Difference between revisions of "Team:Lambert GA/Description"

 
(449 intermediate revisions by 6 users not shown)
Line 3: Line 3:
  
 
<head>
 
<head>
−
<link href="https://fonts.googleapis.com/css?family=Codystar:300,400" rel="stylesheet">
+
 
 +
 
 +
<link href="https://fonts.googleapis.com/css?family=Roboto" rel="stylesheet">
 
<link href="https://fonts.googleapis.com/css?family=Montserrat" rel="stylesheet">
 
<link href="https://fonts.googleapis.com/css?family=Montserrat" rel="stylesheet">
 
<link href="https://fonts.googleapis.com/css?family=Lora" rel="stylesheet">
 
<link href="https://fonts.googleapis.com/css?family=Lora" rel="stylesheet">
 
<style type="text/css">
 
<style type="text/css">
 
#holder {
 
#holder {
−
position: relative;
+
position: fixed;
 
top: 0%;
 
top: 0%;
 
left: 0%;
 
left: 0%;
 
height: 100%;
 
height: 100%;
 
width: 100%;
 
width: 100%;
 +
z-index: -3;
 
}
 
}
 
#oceanvideo {
 
#oceanvideo {
−
position: relative;
+
position: fixed;
 
top: 0%;
 
top: 0%;
 
left: 0%;
 
left: 0%;
Line 24: Line 27:
 
}
 
}
 
#overlay {
 
#overlay {
−
position: absolute;
+
position: fixed;
 
top: 0%;
 
top: 0%;
 
left: 0%;
 
left: 0%;
Line 32: Line 35:
 
opacity: 0.3;
 
opacity: 0.3;
 
z-index: 3;
 
z-index: 3;
−
}
 
−
#bigpicture {
 
−
position: absolute;
 
−
top: 18%;
 
−
left: 45%;
 
−
height: 20%;
 
−
width: 10%;
 
−
z-index: 4;
 
 
}
 
}
 
#bigtitle {
 
#bigtitle {
 
position: absolute;
 
position: absolute;
−
top: 45%;
+
top: 43%;
 
left: 0%;
 
left: 0%;
 
height: 10%;
 
height: 10%;
 
width: 100%;
 
width: 100%;
 
z-index: 2;
 
z-index: 2;
−
font-family: 'Codystar', cursive;
+
font-family: 'Montserrat', sans-serif;
 
color: #FFFFFF;
 
color: #FFFFFF;
 
font-size: 70px;
 
font-size: 70px;
Line 54: Line 49:
 
z-index: 4;
 
z-index: 4;
 
}
 
}
−
#bigdescription {
+
#actualtext {
−
position: absolute;
+
position: relative;
−
top: 53%;
+
top: 400%;
 
left: 0%;
 
left: 0%;
−
height: 10%;
+
height: 170%;
 
width: 100%;
 
width: 100%;
−
z-index: 2;
+
background-color: #FFFFFF;
−
font-family: 'Montserrat', sans-serif;
+
−
color: #FFFFFF;
+
−
font-size: 18px;
+
−
text-align: center;
+
 
z-index: 4;
 
