the positive test result brings extreme anxiety and lowers the quality of life of the patient. Calculation 4 was measuring the probability of not having the disease given a negative test result. The probability of not having the disease came out to be 99%. This test is extremely reliable since it is going to be correct nearly all the time. This is the ideal probability that the tests should have.


Possible Error:

  • The calibration of the fluorimeter may have been completed incorrectly. The solution made for the calibration was incorrect since it did not contain water
  • Improper pipetting techniques. These can include adding too much or too little buffer/SYBR solution to the PCR sample, also mixing the wrong buffers/SYBR solution with the wrong PCR samples.
  • The fluorimeter did not have a phone stand it very difficult to center the phone camera on the drops when taking pictures for ImageJ. The fluorimeter also did not have a way to block out all the light when taking the picture.

Intro to Computer-Aided Design

3D Modeling

Our team used SolidWorks in order to make the necessary changes. SolidWorks from the onset is a very powerful program and allows a great deal of flexibility and freedom when it comes to eats capabilities. However, it seems to have a fairly large learning curve. In SolidWorks, like any design class, seems to have design fundamentals that need to be followed in order to make full use of the program. Furthermore, it's difficult to find any real help online as the everyone's questions are very specific and broad when it comes to the projects each individual is working on further reiterating the need to learn the fundamentals of SolidWorks as a tool in an a BME's skillset.

Our Design


New Heat Sink Design: Image: Tubed new.gif

New Assembled PCR machine: Image: New thing.gif

Old heat Sink: Image: Heat Sink Old.png

New heat Sink: Image: Heat Sink Retubed.png


New PCR Machine with New Cooling Component: Image: Full On PCR.png

We chose this new design due to the increased cooling and control of temperature we would gain from a liquid-cooled device. The original OpenPCR design used a Copper heat sink with a fan. This design with liquid cooled tubing to allow for an even transfer of heat.



Feature 1: Consumables

gPCR kit includes:

  • PCR Mix
  • Primer Solution
  • SYBR Green Solution
  • Buffer
  • Micropipette
  • Micropipette tips


Feature 2: Hardware - PCR Machine & Fluorimeter

In order to better transition the temperature changes in the PCR machine, we've decided to add two new components to the existing concept. First, in order to significantly decrease the amount of time the reaction cools down inbetween cycles, we've integrated a water cooling system to the component where the reaction takes place. Water cooling is a technique used to regulate temperature in machines, particularly computers. Water cooling will also compliment the heat sink and fan by removing heat from the system.

Furthermore, we've implemented insulation barriers around the thermocycler. Insulators help trap heat in the thermocyclers, ensuring that heat doesnt escape from the system, and that reactions stay closer to the temperature they need to be at.


Additionally, we've made significant changes to the fluorimeter set up. Instead of resting on the table, the flourimeter will now rest on a new box with stands and an entry at the bottom for their hands. A clear plastic front so the person can work. Additionally a shroud to cover the plastic front when pictures are needed.




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