Thanks, FoodSmartphone!

I am pleased to be writing my final FoodSmartphone blog as a doctor!

Being part of the FoodSmartphone research consortium has been a transformative experience that was only possible through many people’s dedication (and of course, funding from the MSCA EU H2020 program). So thank you to our project co-ordinator Michel Nielen and project secretaries Wim Beek and Ingeborg van Leeuwen-Bol for keeping everything organized and for the lifetime supply of FoodSmartphone stickers. Thank you to all the project partners from WFSR, QUB, UCT, CSIC, LIU, Aquamarijn, CSEM, Barilla and Zeulab for the advice, discussions, secondments and summer schools. Thank you to my past and present fellow ESRs, (Vincent, Sahl, Raheel) Safiye, Klaudia, Ariadni, Julian, Chi, Javier, Jack, Aris and Jordi. I have valued the great collaborations, idea generation, presentations, beer-drinking and travel – I am sure we will work together again. 

And finally, I will leave with you the video of my consumer-operable analytical device for allergen detection. This system makes it possible for untrained people to totally prepare cookie samples for allergen screening. It uses a single disposable syringe containing 3D-printed sieves for the homogenisation, extraction and filtration of peanut and hazelnut allergens. The syringe plugs into a 3D-printed unibody lab-on-a-chip (ULOC) device with pre-stored running buffer and labeled antibodies and injects the extract. A separate clean air displacement syringe then injects air (i.e., bubbles) into the device, transporting and mixing the extract with the stored reagents and transporting the mixed solution to the test well. The ULOC is then inserted into a smartphone holder and the lateral flow immunoassays (LFIAs) are inserted into the opening at the top of the holder, allowing them to align with the test and reference wells in the ULOC. A smartphone is then used to record a video – for a binary yes/no result, users can read the developing signal on the phone screen in real time, as they would with a typical LFIA. For semi-quantitative results, users can export videos for subsequent image analysis.

Thanks, again to everyone involved with the project, it has been a pleasure – please keep in touch!

Goodbye, Gina 🙂

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