z-index: 4;
 +
}
 +
#afterhome {
 +
position: relative;
 +
top: 99%;
 +
left: 0%;
 +
height: 170%;
 +
width: 100%;
 +
}
 +
#sidebar {
 +
position: absolute;
 +
top: 0%;
 +
left: 8%;
 +
height: 35%;
 +
width: 13%;
 +
z-index: 6;
 +
}
 +
#link {
 +
font-family: 'Montserrat', sans-serif;
 +
color: #000000;
 +
font-size: 24px;
 +
cursor: pointer;
 +
transition: all 0.4s ease;
 +
-webkit-transition: all 0.4s ease;
 +
-moz-transition: all 0.4s ease;
 +
-ms-transition: all 0.4s ease;
 +
-o-transition: all 0.4s ease;
 +
}
 +
#link:hover {
 +
color: #0077be;
 +
text-decoration: none;
 +
}
 +
 +
#maincontent {
 +
position: relative;
 +
top: 0%;
 +
left: 28%;
 +
height: 92%;
 +
width: 64%;
 +
border-top: 30px;
 +
}
 +
#target1{
 +
position: relative;
 +
top: -80px;
 +
}
 +
#target1.5
 +
{
 +
position: relative;
 +
top: -80px;
 +
}
 +
#target2{
 +
position: relative;
 +
top: -80px;
 +
}
 +
#target3{
 +
position: relative;
 +
top: -80px;
 +
}
 +
#target4{
 +
position: relative;
 +
top: -80px;
 +
}
 +
#target5{
 +
position: relative;
 +
top: -80px;
 +
}
 +
#subheading1 {
 +
font-size: 36px;
 +
font-family: 'Montserrat', sans-serif;
 +
}
 +
#content1 {
 +
font-family: 'Lora', serif;
 +
font-size: 15px;
 +
line-height: 1.75em;
 +
 +
}
 +
#subheading2 {
 +
font-size: 36px;
 +
font-family: 'Montserrat', sans-serif;
 +
}
 +
#content2 {
 +
font-family: 'Lora', serif;
 +
font-size: 15px;
 +
line-height: 1.75em;
 +
 +
}
 +
#subheading3 {
 +
font-size: 36px;
 +
font-family: 'Montserrat', sans-serif;
 +
}
 +
#content3 {
 +
font-family: 'Lora', serif;
 +
font-size: 15px;
 +
line-height: 1.75em;
 +
 +
}
 +
#subheading4 {
 +
font-size: 36px;
 +
font-family: 'Montserrat', sans-serif;
 +
}
 +
#subheading5 {
 +
font-size: 36px;
 +
font-family: 'Montserrat', sans-serif;
 +
}
 +
#footer {
 +
height: 100px;
 +
width: 100%;
 +
background-color: #FFFFFF;
 +
z-index: 7;
 +
}
 +
#flogo {
 +
font-size:28px;
 +
color: #767676;
 +
transition: all 0.4s ease;
 +
-webkit-transition: all 0.4s ease;
 +
-moz-transition: all 0.4s ease;
 +
-ms-transition: all 0.4s ease;
 +
-o-transition: all 0.4s ease;
 +
}
 +
#flogo:hover {
 +
color: #3B5998;
 +
}
 +
#tlogo {
 +
font-size:28px;
 +
color: #767676;
 +
transition: all 0.4s ease;
 +
-webkit-transition: all 0.4s ease;
 +
-moz-transition: all 0.4s ease;
 +
-ms-transition: all 0.4s ease;
 +
-o-transition: all 0.4s ease;
 +
}
 +
#tlogo:hover {
 +
color: #00aced;
 +
}
 +
#ilogo {
 +
font-size:28px;
 +
color: #767676;
 +
transition: all 0.4s ease;
 +
-webkit-transition: all 0.4s ease;
 +
-moz-transition: all 0.4s ease;
 +
-ms-transition: all 0.4s ease;
 +
-o-transition: all 0.4s ease;
 +
}
 +
#ilogo:hover {
 +
color: #bc2a8d;
 +
}
 +
#afterhome {
 +
position: relative;
 +
top: 99%;
 +
left: 0%;
 +
height: 170%;
 +
width: 100%;
 
}
 
}
 
</style>
 
</style>
Line 71: Line 213:
  
 
<body>
 
<body>
 +
  
 
<div id="holder">
 
<div id="holder">
−
<video style= "z-index:1;" id="oceanvideo"  autoplay muted loop>
+
    <video style= "z-index:1;" id="oceanvideo"  autoplay muted loop>
−
               <source src="https://static.igem.org/mediawiki/2018/b/b0/T--Lambert_GA--OceanVid.mp4" type="video/mp4">
+
               <source src="https://static.igem.org/mediawiki/2018/2/25/T--Lambert_GA--Descriptionmain.mp4" type="video/mp4">
 
               Your browser does not support video.
 
