BME103 s2013:T900 Group1 L3

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(Original System: PCR Results)
(Original System: PCR Results)
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Calculation 2: The probability that the sample actually has a non-cancer DNA sequence, given a negative diagnostic signal.<br>
Calculation 2: The probability that the sample actually has a non-cancer DNA sequence, given a negative diagnostic signal.<br>
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* A = Frequency of Cancer-Negative Conclusions = 13/20 = .65
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* A = Frequency of Cancer-Negative Conclusions = 11/20 = .55
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* B = Frequency of Negative PCR Reactions = 40/102 = .392
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* B = Frequency of Negative PCR Reactions = 34/60 = .566
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* P (B|A) = Frequency of negative PCR given a cancer-negative conclusion = 10/13 = .769
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* P (B|A) = Frequency of negative PCR given a cancer-negative conclusion = 32/34 = .941
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* '''P(A|B) = 1.28'''
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* '''P(A|B) = .914'''
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Revision as of 23:47, 15 April 2013

BME 103 Spring 2013 Home
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Lab Write-Up 1
Lab Write-Up 2
Lab Write-Up 3
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Contents

OUR TEAM

Kristi Norris:Protocol/Procedure
Kristi Norris:
Protocol/Procedure
Carlos Renteria:Research and Design Specialist
Carlos Renteria:
Research and Design Specialist
Raul Monzolo:Open PCR Machine Engineer
Raul Monzolo:
Open PCR Machine Engineer
Johnny Montez:Open PCR Machine Engineer
Johnny Montez:
Open PCR Machine Engineer
Robert Sanchez:Research and Design Specialist
Robert Sanchez:
Research and Design Specialist
Group 1
Group 1

LAB 3 WRITE-UP

Original System: PCR Results

PCR Test Results

Sample Name Ave. INTDEN* Calculated μg/mL Conclusion (pos/neg)
Positive Control 4967763 235.2946667 N/A
Negative Control 472744.6667 28.99666667 N/A
Tube Label: A1 Patient ID: 29013 rep 1 382980 23.306 NEG
Tube Label: A2 Patient ID: 29013 rep 2 280396.666 20.694 NEG
Tube Label: A3 Patient ID: 29013 rep 3 520011 28.83233333 NEG
Tube Label: B1 Patient ID: 13146 rep 1 5257810.667 250.616 POS
Tube Label: B2 Patient ID: 13146 rep 2 5240422.333 247.8166667 POS
Tube Label: B3 Patient ID: 13146 rep 3 5286556.333 253.3916667 POS

* Ave. INTDEN = Average of ImageJ integrated density values from three Fluorimeter images


Bayesian Statistics
These following conditional statistics are based upon all of the DNA detection system results that were obtained in the PCR lab for 20 hypothetical patients who were diagnosed as either having cancer or not having cancer.

Bayes Theorem equation: P(A|B) = P(B|A) * P(A) / P(B)


Calculation 1: The probability that the sample actually has the cancer DNA sequence, given a positive diagnostic signal.

  • A = The frequency of positive cancer DNA sequence conclusions = 9/20 = .45
  • B = The frequency of total positive DNA sequences in tests = 26/60 = .433
  • P (B|A)= The frequency of total positive DNA sequences in tests given a positive conclusion = 25/26 = .962
  • P(A|B) = .999


Calculation 2: The probability that the sample actually has a non-cancer DNA sequence, given a negative diagnostic signal.

  • A = Frequency of Cancer-Negative Conclusions = 11/20 = .55
  • B = Frequency of Negative PCR Reactions = 34/60 = .566
  • P (B|A) = Frequency of negative PCR given a cancer-negative conclusion = 32/34 = .941
  • P(A|B) = .914


Calculation 3: The probability that the patient will develop cancer, given a cancer DNA sequence.

  • A = The frequency of a "yes" cancer diagnosis = 7/20 = .35
  • B = The frequency of a positive cancer diagnosis = 9/20 = .45
  • P (B|A) = The frequency of positive cancer given a "yes" diagnosis = 6/7 = .857
  • P(A|B) = .925



Calculation 4: The probability that the patient will not develop cancer, given a non-cancer DNA sequence.

  • A = Frequency of patients who developed cancer = 13/20 = .65
  • B = Frequency of a non-cancer DNA sequence = 35/60 = .583
  • P (B|A) = [text description] = 1/7 = .143
  • P(A|B) = .159


New System: Design Strategy

We concluded that a good system Must Have:

  • Results which are easily determined - When doing any kind of diagnostic test, having a clear result is imperative. A system which only distinguishes a positive from a negative result by a narrow margin is not nearly as clear as a system that has a clear distinction between the two. This is even more critical when testing for serious conditions such as cancer because an unclear result may cause a patient to not undergo necessary treatment or to live in fear unnecessarily. Neither option is beneficial.
  • Small Sample volume - We need our system to be able to use small volumes of sample material. A system which requires large volumes of sample necessitates large volumes to be collected from a patient. This may result in several issues, the first being the toll on the patient of having it removed. The second problem becomes that of storing and processing a large volume. Smaller samples allow for higher volumes of tests to be done on a single patient's sample as well as multiple patients' samples to be tested in a high throughput method.


We concluded that we would Want a good system to have:

  • Fewer steps - Each step allows another opportunity for error. Additional steps also require more hands-on time for processing, reducing the efficiency of the over-all process.
  • High volume throughput - In a practical setting, multiple samples are likely to be in line for processing. Even when only doing 3 repetitions of 2 patients, the ability to do more of the process simultaneously would increase the number of readings which could be done per hour or per day. This would allow for more responsive diagnosis and treatment of the patients.


