BME100 f2018:Group8 T0800 L6
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LAB 6 WRITE-UP
Overview of the Original Diagnosis System
In BME 100, students were split into groups to test patients for a certain disease-associated SNP. The students were split into 17 teams of 5-6 students and were each given 2 patient samples to diagnose. This means that the class as a whole ran 90 total PCRs throughout this process. With all of these PCRs being run there had to be some way to reduce the error. In order to do so we made sure that all tubes were properly labeled. We also avoided cross contamination of our samples by properly disposing of micropipet tips between each use. Also, the procedure included replicates which helps in taking away any error that might occur in the diagnosis of the patient. The final data of the class showed whether or not their assigned patients tested positive, negative, or were inconclusive for the disease associated SNP. The conclusions that matched their PCR results included 25 positives and 39 negatives. However there were three inconclusives within the class’ results. In the class diagnosis there were 4 positive conclusions that matched a yes diagnosis and 11 negative conclusions that matched a no diagnosis. Although the data collected by the class was taken in an extensive manner created to make truthful results it does not mean that our results are perfect. This lab was the first time that some students have even used a micropipette or studied DNA. This ignorance could have led to skewed data because the skills were being learned by the students as they went. However, being exposed to these techniques will make sure that the next time the students use them they are sure to be much more accurate.
What Bayes Statistics Imply about This Diagnostic Approach
Calculation 1 implies that the PCR is very reliable for predicting that a person does have Parkinson's. When the PCR reacts positively, it is incredibly likely that the patient has Parkinson's disease. The Bayes value for the sensitivity of detecting Parkinson's is very large.
Calculation 2 implies that the PCR is incredibly reliable for predicting that a patient does not have Parkinson's. If the PCR does not react, the patient most likely does not have Parkinson's. The Bayes value for the specificity of detecting Parkinson's disease is incredibly high.
Calculation 3 implies that the PCR is unreliable predicting that a person will develop Parkinson's in the future. If the PCR reacts positively and the patient does not already have Parkinson's disease, the patient will probably not develop Parkinson's in the future. The Bayes value for the sensitivity of predicting Parkinson's disease is very small.
Calculation 4 implies that the PCR is fairly reliable for predicting that a person will not develop Parkinson's disease in the future. If the PCR does not react, the patient will probably not develop Parkinson's in the future. The Bayes value for the specificity of predicting Parkinson's is large.
Possible Sources of Error
The software my group used was SOLIDWORKS. Solidworks is a type of software where you design a product and pieces of your desire which you can actually eventually print them with a 3D printer. For our design we decided to make a new phone stand to use when taking pictures during the PCR lab. The Stand will have weight evenly distributed to withhold the weight of any phone without the stand falling over. The stand will also allow you to adjust the phone closer or farther, it will even allow you to pivot the stand up or down. These features will go hand in hand to take the best quality pictures with any phone. In comparison to the provided phone stand our design is much better because one will not have to come across tedious complications. In the CAD drawing these features are eminent. The new and improved design would facilitate the tedious task of replacing the phone on the stand when taking pictures making the lab run smoother and faster. The adjusting techniques will improve the quality of the pictures. Our experience using the Solidworks software was very educational, to some of us this was something we never used and to some this had been demonstrated or had been used in the past. With different backgrounds with the software we can all say that have learned something new from it. Our design is definitely different from the one given to us for the PCR lab because the phone stand provided was feasible and would tilt over, that is because the phone used was heavy which would collapse every time, making this an irritable task.
Feature 1: Consumables
The consumables that will be included in our product are liquid reagents which hold PCR mix, primer solution, SYBR Green solution, and buffer. Our kit also includes all non-reusable containers such as plastic tubes,pipette tips and a pipettor that can be reused. The team has decided that the plastic tubes that we will incorporate will be different colors that way the labeling is easier for any group that will complete the experiment. An addition that the team will be making also includes a new phone stand that is extremely detrimental for this specific experiment because an average phone stand is only able to hold specific phones and as was aforementioned the stand will be versatile and will be movable.
Feature 2: Hardware - PCR Machine & Fluorimeter
In the new system created, both the PCR machine and fluorimeter will be included. Our new system is geared towards educational use. Thus, schools and colleges will be able to use the new system for learning purposes. The PCR machine will be kept the same, as there was no problem with the usage. The only weakness with the PCR machine is that it takes a while for the process to complete. In contrast, the fluorimeter will have a new type of hardware added to it. This is due to the many complications with the use of it. For instance, when setting up any phone to the stand that was provided, the phone would fall over if it were too heavy. A phone of lighter mass would have to be used, so that limited the use of the fluorimeter because there could be a probability that no one in the group has a phone of a light mass. As a result, the new design of the fluorimeter will need to have a way to support all phone sizes. Moreover, the other weakness of the fluorimeter is the amount of adjusting it needed to be done to get the phone leveled with the sample of drop. The adjusting needed to be done by another object that was not apart of the fluorimeter system itself. In this case, trays had to be provided by the instructor. The new design will have some type of hardware where it is connected to the fluorimeter system.
The new fluorimeter our group designed is called ActiveFlo. It addresses all the weaknesses that previously were mentioned. The redesigned fluorimeter will have an extended arm stand where one will be able to place the phone. It will be capable of being adjusted by having adjustable knobs either to widen or narrow it to secure the phone. Thus, any phone will be able to fit in the newly designed stand that will be extended from the fluorimeter. The other weakness it will address is it will be able to be adjusted up or down to have it leveled with the phone. This will be done by having another knob attached to the fluorimeter where it will adjust the hardware where the drop lies either to go up or down, ultimately to be leveled with the phone camera itself. All the new parts of hardware added like the knobs and extended arm will make it easier for the student to use. Thus, the student will be able to focus on the image itself and not waste time too much time on the setup of the fluorimeter.