BME100 f2016:Group10 W1030AM L6

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Owwnotebook icon.png BME 100 Fall 2016 Home
Lab Write-Up 1 | Lab Write-Up 2 | Lab Write-Up 3
Lab Write-Up 4 | Lab Write-Up 5 | Lab Write-Up 6
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Amy Polanecki
Tariq Madni
Kyle Hull
Andrea Hnatievych
Neaco Fox

Our Brand Name


Bayesian Statistics

Overview of the Original Diagnosis System

Disease-associated SNP was tested for patients by utilizing several different groups two patients were given to each group and three trails using the flurometer were used for each patient. The final solutions were compared to baseline samples that were also done in trials with five different variable samples solutions.A positive and a negative control was used to establish the spectrum for testing. Image J software was used to evaluate the samples against the controls as well as the calibration samples.Three drops of the calibration samples, the controls and the samples were used for image J calculations and to limit the chance of error in transferring the samples with the micro pipette. Three images were taken as well at consistent but altering distances to allow for the camera focusing inconsistencies. The final data that was uploaded with the rest of class was used to use for the Bayesian calculations. Some challenges that occurred was the smart phone height and slipping in the holder. Reuse of the slide without eliminating all previous samples cross contaminated samples and needed to be retaken. Another issue arose as samples were returned the identification markings were blurred and hard to read making correct documentation of results difficult.

What Bayes Statistics Imply about This Diagnostic Approach

Calculation 1 shows strong probability that a patient will get a positive PCR reaction indicating a positive for the SNP reaction in conjunction with a positive final test, with an accuracy indication of around 75%. Alternately Calculation 2 show probability that a patient showed negative for the disease SNP and a negative diagnostic signal with an almost 100% accuracy. Both tests 1 and 2 have a close to 100% accuracy indicating strong accuracy and reliability.
Calculation 3 and 4 set out to prove the probability of developing disease based on PCR results. Calculation 3 showed indications of a final positive for SNP and disease development with a fairly low accuracy of around 50%. Calculation 4 had a higher accuracy for detection of a negative PCR with a negative probability for disease development of almost 100%. The inconsistencies noticed between the positive reliability and the negative reliability shows proof that this is an inaccurate and unreliable source for determining a diagnostic usable test.

Each of these calculations were examined in terms of direction relation to the system and detection or prediciton of the disease SNP. The calculation that describes the sensitivity of the system regarding the ability to detect the disease SNP​ was Calculation 1, while the calculation that describes the sensitivity​ of the system regarding the ability to predict the disease was Calculation 3. Similarly, the calculation that describes the specificity​ of the system regarding the ability to detect the disease SNP​ proved to be Calculation 2 and the calculation that describes the specificity​ of the system regarding the ability to predict the disease was evidently Calculation 4.

Possible sources of error could have been irregular transfer amounts due to misuse of the micropipette, light exposure during shutter release when capturing photos of droplets, and distance inaccuracies of the camera and the slide. Another source of error may have been a cross contamination of samples or by the subjects conducting the procedure.

Intro to Computer-Aided Design

3D Modeling

The team decided upon the use of SolidWorks due to the program's ability to design in great detail and provide a variety of views for examination of the assembly. Though the program requires constant learning and searching for new methods to create the design in mind, this truly allows for the most precise design possible. SolidWorks allows the user to determine materials, colors, depths, and technical blueprints for each part created. Beginners in terms of learning the program, these details provided slight challenges in the computer-aided design but these challenges were overcome with dedication and focus on the goal at hand. The use of the computer to propel design methods was extremely influential and will be beneficial in future creations.

Our Design

Phone Holder
Phone Holder
Phone Holder
Phone Holder

Phone Holder
The new design will also involve a change in the fluorimeter, the device to hold the phone to be precise. The holder will be universal for all types of smart phones in its wider, encompassing design and will allow for more accuracy in pressing the button, as there is a large cutout for the camera screen activation. Even if the phone is larger or smaller, the design with width of about 2.5 cm will account for any of these differences, and any slant of the phone in the holder will not make a difference. The new design is different from the latter in that it accounts for a variety of phone sizes and allows for specified access to the camera button. The length of the phone stand will ensure that the distance to the fluorimeter is always 4cm.

Labeling Improvement 
Labeling Improvement
Labeling Improvement

Labeling Improvement
The open PCR kit will provide a sheet of labels, for efficient and readable labeling of the tubes that will be used in the reaction. Each of these labels will correspond to a slot in the PCR machine, making the process of differentiating between tubes quicker and without the involvement of even removing the tubes out of the holder. The new design is different from the original in that the old design had no use of labels and relied on the user writing on the tubes with permanent marker, which was often difficult to read.

Feature 1: Consumables

Identification of liquid reagents is very important when trying to avoid cross contamination of samples. One major obstacle was initially identifying samples as the writing implement used on the slick plastic tube, had a tendency to rub off easily or smear making the tube identification very difficult. Accurately documenting what solutions and primers were Incorporated with the PCR mix is of crucial importance when working with a variety of samples and solutions. Current plastic pipette tubes lack the ability accurately and consistently identify samples in use. Our solution was to create a 50 tube holder that offers colored labels at the base of each tube holder. In this case one tube is used at a time eliminating any issues with placement inconsistencies. This new tube system will allow for a reusable base, offering options of correlating colors and a larger area for writing tube identities.An example of how this system will be used will be a red sticker on the Primer solution tube. This tube is placed into the slot that houses the red sticker on the base that also has the written identification of the product. These consumables will offer options for orders of not only the bases but the option of reordering just stickers or coded tubes as well.There will be the option to order stickers that offered in a variety of symbols and colors as well as offering side products such as legend sheets for more extensive work.

Feature 2: Hardware - PCR Machine & Fluorimeter

Our Open PCR system included a change in the fluorimeter, but the Open PCR machine remained the same. Since we had to take pictures at different distances for the fluorimeter, the results were constantly changing with every test. To remove this error in the Open PCR system, we designed a phone holder that will guarantee the same distance for each picture taken. To stabilize the phone, we used hardware that can hold any phone with or without a case. The phone holding stand measures a distance of 4 cm away from the fluorimeter and there is a hole that allows researchers to place their phones within it.

As previously stated, there was a major weakness in the fluorimeter process. The different distances of the camera resulted in different pictures and data. The variance in data could be the major cause in our inaccurate data and misdiagnose of one of our patients. However, we hope to solve this problem with our phone holder stand that is precisely 4 cm away from the fluorimeter.