ultralow concentration
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2021 ◽  
Author(s):  
Nanami Takeuchi ◽  
Moe Hiratani ◽  
Ryuji Kawano

This paper describes nanopore decoding for microRNA (miRNA) expression patterns using DNA computing technology. miRNAs have shown promise as markers for cancer diagnosis due to their cancer type-specificity, and therefore simple strategies for miRNA-pattern recognition are required. We propose a system for pattern recognition of five types of miRNAs overexpressed in bile duct cancer (BDC). The information of miRNAs from BDC is encoded in diagnostic DNAs (dgDNAs) and decoded electrically by nanopore measurement. With this system, we succeeded in distinguishing miRNA expression patterns in the plasma of BDC patients using a label-free method and in real-time. Moreover, our dgDNA-miRNAs complexes can be captured by the nanopore at ultralow concentration, such as 0.1 fM. Such nanopore decoding with dgDNAs could be applied as a simple and early diagnostic tool for cancer in the future.


2021 ◽  
Author(s):  
Nanami Takeuchi ◽  
Moe Hiratani ◽  
Ryuji Kawano

This paper describes nanopore decoding for microRNA (miRNA) expression patterns using DNA computing technology. miRNAs have shown promise as markers for cancer diagnosis due to their cancer type-specificity, and therefore simple strategies for miRNA-pattern recognition are required. We propose a system for pattern recognition of five types of miRNAs overexpressed in bile duct cancer (BDC). The information of miRNAs from BDC is encoded in diagnostic DNAs (dgDNAs) and decoded electrically by nanopore measurement. With this system, we succeeded in distinguishing miRNA expression patterns in the plasma of BDC patients using a label-free method and in real-time. Moreover, our dgDNA-miRNAs complexes can be captured by the nanopore at ultralow concentration, such as 0.1 fM. Such nanopore decoding with dgDNAs could be applied as a simple and early diagnostic tool for cancer in the future.


2021 ◽  
pp. 151446
Author(s):  
Xiuling Zhang ◽  
Xiaoke Hao ◽  
Zhenyu Zhai ◽  
Jiaona Wang ◽  
Huiyu Li ◽  
...  

2021 ◽  
Author(s):  
Ming Qu ◽  
Tuo Liang ◽  
Jirui Hou ◽  
Weipeng Wu ◽  
Yuchen Wen ◽  
...  

Abstract Recently, spherical nanoparticles have been studied to enhance oil recovery (EOR) worldwide due to their remarkable properties. However, there is a lack of studies of nanosheets on EOR. In this work, we synthesize the amphiphilic molybdenum disulfide nanosheets through a straightforward hydrothermal method. The octadecyl amine (ODA) molecules were grafted onto the surfaces of molybdenum disulfide nanosheets due to the presence of active sites over the surfaces of MoS2 nanosheets. The synthesized amphiphilic molybdenum disulfide nanosheets (ODA-MoS2 nanosheets) are approximate 67 nm in width and 1.4 nm in thickness. The effects of ultralow concentration ODA-MoS2 nanosheets on the dynamic wettability change of solid surfaces and emulsion stability were also studied and discussed. Besides, the core flooding experiments were also conducted to reveal the adsorption rules and the oil displacement effects of ultralow concentration ODA-MoS2 nanosheets. Experimental results indicate that the oil-wet solid surface (a contact angle of 130°) can transform into the neutral-wet solid surface (a contact angle of 90°) within 120 hrs after 50 mg/L ODA-MoS2 nanosheets treatment. In addition, micro-scale emulsions in size of 2 µm can be formed after the addition of ODA-MoS2 nanosheets by adsorbing onto the oil-water interfaces. The desorption energy of a single ODA-MoS2 nanosheet from the oil-water interface to the bulk phase is proposed. When the concentration of ODA-MoS2 nanosheets is 50 mg/L, the emulsions are the most stable. Core flooding results demonstrate that the ultimate residue of ODA-MoS2 nanosheets in porous media is less than 11%, and the highest increased oil recovery of around 16.26% is achieved. Finally, the production performance of ultralow concentration of ODA-MoS2 nanofluid (50 mg/L) in the application of Daqing Oilfield is summarized and discussed.


2021 ◽  
Vol MA2021-01 (63) ◽  
pp. 1694-1694
Author(s):  
Wei Liu ◽  
Ding Gu ◽  
Xiaogan Li

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