scholarly journals Screening and identification of the levoglucosan kinase gene (lgk) fromAspergillus nigerby LC-ESI-MS/MS and RT-PCR

2005 ◽  
Vol 251 (2) ◽  
pp. 313-319 ◽  
Author(s):  
Hui-jun Xie ◽  
Xu-liang Zhuang ◽  
Hong-xun Zhang ◽  
Zhi-hui Bai ◽  
Hong-yan Qi
2009 ◽  
Vol 25 (9) ◽  
pp. 1589-1595 ◽  
Author(s):  
Jianghong Dai ◽  
Zhisheng Yu ◽  
Yongzhi He ◽  
Ling Zhang ◽  
Zhihui Bai ◽  
...  

PLoS ONE ◽  
2010 ◽  
Vol 5 (10) ◽  
pp. e13293 ◽  
Author(s):  
Varough M. Deyde ◽  
Rangarajan Sampath ◽  
Rebecca J. Garten ◽  
Patrick J. Blair ◽  
Christopher A. Myers ◽  
...  

2016 ◽  
Vol 203 ◽  
pp. 521-529 ◽  
Author(s):  
Sima Kumari ◽  
R. Elancheran ◽  
Jibon Kotoky ◽  
Rajlakshmi Devi

2015 ◽  
Vol 214 ◽  
pp. 43-45 ◽  
Author(s):  
Justin Hardick ◽  
Andrea Dugas ◽  
Joshua Goheen ◽  
Richard Rothman ◽  
Charlotte Gaydos

2009 ◽  
Vol 69 (S2) ◽  
pp. 157-165 ◽  
Author(s):  
Solange Leite Moraes ◽  
Luiz Elídio Gregório ◽  
José Carlos Tomaz ◽  
Norberto Peporine Lopes

2021 ◽  
Author(s):  
Hulya Torun ◽  
Buse Bilgin ◽  
Muslum Ilgu ◽  
Cenk Yanik ◽  
Sukru Numan Batur ◽  
...  

COVID-19 is detected using reverse transcription polymerase chain reaction (RT-PCR) of nasal swabs. A very sensitive and rapid detection technique using easily-collected fluids like saliva must be developed for safe and precise mass testing. Here, we introduce a metasurface platform for direct sensing of COVID-19 from unprocessed saliva. We computationally screen gold metasurfaces out of a pattern space of 2100 combinations for strongly-enhanced light-virus interaction with machine learning and use it to investigate the presence and concentration of the SARS-CoV-2. We use machine learning to identify the virus from Raman spectra with 95.2% sensitivity and specificity on 36 PCR positive and 33 negative clinical samples and to distinguish wild-type, alpha, and beta variants. Our results could pave the way for effective, safe and quantitative preventive screening and identification of variants.


2007 ◽  
Vol 22 (11) ◽  
pp. 1397 ◽  
Author(s):  
Niklas Forsgard ◽  
Per Sjöberg ◽  
Dan Bylund ◽  
Marit Andersson ◽  
Jean Pettersson

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