Difference between revisions of "Team:NTHU Formosa/Description"

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       <br>  To get rid of limits such as invasiveness and non-real-time tracking, our team proposed <b><i>BioWatcher</i></b>, engineered reporter cells that enable detection and autonomous report of soluble biomarkers in the bloodstream. The sensing parts of the reporter cells are powered by nanobodies, the single-domain antibody that can be engineered to detect different biomarkers. Binding of biomarkers on nanobodies triggers our synthetic gene circuits and, in turn, induces autonomous bioluminescent system as readout for devices to detect. This kind of autonomous reporting system can have great varieties of applications by installation on wearable devices, watches for example. With the required software (will be displayed at the giant jamboree?), the wearable devices could track the level of risk factors by measuring the bioluminescence intensity and record the data as numbers and graphs. It will send an alert to users once the level of the risk factors is too high. Meanwhile, there will be suggestions of nearby hospitals according to the users’ location. The system will also upload and attribute the data to public health analysis under the users’ consent.</p>
 
       <br>  To get rid of limits such as invasiveness and non-real-time tracking, our team proposed <b><i>BioWatcher</i></b>, engineered reporter cells that enable detection and autonomous report of soluble biomarkers in the bloodstream. The sensing parts of the reporter cells are powered by nanobodies, the single-domain antibody that can be engineered to detect different biomarkers. Binding of biomarkers on nanobodies triggers our synthetic gene circuits and, in turn, induces autonomous bioluminescent system as readout for devices to detect. This kind of autonomous reporting system can have great varieties of applications by installation on wearable devices, watches for example. With the required software (will be displayed at the giant jamboree?), the wearable devices could track the level of risk factors by measuring the bioluminescence intensity and record the data as numbers and graphs. It will send an alert to users once the level of the risk factors is too high. Meanwhile, there will be suggestions of nearby hospitals according to the users’ location. The system will also upload and attribute the data to public health analysis under the users’ consent.</p>
 
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Revision as of 03:03, 10 October 2018







Introduction


 People around the world are growing awareness of their health condition. To monitor the health condition, a wide range of biomarkers-- special substances in the bloodstream representing the physiological and pathological states-- has been used in clinical diagnoses. Blood test is one of the most common ways of detecting biomarkers but it suffers from several inevitable drawbacks such as invasiveness, time-consuming procedure, demand for medical staff service, non-real-time tracking and so on. These disadvantages may discourage people from the periodic medical checkup. Indeed, according to a survey (of 1862 samples) pulled by our team, nearly half of the participants took blood test less than once a five-year frequency (Fig. 1), which is impractical for early detection and early treatment of diseases.

 To get rid of limits such as invasiveness and non-real-time tracking, our team proposed BioWatcher, engineered reporter cells that enable detection and autonomous report of soluble biomarkers in the bloodstream. The sensing parts of the reporter cells are powered by nanobodies, the single-domain antibody that can be engineered to detect different biomarkers. Binding of biomarkers on nanobodies triggers our synthetic gene circuits and, in turn, induces autonomous bioluminescent system as readout for devices to detect. This kind of autonomous reporting system can have great varieties of applications by installation on wearable devices, watches for example. With the required software (will be displayed at the giant jamboree?), the wearable devices could track the level of risk factors by measuring the bioluminescence intensity and record the data as numbers and graphs. It will send an alert to users once the level of the risk factors is too high. Meanwhile, there will be suggestions of nearby hospitals according to the users’ location. The system will also upload and attribute the data to public health analysis under the users’ consent.