شماره ركورد كنفرانس :
5318
عنوان مقاله :
A Miniaturized Low-Cost Sniffing Device Based on Chemometrics Analysis an Array of Fluorescent Carbon Quantum Dots and Metallic Nanoclusters for Early Detection of Leukemia in Adults
پديدآورندگان :
Pesaran Shiva , Shojaeifard Zahra , Khalafinejad Abolfazl , Mohammad Karimi Vahid , Hemmateenejad Bahram hemmatb@shirazu.ac.ir , Tashkhourian Javad tashkhourian@shirazu.ac.ir
كليدواژه :
Leukemia , early detection , Electronic nose , Non , invasive , Sensor array , Discriminant analysis
عنوان كنفرانس :
نهمين سمينار ملي دوسالانه كمومتريكس ايران
چكيده فارسي :
The non-invasive detection of leukemia remains a significant challenge. Blood volatile organic compounds (VOCs) are useful biomarkers [1]. This study demonstrates the potential of an integrated design, consisting of both a sensor array and a sampling vessel, of a paper-based fluorescence sensor array. The paper substrate serves as both a sensing surface and a vessel for samples. To accommodate the paper substrate, a miniature cubic reaction chamber, with dimensions of 330×30×0.02 mm and a tiny opening for blood sample injection, was created using 3D printing technology. Blood samples were taken from 70 new cases of leukemia and 51 healthy individuals as a control group. The sensor array consists of 7 nanoclusters, quantum dots, and carbon dots deposited on hydrophilic regions of a Whatman paper design. 60 µL of the sample that was diluted with heparin was injected through an opening hole in the container cap. An image of the sensor was then captured with a smartphone (irradiated by a 366 nm UV lamp) and compared to the image before the blood vapor was released. The interaction of the sensing element with the volatile blood metabolome caused the fluorescence quenching. The image analysis of sample gave leukemia blood samples specific patterns that differed from healthy samples. A color difference map (CDM) of the sensor array was obtained before and after exposure to blood vapor, which shows that the distinct behavior of the sensor elements in response to exposure of healthy and patient samples results in different color difference maps. A variable selection was performed on the 11 sensor elements, and 7 elements with the highest absolute loading values were chosen to serve as the final indicators. Linear discriminant analysis (LDA) was used to evaluate each multivariate dataset, and the array was able to accurately discriminate between healthy and patient samples with 100% accuracy. In total, the proposed array system provides a non-invasive, portable, fast and cost-effective sensor for early detection of Leukemia in Adults.