We concluded that a good system Must Not Have:

  • Easy to mix samples during imaging - This is a source of error that can very easily be eliminated. Contamination of the samples in the very last step in which they are used is an unnecessary and unwanted source of potential incorrect readings.
  • Fire Hazard - Safety issues take precedence. A slightly increased cost to raise the safety quality of an electric item which intentionally produces heat is a cost worth accepting.


We concluded that a good system Should Avoid:

  • Minute adjustments of the phone - Adjustment and careful placement of the phone with each picture is a very time-consuming step in this process. Elimination of this procedure would aid in our other goals of higher volume and more streamlined processing.
  • Manual processing of the images - Manual image processing is very time consuming. The processing step alone takes significant amounts of time. Additionally, because the processing is manual, there is more room for error. The area selected is unlikely to be always consistent; the variations in reflections might be improperly included or excluded. An automatic image processing system would eliminate time and error from this procedure.




New System: Machine/ Device Engineering

SYSTEM DESIGN


KEY FEATURES

We chose to include these new features

  • Microwell plate - using a micro-well plate for the samples will dramatically reduce the chance of samples inadvertently mixing together. It also lends itself to a high through put system, allowing for up to 92 sample runs and controls to be prepared simultaneously.
  • Microwell plate Reader - "reading" the samples with the micro-well plate reader will accomplish many of our goals. It allows for high volume processing by measuring multiple samples simultaneously. Using the reader will also eliminate the manual image processing required by use of the fluorimeter/camera/ImageJ system as the reader produces numerical results for each well.




INSTRUCTIONS




New System: Protocols

DESIGN

We chose to include these new approaches/ features

  • Feature 1 - explanation of how this addresses any of the specifications in the "New System: Design Strategy" section
  • Feature 2 - explanation of how this addresses any of the specifications in the "New System: Design Strategy" section
  • Etc.

[OR]

We chose keep the protocols the same as the original system

  • Feature 1 - explanation of how a pre-existing feature addresses any of the specifications in the "New System: Design Strategy" section
  • Feature 2 - explanation of how a pre-existing feature addresses any of the specifications in the "New System: Design Strategy" section
  • Etc.


MATERIALS

Supplied in Kit Supplied by User
dNTPs Template DNA
MgCl2 Forward Primer(s)
Reaction buffers Reverse Primer(s)
Taq DNA Polymerase Mineral oil (optional)


PROTOCOLS

  • PCR Protocol

Thermal Cycler Program

Stage 1
95°C for 3 minutes: Initial DNA strand is separated.
Stage 2
35 cycles of the following steps, each with a duration of 30 seconds:

  1. 95°C: Double strands of DNA separate.
  2. 57°C: Primers attach at ends of target DNA segment.
  3. 72°C: DNA polymerase activates and replicates target segment of DNA.

Stage 3
Final Hold 4°C for 3 minutes: PCR reaction is stopped.

Screen shot of the Open PCR program detailed above 


PCR Reaction Mix

  • Taq DNA polymerase
  • MgCl2
  • dNTPs

Add 25μL of the 2x Master Mix to each reaction tube
DNA Sample/Primer Mix

  • 1-5μL Extracted sample of a particular patient's DNA
  • ~2.5μL Forward Primer (for both the cancer-specific and human DNA-specific primers)
  • ~2.5μL Reverse Primer (for both the cancer-specific and human DNA-specific primers)

DNA Sample Set-up Procedure

  1. Prepare the PCR Reaction Mix and DNA/Primer sample solutions as prescribed above
  2. Label reaction tubes for each sample or control
  3. Add 50μL of each DNA sample Mix to the correspondingly labeled reaction tube (using a new pipette tip for each transfer in order to avoid cross-contamination between samples)
  4. Place the reaction tubes into the thermocycler
  5. Run the thermocycler program detailed above so that PCR will occur in each reaction tube



  • DNA Measurement and Analysis Protocol
  1. Step 1
  2. Step 2
  3. Etc.



New System: Research and Development

BACKGROUND


DESIGN


Primers for PCR


-Guys, I think we'll be using fluorescent primers- ones which attach to the cancerous DNA, then release a particle which fluoresces a particular wave length. I'm not sure yet if we'll manage to have two sets of primers to generate possibly two signals; one that glows (for example) green for the cancer primers and another primer set which fluoresces (for example) red but is specific to a section of human DNA. The end result being, in theory, that we'd mix two sets of primers (one red, one green) with each sample for PCR. Then, after transferring to a micro-well plate, we can set the micro well plate reader to different frequencies. We'd then read each plate twice; one at red, one at green. The up-shot is that we'd hope to have the red signal as a base line in each sample. This is a control that tells us we're actually looking at DNA (this is one of the down-falls we discussed in class in regards to the old protocol). For the second reading, we'd set the reader to green and collect another set of data. This would be the equivalent of the data we got for this lab- we'd get a result if it's cancer-positive but no result if it's cancer-negative. I hope this makes sense. I know it's a little more work for whoever is doing the primers, but I think if you look for the human metabolic gene it should hopefully help (I think additional resources are also posted on BB). If you have questions about the theory, let me know! -Kristi

Our primers address the following design needs

  • Design specification 1 - explanation of how an aspect of the primers addresses any of the specifications in the "New System: Design Strategy" section
  • Design specification 2 - explanation of how an aspect of the primers addresses any of the specifications in the "New System: Design Strategy" section
  • Etc.




New System: Software

[THIS SECTION IS OPTIONAL. If your team has creative ideas for new software, and new software is a key component included in your new protocols, R&D, or machine design, you may describe it here. You will not receive bonus points, but a solid effort may raise your overall page layout points. If you decide not to propose new software, please delete this entire section, including the ==New System: Software== header.]



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