               Your browser does not support video.
 
             </video>
 
             </video>
−
<div id="overlay"></div>
+
    <div id="overlay"></div>
−
<div id="bigtitle">
+
          <div id="bigtitle">
−
D E S C R I P T I O N
+
              D E S C R I P T I O N
 +
          </div>
 
</div>
 
</div>
−
<div id="bigdescription">
+
 
−
CAPTURE THE DISEASE | ACTIVATE THE RESPONSE
+
<br><br><br>
 +
<br><br><br>
 +
<br><br><br>
 +
<br><br><br>
 +
<br><br><br>
 +
<br><br><br>
 +
<br><br><br>
 +
<br><br><br>
 +
<br><br><br>
 +
<br><br><br>
 +
<br><br><br>
 +
 
 +
<div id="actualtext">
 +
 
 +
 
 +
<div id="afterhome">
 +
      <div id="sidebar">
 +
<br>
 +
                      <div id="link">
 +
                            <b><a style="color:black; text-decoration: none; line-height:1.1;" href="#target1">PROJECT OVERVIEW</a></b>
 +
                      </div>
 +
 
 +
<br><br>
 +
                      <div id="link">
 +
                            <b><a style="color:black; text-decoration: none; line-height:1.1;" href="#target2">CURRENT METHODS</a></b>
 +
                      </div>
 +
<br><br>
 +
                      <div id="link">
 +
                            <b><a style="color:black; text-decoration: none; line-height:1.1;" href="#target3">OUR PROJECT</a></b>
 +
                      </div>
 +
<br><br>
 +
                      <div id="link">
 +
                            <b><a style="color:black; text-decoration: none; line-height:1.1;" href="#target4">FUTURE IMPLICATIONS</a></b>
 +
                      </div>
 +
<br><br>
 +
                      <div id="link">
 +
                            <b><a style="color:black; text-decoration: none; line-height:1.1;" href="#target5">REFERENCES</a></b>
 +
                      </div>
 +
      </div>
 
</div>
 
</div>
 +
 +
 +
<div id="maincontent">
 +
<br><br>
 +
 +
<div id="target1"></div>
 +
<div id="subheading1">
 +
<b>Project Overview</b>
 
</div>
 
</div>
 +
<br><br>
 +
<div id="content1">
 +
The identification of pathogens in potentially contaminated sources is crucial for the prevention and treatment of affected individuals from across the world. People in developing nations are particularly distressed by infectious diseases as a consequence of poor sanitation and lack of personal hygiene and access to sufficient resources. Approximately 844 million of these people suffer from a lack of access to safe water, of which 3.4 million succumb to the wide range of infectious diseases transmitted through contaminated water sources [1][2]. Numerous organizations have strived to increase access to clean water in impoverished communities within developing nations. However, pathogens are still able to thrive in water sources, allowing for the emergence of endemics and epidemics that devastate large segments of the population.
  
