A novel fluorescent strategy for Golgi protein 73 determination based on aptamer/nitrogen-doped graphene quantum dots/molybdenum disulfide @ reduced graphene oxide nanosheets.
Аннотация
The effective detection of biomarkers associated with hepatocellular carcinoma (HCC) is of great importance. Golgi protein 73 (GP73), a serum biomarker of HCC, has better diagnostic value than Alpha-fetoprotein (AFP) has been reported. In this paper, highly accurate fluorescence sensing platform for detecting GP73 was constructed based on fluorescence resonance energy transfer (FRET), in which nitrogen-doped graphene quantum dots (NGQDs) labelling with GP73 aptamer (GP73Apt) was used as fluorescence probe, and molybdenum disulfide @ reduced graphene oxide (MoS2@RGO) nanosheets was used as fluorescent receptors. MoS2@RGO nanosheets can quench the fluorescence of NGQDs-GP73Apt owing to FRET mechanisms. In the presence of GP73, the NGQDs-GP73Apt specifically bound with GP73 to from the deployable structures, making NGQDs-GP73Apt far away from MoS2@RGO nanosheets, blocking the FRET process, resulting in fluorescence recovery of NGQDs-GP73Apt. Under optimal conditions, the recovery intensity of fluorescence in the detection system is linearly related to the concentration of GP73 in the range of 5 ng/mL - 100 ng/mL and the limit of detection is 4.54 ng/mL (S/N = 3). Moreover, detection of GP73 was performed in human serum samples with good recovery (97.21-100.83%). This platform provides a feasible method for the early diagnosis of HCC, and can be easily extended to the detection of other biomarkers.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.