Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Hanjun Chen"'
Publikováno v:
ACS Applied Materials & Interfaces. 15:8937-8945
Publikováno v:
2022 2nd International Conference on Electrical Engineering and Control Science (IC2ECS).
Publikováno v:
Analysis & Sensing. 1:111-116
Publikováno v:
Biosensors and Bioelectronics. 222:115013
Exosomal microRNAs (miRNAs) are emerging as attractive non-invasive and reliable biomarkers for disease diagnosis. In situ exosomal miRNA detection can avoid laborious and time-consuming exosome lysis, RNA extraction and effectively improve the accur
Publikováno v:
Biosensorsbioelectronics. 200
The abnormal expression of microRNAs (miRNAs) is associated with various diseases. Developing simple and portable methods for sensitive, rapid and simultaneous detection of multiple miRNAs is critical to achieve accurate and timely diagnosis. Herein,
Publikováno v:
2021 China International Conference on Electricity Distribution (CICED).
Distribution stations are the pivots for distribution system in urban areas, which spread massively, cover large areas and are hard to manage. The disposition of image surveillance system for environment and equipment in distribution stations largely
Publikováno v:
Journal of Molecular Liquids. 351:118643
Autor:
Hanjun, Chen, Zhaoyun, Li, Lihong, Zhang, Liming, Zhang, Yaqiong, Zhang, Yichao, Wang, Meifen, Xu, Qianyi, Zhong
Publikováno v:
Annals of clinical and laboratory science. 50(4)
Triple-negative breast cancer (TNBC) is one of the most common malignant, highly heterogeneous tumors in women. MicroRNAs (miRNAs), such as miR-200c, play an important role in various types of malignant cancer, including TNBC. However, the biological
Publikováno v:
The Plant Cell. 30:2402-2424
Zeins are the most abundant storage proteins in maize (Zea mays) kernels, thereby affecting the nutritional quality and texture of this crop. 27-kD γ-zein is highly expressed and plays a crucial role in protein body formation. Several transcription
Publikováno v:
DNA and cell biology. 38(12)
Because of the phenotypic and molecular diversity, it is still difficult to predict breast cancer prognosis. This study aimed to develop and validate a multi-lncRNA (long noncoding RNA) signature to improve the survival prediction for breast cancer.