BME100 s2015:Group2 12pmL6

BME 100 Spring 2015	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: Levi Riley Name: Alexandria Clark Name: Blossom Mendonca Name: Alina Kilic Name: Trevor Douglass Name: Andre Dang LAB 6 WRITE-UP Bayesian Statistics Overview of the Original Diagnosis System The division of labor consisted of 34 teams of 5 or 6 students who diagnosed a total of 68 patients. Each group ran a PCR test on two patients, and prepared three samples of replicated DNA of each patient along with a primer mix to ensure accuracy. Each of the solutions were compared to both positive and negative controls. The positive control would fluoresce if it contained DNA, while the negative control would do nothing if it did not contain any DNA. If the sample did have DNA, it was compared to the positive control. If the sample did not contain DNA, it was compared to the H20 curve. To avoid error, a practice trial for using a micropipette was conducted so that it could be used with ease when testing with actual samples. After each experiment, photos of the samples were taken and analyzed through the use of ImageJ. ImageJ separated the photo into three different color channels (red, blue, and green), although only the green channel was used. The wavelengths of that green channel were compared to the light of the droplet in the test tube. That drop was analyzed to determine the density and area. There were three images per unique PCR sample, however, only the best picture of each sample was used for the ImageJ calculations. Every group’s final data was then uploaded onto a document to compare the overall results and come to a conclusion. Overall, the class had a successful conclusion. On the other hand, this group’s conclusions were not successful as the data was inconsistent with the results. From the overall results, it can be deduced that the probability of having positive PCR results directly relates to having Coronary Heart Disease. What Bayes Statistics Imply about This Diagnostic Approach The results for calculations 1 where variable A meant there was a positive test conclusion while variable B showed the positive PCR reaction. Both individually showed the number of patients diagnosed and tested for both produced values that were less than .500 being relatively close to each other, indicating that Variable A and B correlates through the experiments. Now taking the Bayes values from both variables, A for positive test conclusion and variable B for positive PCR reaction where the probability of variable B given A shows that the Bayes value is close to 1.00 or 90%, which means that majority of the patients that did test positive to the PCR reactions did in fact also test positive for cancer. Switching the variables where the probability of Variable A given B where the patients that concluded positive for coronary heart disease given having positive PCR reactions equaled 94%, a higher frequency then the probability of B given A. This concludes that the number of patients that tested positive for either PCR reaction or Positive Coronary heart disease has a high probability of testing positive for the other. The results for calculation 2 where Variable A meant there was a negative test conclusion while variable B showed the negative PCR reaction. Both variable A and B showed the number of patients diagnosed and tested negative produced Bayes values that were slightly above .500 being 2% different from each other, indicating both negative test results correlate with each other through the experiment. Taking the frequency from both variables, where the probability of having a negative PCR reaction given negative test conclusions shows that both variables correlate with each other having a probability of 94%. Inversely, the probability of a negative PCR result given the conclusion being negative gives a probability of 90%. In conclusion, a negative Final Test Conclusion and Negative PCR reaction does in fact correlate with each other. The results for calculation 3 where Variable A meant the total patient that will develop disease while Variable B shows the positive test conclusion. Variable A producing value of 37% and variable B producing a value of 43%. Now the probability of variable B given A, Frequency of positive test conclusion given patient that will develop disease, gives a value of .9 or 90% means that the number of patients that do test positive will have a high probability of developing the disease. Now the probability of variable A given B, total patients that will develop the disease given the probability of positive final test conclusions, gives a value of .77 or 77% means that the patient that will develop the disease later on will test positive during the final test but not completely conclusive. Since the value is not close to 1.00 there were errors in the value or the actual experiment. The results for calculation 4 where Variable A meant the total patients that will not develop the disease while variable B shows the total negative test conclusions. Variable A showed the Bayes value being close to .500 or 56% and Variable B shows a value above .60 or 62%. Taking the frequency for both values where the probability