 +
 +
<br><br>
  
 +
One disease in particular, Cholera, is notorious for claiming approximately a million lives annually. While its presence is relatively non-existent in developed nations due to sufficient treatments that are easily accessible, this pathogen devastates communities in developing nations. Current strategies to detect Cholera are severely inadequate and inefficient. Consequently, Cholera cases are prevalent in these communities. Therefore, Lambert iGEM hopes to develop a practical, yet efficient solution to ensure that these epidemics can not only be detected but prevented as well.
 +
 +
 +
</div>
 +
<br><br>
 +
 +
 +
 +
<div id="target2"></div>
 +
<div id="subheading2">
 +
<b>Current Methods</b>
 +
</div>
 +
<br><br>
 +
<div id="content2">
 +
With the increasing occurrence of epidemics of Cholera, numerous tools have been developed to detect this pathogen in fecal and water samples. However, they significantly vary in cost and precision, making them incompetent for deployment in the field. The most prevalent detection mechanism for Cholera is the Crystal VC Dipstick, an inexpensive tool that can be easily transported and utilized. However, the accuracy range for this device varies between 60% and 99%, which requires additional lab testing for confirmation and act as a deterrent for guaranteed positive/negative results[4]. Immunoassays are also incorporated for confirmation of the Cholera pathogen. However, the precision of these devices comes at a high cost, as the materials necessary to conduct these tests are expensive and difficult to deploy and transport in a field setting, making it inefficient for testing outside the confines of a laboratory[11]. Another common method involves Polymerase Chain Reaction (PCR), which allows for amplification of the target genes of the Cholera pathogen for confirmation of the O1 and O139 strains. However, incorporation of the PCR method requires the utilization of numerous reagents in the field, in addition to a thermocycler and gel electrophoresis apparatus, making it difficult to exploit in the field[11]. The inefficiency of these methods in terms of costs and/or accuracy has driven the 2018 Lambert iGEM team to develop a novel system capable of delivering accurate and precise results for Cholera identification at a significantly lower cost.
 +
 +
 +
 +
</div>
 +
<br><br>
 +
<div id="target3"></div>
 +
<div id="subheading3">
 +
<b>Our Project</b>
 +
</div>
 +
<br><br>
 +
<div id="content3">
 +
 +
Recognizing the limitations of the current methods utilized for the detection of Cholera, Lambert iGEM has developed a novel platform to detect and analyze data from this pathogen at a fraction of the cost.  While many caveats persist towards pathogen identification in large water sources, access to efficient and inexpensive technology has become the primary prohibitive factor. Inexpensive tests currently utilized for detection have a significant variance in the positive/negative outputs, whereas the precision of other technologies correlates with heightened costs with the lack of access to necessary materials in the field. Lambert iGEM demonstrates the potential for a gene-based detection mechanism for Cholera pathogens that can easily be deployed in the field at drastically lower costs, without sacrificing quality or performance. In tandem, we propose a machine learning model that can predict outbreak inception and spread, allowing for a preventative approach, rather than a reactive one.
 +
<center><img src="https://static.igem.org/mediawiki/2018/0/07/T--Lambert_GA--processmapping.jpg" style="height:600px; padding-top:50px;"><br><br><i><div style="font-size:15px; padding-left:100px; padding-right:100px;">This overview explains how the multiple parts of our project work together to be a proactive approach to preventing V. cholerae epidemics using Yemen as a test case.  Our process begins with the CALM software predicting outbreaks up to 8 weeks in advance.  Our kit with the necessary hardware, software and biosensor cells are pre-deployed to aid workers.  