A fully automated, ultrasensitive luminescence cascade sensor to address hepatitis C diagnostic disparity.

一种全自动、超灵敏的发光级联传感器,用于解决丙型肝炎诊断差异问题

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作者:Kim Sungwan, Chellappaa Adharsh, Chun Juhyeon, Lee Jaebaek, Hardie Joseph M, Kanakasabapathy Manoj K, Kandula Hemanth, Thirumalaraju Prudhvi, Fricker Gregory P, Gustafson Jenna, Chung Raymond T, Mera Jorge, Shafiee Hadi
Viral hepatitis poses a significant global health burden, with chronic hepatitis B and C causing about 1 million annual deaths from liver cancer and cirrhosis. Over 1.5 million new hepatitis C virus (HCV) cases arise yearly, especially among vulnerable groups like American Indians and Alaska Natives (AI/AN). Despite effective direct-acting antivirals, early HCV diagnosis remains challenging, particularly in resource-limited settings. Current two-step testing methods are costly and prone to patient dropout. Point-of-care (POC) HCV antigen (Ag) testing offers a promising early detection approach, but no US Food and Drug Administration (FDA)-approved POC test meets the sensitivity and specificity needed for low viral loads. To address this, we developed a fully automated bioluminescence-based POC assay using a cascade-based signal amplification strategy. Evaluated on 71 AI/AN samples, it showed 97% sensitivity, 94% specificity, and 96% accuracy. This technology can improve health equity by enabling accessible and reliable HCV testing for disproportionately affected populations.

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