Avoiding Thiol Compound Interference: A Nanoplatform Based on High-Fidelity Au-Se Bonds for Biological Applications

2018 ◽  
Vol 57 (19) ◽  
pp. 5306-5309 ◽  
Author(s):  
Bo Hu ◽  
Fanpeng Kong ◽  
Xiaonan Gao ◽  
Lulu Jiang ◽  
Xiaofeng Li ◽  
...  
2018 ◽  
Vol 130 (19) ◽  
pp. 5404-5407 ◽  
Author(s):  
Bo Hu ◽  
Fanpeng Kong ◽  
Xiaonan Gao ◽  
Lulu Jiang ◽  
Xiaofeng Li ◽  
...  

RSC Advances ◽  
2017 ◽  
Vol 7 (5) ◽  
pp. 2884-2889 ◽  
Author(s):  
Dan Voicu ◽  
Gabriella Lestari ◽  
Yihe Wang ◽  
Michael DeBono ◽  
Minseok Seo ◽  
...  

Photolithography and hot embossing offers the capability of cost-efficient and high-fidelity fabrication of polymer microfluidic devices.


2019 ◽  
Author(s):  
Mu-Sen Liu ◽  
Shanzhong Gong ◽  
Helen-Hong Yu ◽  
Kyungseok Jung ◽  
Kenneth A. Johnson ◽  
...  

AbstractCRISPR/Cas9 is a programmable genome editing tool that has been widely used for biological applications. While engineered Cas9s have been reported to increase discrimination against off-target cleavage compared with wild type Streptococcus pyogenes (SpCas9) in vivo, the mechanism for enhanced specificity has not been extensively characterized. To understand the basis for improved discrimination against off-target DNA containing important mismatches at the distal end of the guide RNA, we performed kinetic analyses on the high-fidelity (Cas9-HF1) and hyper-accurate (HypaCas9) engineered Cas9 variants. While DNA unwinding is the rate-limiting step for on-target cleavage by SpCas9, we show that chemistry is seriously impaired by more than 100-fold for the high-fidelity variants. The high-fidelity variants improve discrimination by slowing the rate of chemistry without increasing the rate of DNA rewinding—the kinetic partitioning favors release rather than cleavage of a bound off-target substrate because chemistry is slow. Further improvement in discrimination may require engineering increased rates of dissociation of off-target DNA.


Author(s):  
Philippe Fragu

The identification, localization and quantification of intracellular chemical elements is an area of scientific endeavour which has not ceased to develop over the past 30 years. Secondary Ion Mass Spectrometry (SIMS) microscopy is widely used for elemental localization problems in geochemistry, metallurgy and electronics. Although the first commercial instruments were available in 1968, biological applications have been gradual as investigators have systematically examined the potential source of artefacts inherent in the method and sought to develop strategies for the analysis of soft biological material with a lateral resolution equivalent to that of the light microscope. In 1992, the prospects offered by this technique are even more encouraging as prototypes of new ion probes appear capable of achieving the ultimate goal, namely the quantitative analysis of micron and submicron regions. The purpose of this review is to underline the requirements for biomedical applications of SIMS microscopy.Sample preparation methodology should preserve both the structural and the chemical integrity of the tissue.


2018 ◽  
Vol 17 (3) ◽  
pp. 155-160 ◽  
Author(s):  
Daniel Dürr ◽  
Ute-Christine Klehe

Abstract. Faking has been a concern in selection research for many years. Many studies have examined faking in questionnaires while far less is known about faking in selection exercises with higher fidelity. This study applies the theory of planned behavior (TPB; Ajzen, 1991 ) to low- (interviews) and high-fidelity (role play, group discussion) exercises, testing whether the TPB predicts reported faking behavior. Data from a mock selection procedure suggests that candidates do report to fake in low- and high-fidelity exercises. Additionally, the TPB showed good predictive validity for faking in a low-fidelity exercise, yet not for faking in high-fidelity exercises.


2019 ◽  
Vol 12 (1) ◽  
pp. 18-33 ◽  
Author(s):  
Horea Pauna ◽  
Pierre-Majorique Léger ◽  
Sylvain Sénécal ◽  
Marc Fredette ◽  
Élise Labonté-Lemoyne ◽  
...  

2016 ◽  
Vol 31 (4) ◽  
pp. 337 ◽  
Author(s):  
SUN Xiao-Dan ◽  
LIU Zhong-Qun ◽  
YAN Hao

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