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.
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
| 期刊: | Innovation (Camb) | 影响因子: | 0.000 |
| 时间: | 2025 | 起止号: | 2025 May 15; 6(8):100952 |
| doi: | 10.1016/j.xinn.2025.100952 | 研究方向: | 炎症/感染 |
| 疾病类型: | 肝炎 | ||
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