Text messages are sent to the aid agencies who notify local workers to deploy the testing kits.  Water samples are taken and filtered to extract cells in the size range of V. Cholerae.  The cells are lysed and RNA or DNA is extracted (depending whether NASBA is available in field)  The RNA/DNA is electroporated into the biosensor cells using our Electropen.  Biosensor cells are incubated for 24 hours after which the cell solution is pelleted using the 3-D fuge.  The sample is loaded onto the Chrome Q base and using the Color Q App, the results are quantified and uploaded to AWS server which publishes the results.  The results from the water sampling feeds into our CALM model completing a feedback loop to ensure continual model improvement.</div></i></center> <br><br><br>
 +
 +
</div>
 +
 +
<div id="target4"></div>
 +
<div id="subheading4">
 +
<b>Future Implications</b>
 +
</div>
 +
<br><br>
 +
<div id="content3">
 +
While our current technology functions for identification of Cholera, Lambert iGEM hopes to expand this technology to numerous pathogens, establishing a collection of genetic tools for detection and compiling them into a portable synthetic biology toolkit that can be distributed to aid organizations for confirmation of clean water provisions. This detection platform with visible readouts can be integrated into a data collection platform on a global scale, allowing for a proactive response to disease outbreaks and ensuring the safety of the people residing in potentially at-risk areas. Lambert iGEM hopes to revolutionize pathogen detection in order to enhance feasibility, accessibility, affordability, and efficiency.
 +
 +
 +
 +
 +
<br><br>
 +
 +
</div>
 +
<div id="target5"></div>
 +
<div id="subheading5">
 +
<b>References</b>
 +
</div>
 +
<br><br>
 +
<div id="content3">
 +
[1] Drinking-water. (2018, February 7). Retrieved from http://www.who.int/news-room/fact- sheets/detail/drinking-water
 +
<br>
 +
[2] (n.d.). Retrieved from http://www.who.int/water_sanitation_health/takingcharge.html
 +
<br>
 +
[3] Berman, J. (2009, October 29). WHO: Waterborne Disease is World's Leading Killer. Retrieved from https://www.voanews.com/a/a-13-2005-03-17-voa34-67381152/274768.html
 +
<br>
 +
[4] Learn How to Use the Crystal VC Dipstick Test to Detect Vibrio Cholera in Our New Video | DOVE: Stop Cholera. (n.d.). Retrieved from https://www.stopcholera.org/blog/learn-how-use-crystal-vc-dipstick-test-detect-vibrio-cholera-our-new-video
 +
<br>
 +
[5] Cholera - Vibrio cholerae infection. (2018, May 14). Retrieved from https://www.cdc.gov/cholera/diagnosis.html
 +
<br>
 +
[6] The Burden of Soil-transmitted Helminths (STH). (2011, June 06). Retrieved from
 +
https://www.cdc.gov/globalhealth/ntd/diseases/sth_burden.html
 +
<br>
 +
[7] Water. (2016, April 22). Retrieved from https://www.cdc.gov/parasites/water.html
 +
<br>
 +
[8] Collender, P. A., Kirby, A. E., Addiss, D. G., Freeman, M. C., & Remais, J. V. (2015, December). Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4679500/
 +
<br>
 +
[9] Action Against Worms. (2008, February). Retrieved from http://www.who.int/neglected_diseases/preventive_chemotherapy/pctnewsletter11.pdf
 +
<br>
 +
[10] Pilotte, N., Papaiakovou, M., Grant, J. R., Bierwert, L. A., Llewellyn, S., McCarthy, J. S., & Williams, S. A. (n.d.). Improved PCR-Based Detection of Soil Transmitted Helminth Infections Using a Next-Generation Sequencing Approach to Assay Design. Retrieved from http://journals.plos.org/plosntds/article?id=10.1371/journal.pntd.0004578
 +
<br>
 +
[11] Detection of Cholera Toxin [PDF]. (n.d.). Atlanta: Centers for Disease Control and Prevention.
 +
https://www.cdc.gov/cholera/pdf/laboratory-methods-for-the-diagnosis-of-vibrio-cholerae-chapter-7.pdf
 +
 +
<br>
 +
<br><br>
 +
 +
</div>
 +
 +
</div>
 +
 +
<div id="footer">
 +
<br><br>
 +
<a href="https://www.facebook.com/groups/198318606966726/"><i class="fa fa-facebook" id="flogo"></i></a>
 +
 +
<a href="https://twitter.com/lamberths_igem?lang=en"><i class="fa fa-twitter" id="tlogo"></i></a>
 +
 +
<a href="https://www.instagram.com/lambertigem/"><i class="fa fa-instagram" id="ilogo"></i></a>
 +
 +
</div>
 +
 +
</div>
 
