Difference between revisions of "Team:UCL/Description"
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<p><b>How do our devices work?</b></p> | <p><b>How do our devices work?</b></p> | ||
− | The devices we made consist of two main components. | + | <p>The devices we made consist of two main components. Detecting modules that sense the existence of a biomarker of depression or anxiety in the gut and responding modules that consist of genes that are involved in the pathways between the brain and the gut, for example TPH1 and Gad, which are important for Serotonin and GABA production.</p> |
<!--Good place for an explanatory picture of one of the pathways, or a video! --> | <!--Good place for an explanatory picture of one of the pathways, or a video! --> | ||
− | More about <a href="https://2015.igem.org/Team:UCL/Sensors"> | + | More about <a href="https://2015.igem.org/Team:UCL/Sensors">detectors</a> and <a href="https://2015.igem.org/Team:UCL/Effectors">responding modules</a> |
Revision as of 23:55, 14 September 2015
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Why mental health?
Millions of people worldwide suffer from mental health disorders and the consequences are severe for the economy, society and individuals. The WHO estimates that depression will be the most second-most important disease burden in the world by 2020, even surpassing cancer. Today already, there are an estimated 450 million people suffering from mental illnesses.
However, there is still only limited knowledge about the causes of many mental health diseases which makes patients face problems such as stigma, misconceptions and side-effects from medication. In recent years research has offered some insight into the connection between mental health and the bacteria inhabiting our bodies, the microbiom.
We therefore decided to dedicate our summer to tackle mental health problems, especially depression and anxiety using synthetic biology tools and targeting this connection. Our project is not only a proof of concept that mental health can be addressed with synthetic biology, we also found our project to be effective to reduce the stigma around mental health problems.
What we have done
Our parts
We have designed mechanisms in probiotic bacteria that allow them to respond to and take an effect on mental health. This means our probiotics can sense when a person is feeling depressed or anxious or has a panic attack and can then respond appropriately in order to reduce the symptoms.We have made … new parts and have improved … parts.
One of the basic parts that is central to our project the TPH1 producing part which is the rate limiting enzyme for Serotonin production, one of the human’s most important natural happy-makersHow do our devices work?
The devices we made consist of two main components. Detecting modules that sense the existence of a biomarker of depression or anxiety in the gut and responding modules that consist of genes that are involved in the pathways between the brain and the gut, for example TPH1 and Gad, which are important for Serotonin and GABA production.
More about detectors and responding modulesPublic engagement
We organised several events to make people express their feelings about mental health and about GMOs. This includes late night events at the science museum, art exhibitions, interview with stake-holders and more. One of our events, an “open-mind night” was so successful that one of the charities we worked with is making it a monthly event.Entrepreneurship
Researchers found out that chocolate was a more efficient delivery method for probiotics than yogurt or milk, so we developed a product that could deliver our bacteria and taste good at the same time. We worked out a complete business model and are about to have our product “Prokao” patented.The gut-on-the-chip
We developed a model that can be used to imitate conditions in the human gut, even recreating the motion of segmentation and peristalsis, something which has never been done before. This can allow us and future researchers to conduct experiments in controlled conditions without human subjects.References
You can find our references on this page and also by hovering over the references in the texts in our wiki.