BME100 f2015:Group15 1030amL6

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BME 100 Fall 2015 Home
Lab Write-Up 1 | Lab Write-Up 2 | Lab Write-Up 3
Lab Write-Up 4 | Lab Write-Up 5 | Lab Write-Up 6
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Name: Paige Williams
Name: Sydney Spicer
Name: Esteban Medrano
Name: Elijah Olivas
Name: Tofi Lautoa
Name: Vishal Giri


Bayesian Statistics

Overview of the Original Diagnosis System

(A)BME100 was assigned the task of testing 34 patients for a specific disease-associated SNP, and the class was divided into 17 teams of 6 students each so each team was assigned 2 patients to test. One person in the group was in charge of labeling and keeping track of the primers, PCR mixes, and controls, and a second person was in charge of using the pipette to make the PCR reaction. For the second part of the test using a fluorimeter, another person in the group was in charge of pipetting the PCR reaction onto the slide while another group member set up the box, height of the stand, and calibrated the phone for the fluorimeter. The rest of the group members were in charge of taking images of the drops in the fluorimeter and analyzing them using ImageJ. (B) In the first half of the PCR test multiple PCR reactions were tested per patient to increase accuracy, for example a PCR reaction was made for a positive and negative control, then three identical PCR reactions were made for patient 1 and three identical PCR reactions were made for patient 2. The positive and negative controls were made to test the patient PCR results against because the positive control contained the desired SNP while the negative control did not. In the second half of the PCR test, ImageJ was used to analyze the drops of PCR reaction, so certain measurements needed to be kept constant for all of the reactions. These measurements included area, integrated density, and mean gray value. For every PCR sample, three photos were taken of the drop in the fluorimeter and this was done to get the clearest image for use in ImageJ. (C) After running all of the PCR reactions, 30 successful conclusions were made on the diagnoses of the assigned patients. 13 patients tested positive for the disease-associated SNP, 17 tested negative for the disease-associated SNP, 2 tests were inconclusive and 2 groups had no test. Since this was the first time many members of our group had used a micropipette there were issues in the beginning with using it correctly and this could have caused inconsistencies in our data. With the fluorimeter, it was difficult to get the phone to focus on the PCR drop and at the right level because the phone sat at an odd angle in the holder. The box that covered the fluorimeter was also inadequate because it was nearly impossible to take a picture on the phone without allowing light into the box, which affected the images of the PCR drops and hence the data.

What Bayes Statistics Imply about This Diagnostic Approach

Calculation 1 gives the probability of a positive test conclusion given a positive PCR reaction and it is implied that the individual PCR replicates were about 77% accurate for concluding if a person has the disease SNP. Calculation 2 gives the probability of a negative test conclusion given a negative PCR reaction and it is implied that the individual PCR replicates were about 89% accurate for concluding if a person did not have the disease SNP. Together, calculations 1 and 2 imply that the individual PCR replicates are reliable for concluding that a person has the disease SNP.

Calculation 3 gives the probability of a patient developing the disease given a positive test conclusion. The accuracy of PCR for predicting the development of the disease was low, near 20%. Calculation 4 gave the probability of a patient not developing the disease given a negative test conclusion. The accuracy of PCR for predicting that a patient will not develop the disease based on a negative test conclusion was very high at almost 100% accuracy. It is hard to determine the reliability of PCR in general for predicting the development of the disease using both calculation 3 and 4 because the two calculations were drastically different. Calculation 3 shows low reliability in diagnosis while calculation 4 shows very high reliability in diagnosis.

Intro to Computer-Aided Design


TinkerCAD is a much simplified version of SolidWorks, although not necessarily for the better. The software makes use of pre-made shapes and allows the connection of different designs. Also, the ability to add letters and numbers simply is an option that doesn't really exist on SolidWorks. A benefit of the simplicity of TinkerCAD is that simple shapes can be chosen, dragged to desired size and put together. Unfortunately, cutting shapes to very precise measurements is physically difficult with just a mouse and no option to manually type desired dimensions. Also, different shapes don't fit together very easily. So instead of using very basic shapes and creating them into more complex, cohesive shapes, simple shapes are put together to make compilations of simple shapes rather than anything complex. For this design, squares, cylinders and cones were manipulated to roughly acceptable measurements and then pieced together as smoothly as possible. The overall product was meant to resemble a micropipette with added blocks, rather than just two blocks on current micropipettes, that produce small clicks and allow the user to feel how quickly the top of the device is being pressed down so as to avoid the inclusion of air bubbles in a collected sample.

Our Design

The micropipette was redesigned for this project due to practicality issues with the original design. The micropipette used for the OpenPCR investigation had only two clicks during the pressing of the top button that allow the user to differentiate between the different functions. However, there is a lot of capacity to use the device too quickly or to accidentally press the lever down wrong and to consequentially get air bubbles in the micropipette tip. With the new design, there are added "bumps" along the cylinder that are felt while pressing the lever down, in addition to the two larger bumps, that prevent the lever from being pressed down too quickly. By having extra blocks, the lever cannot slip too quickly and it gets much more difficult to get air bubbles into the micropipette tip.

Feature 1: Consumables

PCR reaction kits include "very important" consumables which are non-machine materials that are necessary for a PCR reaction and for testing for disease-associated SNP's. These consumables include PCR mix, primer solution, SYBR green solution, buffer, patient and control samples, glass slides, plastic tubes, and pipette tips. Our company's PCR reaction kit will include all of the items listed above, but two of the plastic tubes will be totally black instead of clear because these two tubes will be for the SYBR green solution. These black tubes will solve the issue of the SYBR green solution being exposed to light, because the solution is sensitive to light. This product will go along with our redesigned box used with the fluorimeter which also keeps the SYBR green solution out of the light so that it shows up better in images.

Feature 2: Hardware - PCR Machine & Fluorimeter

Our company will include both the Open PCR machine and the fluorimeter in our system. The open PCR machine will be used just as it was in the lab because we found this process easy to follow, and accurate results were obtained as well. A fluorimeter with a tripod to hold the phone, and a design to keep light out will also be included in our system. The micropipette was redesigned in order to improve the accuracy with collecting and depositing samples.