</body>
 
</body>
 +
 +
 +
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.3.1/jquery.min.js"></script>
 +
<script>
 +
$(window).scroll(function(e){
 +
  parallax();
 +
});
 +
 +
//PARALLAX FUNCTION
 +
function parallax(){
 +
  var scrolled = $(window).scrollTop();
 +
  $('#oceanvideo').css('top',-(scrolled*0.35)+'px');
 +
}
 +
 +
//NOT THE MOST EFFICIENT PARALLAX, BUT SIMPLE
 +
</script>
  
  
 
</html>
 
</html>

Latest revision as of 22:41, 2 November 2018

CALM ELECTROPEN
BACKGROUND DATA & METHODS RESULTS DISCUSSION COLOR Q SUPPLEMENTARY REFERENCES
COLOR Q CHROME Q REFERENCES
PRINCIPLES & DESIGN MODEL & THEORY PRODUCT DESIGN REFERENCES
INTEGRATED HUMAN PRACTICES EDUCATION & ENGAGEMENT COLLABORATIONS
BASIC PARTS COMPOSITE PARTS
DESCRIPTION BACKGROUND DESIGN EXPERIMENTS LAB NOTEBOOK INTERLAB RESULTS DEMONSTRATE THE VISION
TEAM MEMBERS ATTRIBUTIONS
D E S C R I P T I O N



































Project Overview


The identification of pathogens in potentially contaminated sources is crucial for the prevention and treatment of affected individuals from across the world. People in developing nations are particularly distressed by infectious diseases as a consequence of poor sanitation and lack of personal hygiene and access to sufficient resources. Approximately 844 million of these people suffer from a lack of access to safe water, of which 3.4 million succumb to the wide range of infectious diseases transmitted through contaminated water sources [1][2]. Numerous organizations have strived to increase access to clean water in impoverished communities within developing nations. However, pathogens are still able to thrive in water sources, allowing for the emergence of endemics and epidemics that devastate large segments of the population.

One disease in particular, Cholera, is notorious for claiming approximately a million lives annually. While its presence is relatively non-existent in developed nations due to sufficient treatments that are easily accessible, this pathogen devastates communities in developing nations. Current strategies to detect Cholera are severely inadequate and inefficient. Consequently, Cholera cases are prevalent in these communities. Therefore, Lambert iGEM hopes to develop a practical, yet efficient solution to ensure that these epidemics can not only be detected but prevented as well.


Current Methods


With the increasing occurrence of epidemics of Cholera, numerous tools have been developed to detect this pathogen in fecal and water samples. However, they significantly vary in cost and precision, making them incompetent for deployment in the field. The most prevalent detection mechanism for Cholera is the Crystal VC Dipstick, an inexpensive tool that can be easily transported and utilized. However, the accuracy range for this device varies between 60% and 99%, which requires additional lab testing for confirmation and act as a deterrent for guaranteed positive/negative results[4]. Immunoassays are also incorporated for confirmation of the Cholera pathogen. However, the precision of these devices comes at a high cost, as the materials necessary to conduct these tests are expensive and difficult to deploy and transport in a field setting, making it inefficient for testing outside the confines of a laboratory[11]. Another common method involves Polymerase Chain Reaction (PCR), which allows for amplification of the target genes of the Cholera pathogen for confirmation of the O1 and O139 strains. However, incorporation of the PCR method requires the utilization of numerous reagents in the field, in addition to a thermocycler and gel electrophoresis apparatus, making it difficult to exploit in the field[11]. The inefficiency of these methods in terms of costs and/or accuracy has driven the 2018 Lambert iGEM team to develop a novel system capable of delivering accurate and precise results for Cholera identification at a significantly lower cost.


Our Project


Recognizing the limitations of the current methods utilized for the detection of Cholera, Lambert iGEM has developed a novel platform to detect and analyze data from this pathogen at a fraction of the cost. While many caveats persist towards pathogen identification in large water sources, access to efficient and inexpensive technology has become the primary prohibitive factor. Inexpensive tests currently utilized for detection have a significant variance in the positive/negative outputs, whereas the precision of other technologies correlates with heightened costs with the lack of access to necessary materials in the field. Lambert iGEM demonstrates the potential for a gene-based detection mechanism for Cholera pathogens that can easily be deployed in the field at drastically lower costs, without sacrificing quality or performance. In tandem, we propose a machine learning model that can predict outbreak inception and spread, allowing for a preventative approach, rather than a reactive one.


