인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Rapid and reliable analytical techniques play important roles in various research fields and are particularly crucial for diagnosing infectious diseases in clinical settings. African swine fever (ASF) is a devastating viral pig disease for which no effective vaccine is available. The ongoing ASF pandemic has highlighted the importance of rapid and accurate diagnosis, which enables the timely implementation of control and eradication measures. In this study, a ready-to-use bioluminescence immunosensor based on a split-nanoluciferase (NanoLuc) reporter system was proposed for the one-step sensitive detection of ASF virus (ASFV) antibodies. Specifically, the NanoLuc subunits SmBiT/LgBiT were each genetically fused to the ASFV p30 protein and protein G and used as probes. The simultaneous binding of the probes to ASFV IgGs induced the reconstitution of functional NanoLuc, which can generate a strong bioluminescent signal output by catalysing the substrate furimazine. This immunosensor allows the rapid and homogeneous detection of ASFV antibodies in solution, requiring only one incubation step of 10 min. This immunosensor also has high sensitivity, high specificity, and a wide dynamic range and is particularly promising for point-of-care testing. Comparative analysis of clinical samples validated the reliability and robustness of this approach and demonstrated high consistency with enzyme-linked immunosorbent assay (ELISA) results (concordance rate: 98.71%). These results suggest that the proposed immunosensor provides an attractive alternative to conventional immunoassays and could be easily repurposed by generating specific probes for antibody detection in other diseases.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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