BME100 f2015:Group1 1030amL6

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Contents

OUR COMPANY - "Nappy Happy"

Name: Matt ChrestRole(s)
Name: Matt Chrest
Role(s)
Name: Lindsey O'BrienRole(s)
Name: Lindsey O'Brien
Role(s)
Name: Jacob AperiRole(s)
Name: Jacob Aperi
Role(s)
Name: Michael Otis ClyneRole(s)
Name: Michael Otis Clyne
Role(s)
Name: Nichole TorgersonRole(s)
Name: Nichole Torgerson
Role(s)
Name: Alarmel SiraRole(s)
Name: Alarmel Sira
Role(s)


LAB 6 WRITE-UP

Bayesian Statistics

Overview of the Original Diagnosis System

Seventeen teams of six students each diagnosed 34 patients total. Each team diagnosed two patients. There were multiple aspects to the lab that eliminated the error. The first thing was there was three replicates for each patient instead of just one. Then we also created a positive and negative control for the PCR, which we used water and the positive PCR, and water with negative PCR. The imageJ calibration controls were created by making six different concentrations of Calf Thymus DNA and relating those to the average amount of pixels of the drops. We took a total of 18 pictures, three pictures per concentration, for the calibrations. Next we took 24 pictures, three pictures of each the positive and negative controls.Then three pictures of each replicate of the patients.

Image:GROUP_1_1030AM_PCR_LAB_E_DATA.jpg

Our class data resulted with 34 total final results, with 2 No Tests, 2 Inconclusive tests,13 positive tests and 19 negative tests.

Our group had two conclusive patients, one being positive and one being negative. We encountered a couple of problems throughout this process. When we were making the mixtures of PCR we were lacking some reagents, which made it difficult to replicate data for accuracy. We also encountered a problem figuring out how to do the final calculations, once we figured out what number to use we achieved our final data.

What Bayes Statistics Imply about This Diagnostic Approach

The results for calculation 1 is about 75% reliable that an individual receives a positive test result given a positive PCR reaction. The result for calculation 2 is close to 100% reliable that an individual receives a negative test result given a negative PCR reaction.

The result for calculation 3 has a very low reliability that an individual will develop the disease when they get a positive test result. The result for calculation 4 has close to 100% reliability that an individual will not develop the disease when they get a negative test result.

Three possible sources of error:

1) Lack of settings on the error so the image wasn't as clear as it could've possibly been

2) The distance of the camera to the drop could have varied throughout each trial

3) Lack of reagents given to us to create the drops

Intro to Computer-Aided Design

TinkerCAD
We initially created a replica of the current Fluorimeter. After evaluating the strengths and weaknesses of the current design, we agreed on adding a built in camera to reduce error in the system, and to make the system simpler to operate. Using TinkerCAD as a tool was fairly simple, since it was designed for kids. Yet having previous experience with solid works, some of the team members preferred the more detailed Solid Works software. TinkerCAD was an adequate program for beginners, and worked well as an intro for this lab.

Our Design

Image:Group1_Lab6a_1030AM_Fluorimeter3.jpg
The Open PCR machine, the disease-specific consumables and the consumables remain the same, where we focused on redesigning the Fluorimeter machine instead. The weaknesses we found with the current Fluorimeter design consisted of: problems with the camera distance, re-positioning of the camera, and the possible lack of camera settings. Thus our new model of Fluorimeter incorporated a built-in Camera. The camera is fixed to the slide carrier, removing the need for specific placement, and is capable of having the specific photo parameters needed for analysis. The fixed design also places the camera at the correct height and distance optimal for analysis. Once the Fluorimeter lid is closed, the camera can take and upload pictures directly via Bluetooth. This once again simplifies the system, making it more efficient. The camera is 5.8 cm from the droplet, placing it at the optimal distance.


Feature 1: Consumables

Consumables:

Glass slides that are 3/4 inch by 3 inches

PCR mix

Primer solution

SYBR Green Solution

Buffer solution

Standard plastic tubes


Feature 2: Hardware - PCR Machine & Fluorimeter

Our design utilizes the current PCR machine and a redesigned fluorimeter. A major faw with the current fluorimeter is having to use an external camera and the errors associated with handling and re-positioning the camera between trials.

In order to reduce the chance of error from the position of the camera, we added a built-in camera to the existing fluorimeter. As shown in the TinkerCAD drawing above the slide holder slot and light remain unchanged, while an arm is added with a built-in camera positioned at the height of a drop of DNA on a slide and exactly 5.8 cm away from the drop.

When the box lid is closed, a signal is sent to the camera and after a short delay 3 pictures are taken. These pictures are immediately uploaded via bluetooth or cable to the computer for image processing. This also eliminates the trouble we had keeping pictures in order and uploading them to process with ImageJ software.







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