This overview explains how the multiple parts of our project work together to be a proactive approach to preventing V. cholerae epidemics using Yemen as a test case. Our process begins with the CALM software predicting outbreaks up to 8 weeks in advance. Our kit with the necessary hardware, software and biosensor cells are pre-deployed to aid workers. Text messages are sent to the aid agencies who notify local workers to deploy the testing kits. Water samples are taken and filtered to extract cells in the size range of V. Cholerae. The cells are lysed and RNA or DNA is extracted (depending whether NASBA is available in field) The RNA/DNA is electroporated into the biosensor cells using our Electropen. Biosensor cells are incubated for 24 hours after which the cell solution is pelleted using the 3-D fuge. The sample is loaded onto the Chrome Q base and using the Color Q App, the results are quantified and uploaded to AWS server which publishes the results. The results from the water sampling feeds into our CALM model completing a feedback loop to ensure continual model improvement.



Future Implications


While our current technology functions for identification of Cholera, Lambert iGEM hopes to expand this technology to numerous pathogens, establishing a collection of genetic tools for detection and compiling them into a portable synthetic biology toolkit that can be distributed to aid organizations for confirmation of clean water provisions. This detection platform with visible readouts can be integrated into a data collection platform on a global scale, allowing for a proactive response to disease outbreaks and ensuring the safety of the people residing in potentially at-risk areas. Lambert iGEM hopes to revolutionize pathogen detection in order to enhance feasibility, accessibility, affordability, and efficiency.

References


[1] Drinking-water. (2018, February 7). Retrieved from http://www.who.int/news-room/fact- sheets/detail/drinking-water
[2] (n.d.). Retrieved from http://www.who.int/water_sanitation_health/takingcharge.html
[3] Berman, J. (2009, October 29). WHO: Waterborne Disease is World's Leading Killer. Retrieved from https://www.voanews.com/a/a-13-2005-03-17-voa34-67381152/274768.html
[4] Learn How to Use the Crystal VC Dipstick Test to Detect Vibrio Cholera in Our New Video | DOVE: Stop Cholera. (n.d.). Retrieved from https://www.stopcholera.org/blog/learn-how-use-crystal-vc-dipstick-test-detect-vibrio-cholera-our-new-video
[5] Cholera - Vibrio cholerae infection. (2018, May 14). Retrieved from https://www.cdc.gov/cholera/diagnosis.html
[6] The Burden of Soil-transmitted Helminths (STH). (2011, June 06). Retrieved from https://www.cdc.gov/globalhealth/ntd/diseases/sth_burden.html
[7] Water. (2016, April 22). Retrieved from https://www.cdc.gov/parasites/water.html
[8] Collender, P. A., Kirby, A. E., Addiss, D. G., Freeman, M. C., & Remais, J. V. (2015, December). Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4679500/
[9] Action Against Worms. (2008, February). Retrieved from http://www.who.int/neglected_diseases/preventive_chemotherapy/pctnewsletter11.pdf
[10] Pilotte, N., Papaiakovou, M., Grant, J. R., Bierwert, L. A., Llewellyn, S., McCarthy, J. S., & Williams, S. A. (n.d.). Improved PCR-Based Detection of Soil Transmitted Helminth Infections Using a Next-Generation Sequencing Approach to Assay Design. Retrieved from http://journals.plos.org/plosntds/article?id=10.1371/journal.pntd.0004578
[11] Detection of Cholera Toxin [PDF]. (n.d.). Atlanta: Centers for Disease Control and Prevention. https://www.cdc.gov/cholera/pdf/laboratory-methods-for-the-diagnosis-of-vibrio-cholerae-chapter-7.pdf