BME100 f2016:Group2 W1030AM L6

BME 100 Fall 2016	Home People Lab Write-Up 1 | Lab Write-Up 2 | Lab Write-Up 3 Lab Write-Up 4 | Lab Write-Up 5 | Lab Write-Up 6 Course Logistics For Instructors Photos Wiki Editing Help
OUR COMPANY Name: Danielle Mara Name: Lauren Gustafson Name: Joel Reynoso Name: Merin Jacob Name: Maribel Diaz Name: student Our Brand Name LAB 6 WRITE-UP Bayesian Statistics Overview of the Original Diagnosis System During the lab, 34 patients were observed by 17 teams of 6 scientists. Every team was assigned two patients to overlook and diagnose for the SNP disease. Varying things were done to get rid of any type of error that might have occurred during the lab. A total of three replicates were used for each patient and performed three samples per patient. Certain PCR control standards were upheld including not reusing tips, making sure the phone used was five centimeters away from the system. Several pictures were also taken to get optimal ImageJ data. In order to produce a more accurate average of the drops, 3 images were used in the IMageJ program. These images used the same settings that the lab notebook prescribed. The class data resulted in three inconclusive data tests, 7 positive and yes tests, 13 negative and no diagnosis and 26 total tests with ‘No test’ not included. However, there were 4 ‘No test” or blank data points in the class spreadsheet. Due to ‘Inconclusive tests’ and ‘No tests’, it was difficult to fully analyze the consistency of the results. Other errors included not being able to get a completely accurate ImageJ procedure since making an outline on the oval was not fully precise. What Bayes Statistics Imply about This Diagnostic Approach Calculation number one looks at the probability that a patient will be having a positive final diagnosis for the disease. The percentage obtained was about an 80% which shows that there is a fairly high probability. Calculation number two describes the probability that a patient will be having a negative final diagnosis. For this, a high percentage of almost 100% was obtained. These two results indicate that the tests are quite reliable. Calculation three shows what the probability of actually coming out positive with a disease after the test points out positive will be. In this case, we obtained a 43% which isn’t really that accurate. Calculation four describes how likely it is for the patient to not have the disease after the test came out negative. The percentage obtained was a 96%, close to 100% meaning that if the test says negative, the disease will very likely not be there. Machines can be pretty accurate but only when everything else is done to perfection as well. A human error could’ve happened such as contamination of the DNA sample. Another possibility could be that the camera used to take the pictures was not good enough to produce a good high quality image. Also, the camera could’ve been placed too close or too far between different sample tests. Intro to Computer-Aided Design A side view of our new fluorimeter system. A front view of the system, looking through the tunnel and at the cuvette inside. An inside view of the cuvette and the light source underneath it. 3D Modeling The software that was used during the Computer-Aided Design lab was Tinkercad. Tinkercad is an online tool used to create digital designs. We used Tinkercad to create a 3D model of our new open PCR machine. Our lab group found the program difficult to use. We found it challenging to align each of the components, especially when dealing with holes. We watched several Youtube videos to learn more about the different tool available in this program. Because we are all new to this program, our design is fairly simple, yet represents the main adjustments we are making to the machine. Instead of having an open system, this fluorimeter is self contained within the box. Our design utilizes a cuvette in place of the slide in order to create less variability. This is represented by the grey piece inside the device. Because the cuvette has flat face surfaces, the light of the fluorimeter is shown through the bottom instead of the side to avoid deflection and glares. The light source is represented by the light blue cylinder in the inside bottom of the box. Finally, our design includes a dark "tunnel" that the phone camera can be lined up with, eliminated the need of a box around the whole system. This is the portion protruding from the face of the device. Feature 1: Consumables In our analysis of the weaknesses, we noticed that in order to do a PCR lab, there are many steps that are quite time consuming. Therefore, we developed a way to cut down on the amount of steps to prepare the DNA and also to cut down on the amount of plastics and used in the lab. In order to improve the consumables kit in our lab, we decided to decreases the amount of steps for the lab which will reduce the amount of containers, pipette tips, and plastics used to prepare the solutions. Primers, water, and DNA are initially separated in the lab. We will focus on adding the primer to the other elements of the lab which will then be sold to other companies. This will improve the consumables by requiring less plastics and it will also decrease the amount of steps for the lab technicians. The primer will be initially added to the PCR promega mix (buffer with specific salts to maintain pH, MgCl2, taq polymerase, nucleotides (ATCG)). The final concentration must be = 1 micromolar in final reaction, therefore, the primers have to be packaged as 2M concentration. Since the consumables come premixed with the primers, each mix sold will be for a specific disease. Overall this effort reduces the need to dilute, packaging plastics, pipette tips and it cuts down on plastics to use to create mix which will overall decrease the cost for students and teachers purchasing our products. Feature 2: Hardware - PCR Machine & Fluorimeter A solar battery pack will be attached to the new PCR machine, allowing portability. A glass cuvette will be used in place of a slide. PCR Machine: In our analysis, the PCR machine’s immobility was a weakness. To improve that weakness, we would change the PCR machine to include a battery to take it wherever the machine is needed. The battery will be solar powered. The solar cells will be lined along the outer wall of the PCR machine. We included a battery so that the PCR machine will recharge itself as long as there is sunlight. We included a solar powered battery in the effort to enhance the PCR machine's portability and convenience. Fluorimeter: The biggest area of redesign in our project was with the fluorimeter. First off, we made the whole system self-contained, so there are less moving parts. Our design utilizes a cuvette instead of a slide in order make the whole process less susceptible to disruption as the sample contents is enclsoed within it. Since we are using cuvettes, we created the light source at the base of the cuvette, shining up, instead of across it from the side, like with the slide technique. We designed it this way in order to avoid error due to glare and deflection from the flat faces and the sharp corners of the cuvette. Finally, we redesigned the box to have a "tunnel" protruding from the front of the device that the phone camera can lay flush against to get a good picture while not allowing any light in. This is an improvement from the fluorimeter we used because the user can easily reach their phone to touch the camera button without letting any light into the system. It eliminates the need for a camera timer and allows the user to focus the camera more easily.