(A)
34 patients were diagnosed by 17 teams of 6 students. Each team identified samples representing 2 patients to accumulate results for all 34 patients.
(B)
3 replicas of DNA were used for each patient to increase the accuracy of the tests, and 3 pictures of each of those samples was used in testing. A positive control and a negative control were used by each to team to aid in identification of the samples. 5 samples of calibration fluid with decreasing amounts of concentration were used to ensure clear photo taking and diagnosis.
(C)
Out of 30 conclusions, the class determined 11 to be positive, 16 to be negative and 3 to be inconclusive. The results were determined to be inconclusive when the 3 replicas of DNA for 1 patient showed no trend in their results. A doctor then correctly diagnoses these patients. The doctor determined 10 of the samples to be positive and 20 to be negative. Comparing our data to these results showed that we correctly identified 15 out of the 30 results. This margin of error is due to the inability of the students to correctly use ImageJ, and accurately complete the lab. This was the first time many of us had used these programs and lab techniques. Despite inexperience, the class was still able to work well as teams, learn about the process and understand how to make the diagnosis.
Variable
Description
Numerical Value
P(A)
The probability of a positive PCR reaction
0.37
P(B)
The probability that the patient will get a positive PCR conclusion
0.33
P(BlA)
The probability that the patient will get a positive PCR reaction given that they have a positive PCR conclusion
0.83
P(AlB)
The probability they the patient will get a positive PCR conclusion given that they get a positive PCR reaction
0.93
Variable
Description
Numerical Value
P(A)
The probability of a negative PCR reaction
0.53
P(B)
The probability that the patient will get a negative PCR conclusion
0.490
P(BlA)
The probability that they will get a negative PCR reaction given that they have a negative PCR conclusion
0.89
P(AlB)
The probability they the patient will get a negative PCR conclusion given that they get a negative PCR reaction
0.96
Variable
Description
Numerical Value
P(A)
The frequency of "yes" diagnoses among the 30 patients.
0.33
P(B)
The frequency of positive test results.
0.37
P(BlA)
The probability of a positive test result given that a patient develops the disease.
0.36
P(AlB)
The probability of a patient developing the disease, given a positive test result.
0.32
Variable
Description
Numerical Value
P(A)
The frequency of "no" diagnoses among the 30 patients.
0.67
P(B)
The frequency of negative test results
0.53
P(BlA)
The probability of negative test result given that a patient does not develop the disease.
0.69
P(AlB)
The probability of a patient not developing the disease, given a negative test result.
0.87
What Bayes Statistics Imply about This Diagnostic Approach
Calculation 1 displayed that the probability of a patient getting a positive final test conclusion given a positive PCR reaction was very high indicating a reliable test. Calculation 2 displayed that the probability of a patient getting a negative final test conclusion given a negative PCR reaction was very high indicating a reliable test.
Calculation 3 displayed that the probability of a patient developing the disease given a positive final test conclusion was low, indicating an unreliable test. Calculation 4 displayed that the probability of a patient not developing the disease given a negative final test conclusion, was moderately high indicating a reliable test.
Some sources of error included:
Excess light entering the box when obtaining ImageJ photos may have altered the final calculations of the experiment.
Micropipetting is subject to human error. An insufficient amount of Sybr green being added would have resulted in lower detection rates.
When micropipetting, cross-contamination could have occurred and may have altered the calibration controls.
Intro to Computer-Aided Design
3D Modeling
SolidWorks is a 3-D design software used by engineers and designers for computer-aided design and visualization. With each part of a design divided into separate individual files, SolidWorks can often be difficult and tedious to use and takes a lot of time and effort to become acquainted with. But, using the software in other classes at ASU such as BME 182, our group was very familiar with the tools and commands used in SolidWorks and felt comfortable using this software to redesign our product. When using the software, we found it very easy to recreate the rectangular shape of the fluorimeter box, as SolidWorks easily creates square and linear shapes found throughout the design of the fluorimeter. Some of the larger challenges that we encountered in our use of the software were applying the correct and desired dimensions to our redesigned fluorimeter box and recreating the elliptical shape of the box's handle. However, after a lot of measurement and tinkering with the tools in SolidWorks, we were able to effectively visualize our redesigned fluorimeter.
Our Design
Solidwork Design of New Fluorimeter: Angle 1
Solidwork Design of New Fluorimeter: Angle 2
Solidwork Design of New Fluorimeter: Angle 3
Drawing of New Fluorimeter
One of the big problems that we encountered while working with the fluorimeter was the clunky nature and unnecessarily large size of the box. Furthermore, when attempting to capture a photo of the sample, we had to stack multiple layers of objects underneath the phone to adjust the height and effectively image the PCR product. To address these design flaws, our redesigned PCR fluorimeter has dimensions of 6 in X 6 in X 7 in and has no removable parts to simplify the hardware's use. Additionally, the fluorimeter has a built-in adjustable stand to more easily set the height of the phone.
Feature 1: Consumables
The consumables kit included with our product have similar liquid reagents, plastic tubes, and glass slides that we worked with in the previous lab. Specifically, our consumables kit will include the following liquid reagents: polymerase chain reaction (PCR) mix, primer solution, SYBR Green solution, and a buffer solution. Glass slides, plastic PCR tubes of two different sizes, and accompanying plastic PCR tube racks will also be included in the consumables kit, but will remain unchanged from the materials used in the previous lab. Pipettors and pipette tips are not provided in our consumables kit.
The plastics and glassware provided in our consumable kit.
Feature 2: Hardware - PCR Machine & Fluorimeter
Our group has decided to redesign the fluorimeter, but keep the existing PCR machine. The PCR machine was already moderately efficient and easy to use. We all thought that the set up of the fluorimeter, though, was inconvenient, bulky and prone to error. Because of this, we will create a device that is smaller and more consumer friendly.
BME 100 Fall 2018