of variable B given A, negative Test Conclusion given Total Patient that will not develop disease, gives a Bayes value close to 1.00 or 94% which shows that yes, patients that test negative will be likely to not develop the disease. Now the probability of variable A given B, total patients that will not develop the disease given the probability of the negative final test conclusion, gives a frequency that is 84%. Meaning that majority of the total patients that do not develop the disease will be more likely to have a negative final test conclusion though not completely conclusive. Computer-Aided Design TinkerCAD The tinkerCAD tool is an online interface to create 3D objects and devices. This interface can be used to create simple objects or to create intricate designs. During this lab, TinkerCAD was used to create part of the open PCR device container(front-back-bottom and one side). The rest of the PCR machine would be assembled in a likewise fashion; however, the lab TA told the group to only assemble 3 sides for this portion. The TinkerCAD for the basics of the PCR Machine is as follows: Our Design The new design was chosen to address the problem regarding amount of samples which can be tested. The original openPCR device only could fit 16 micro-tubes, which only allowed for 16 tests, and in the application of this course, only allowed for two teams per box. This new design will expand the amount of tests per box, allowing for more tests, the new openPCR design has double the area for microtubes, allowing for double the amount of tubes. The new design will accommodate up to 32 micro-tubes. In order to do this, the group assembled the outside of the Open PCR machine and increased the length and width so that the dimension created a doubling of the inside area. This doubling in area means that double the amount of test tubes will be able to be tested. Feature 1: Consumables Kit The consumables that will be packaged in the kit will be: PCR reagent mixers test tubes to hold samples 32 test tubes which are 50 μL of content in each: Mix contains Taq DNA polymerase, MgCl2, and dNTP’s DNA/ primer mix, 32 tubes, 50 μL each: All tubes contain the correct reverse and forward primer 32 empty PCR tubes Pipette tips Micropipettor SYBR Green I Dye Glass Slides For Fluorimeter For the way in which these consumables will be packaged, they will come in a box which contains each section divided appropriately so that each consumable will be grouped together. The box will have a flip-top lid which moves backwards and has printed labels at the top which identify exactly which consumable is in each compartment. The consumables will be grouped together and allow for the production of thirty two PCR reactions. This means that the contents will be enough to fill the newly designed PCR machine for one full run in which each compartment is entirely filled with an individual PCR tube. The benefit of this is that the new consumables are organized and easy to keep track of that so that the experimenter will never get the components mixed up. The new feature that this group is offering is also the ability to order specific primers in the consumables package so that the PCR can be ran for whatever the consumer needs. Also, the new pipette tips will allow for reuse so that they do not need to be thrown away. When consumers order new consumable packages, there will be an option on whether to include or not include pipette tips. This is a customizable feature to help the consumer and allow them to spend less money in the long run. A major problem with the consumables in our kit used in this experiment were the amount of plastic disposed. As engineers, sustainability should always be a top priority when conducting an experiment. As a solution to this problem, the plastic tubes used for micro-pipetting should be produced using more durable material and eco-friendly materials. This material will have to be one where it will not absorb the sample or liquid that it is picking up, so as to not contaminate later samples. With more durable and eco-friendly materials, these plastic tubes can then be sanitized and reused multiple times before disposal, thus lessening the amounts of plastic waste. Also, with eco-friendly material, the decomposition of these tubes will not contribute to rapid increase of plastic pollution in the environment. Feature 2: Hardware - PCR Machine & Fluorimeter The PCR machine and fluorimeter that will be included in the system will remain the same as the original. The PCR machine will include holder for 32 test tubes instead of 16, so that more samples can be analyzed in lesser time. Also, A camera would have to be implanted to take photos of the samples, hence an amateur cell phone camera does not have to be used. This will lead to better pictures to analyze and more accurate and precise data. Moreover, the photos taken by the camera would be automatically transmitted to a computer that is synced with the PCR machine so that all the results can be automatically analyzed, greatly reducing the chance of human error. The PCR machine also tends to heat up, so a cooling fan would help to keep the system cool and reduce any risks of burns.