Draz Mohamed S, Vasan Anish, Muthupandian Aradana, Kanakasabapathy Manoj Kumar, Thirumalaraju Prudhvi, Sreeram Aparna, Krishnakumar Sanchana, Yogesh Vinish, Lin Wenyu, Yu Xu G, Chung Raymond T, Shafiee Hadi
Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02139, USA.
Harvard Medical School, Boston, MA 02115, USA.
Sci Adv. 2020 Dec 16;6(51). doi: 10.1126/sciadv.abd5354. Print 2020 Dec.
Emerging and reemerging infections present an ever-increasing challenge to global health. Here, we report a nanoparticle-enabled smartphone (NES) system for rapid and sensitive virus detection. The virus is captured on a microchip and labeled with specifically designed platinum nanoprobes to induce gas bubble formation in the presence of hydrogen peroxide. The formed bubbles are controlled to make distinct visual patterns, allowing simple and sensitive virus detection using a convolutional neural network (CNN)-enabled smartphone system and without using any optical hardware smartphone attachment. We evaluated the developed CNN-NES for testing viruses such as hepatitis B virus (HBV), HCV, and Zika virus (ZIKV). The CNN-NES was tested with 134 ZIKV- and HBV-spiked and ZIKV- and HCV-infected patient plasma/serum samples. The sensitivity of the system in qualitatively detecting viral-infected samples with a clinically relevant virus concentration threshold of 250 copies/ml was 98.97% with a confidence interval of 94.39 to 99.97%.
新出现和再次出现的传染病对全球健康构成了日益严峻的挑战。在此，我们报告一种基于纳米颗粒的智能手机（NES）系统，用于快速、灵敏地检测病毒。病毒被捕获在微芯片上，并用专门设计的铂纳米探针进行标记，以便在过氧化氢存在的情况下诱导气泡形成。所形成的气泡被控制以产生独特的视觉图案，从而能够使用启用了卷积神经网络（CNN）的智能手机系统，在不使用任何光学硬件智能手机附件的情况下进行简单且灵敏的病毒检测。我们评估了所开发的CNN-NES用于检测诸如乙型肝炎病毒（HBV）、丙型肝炎病毒（HCV）和寨卡病毒（ZIKV）等病毒。该CNN-NES用134份添加了ZIKV和HBV以及感染了ZIKV和HCV的患者血浆/血清样本进行了测试。该系统在以250拷贝/毫升的临床相关病毒浓度阈值定性检测病毒感染样本时的灵敏度为98.97%，置信区间为94.39%至99.97%。
