Multi-analyte LC-MS/MS quantification of 38 antipsychotics and metabolites in plasma: Method validation & application to routine analyses

2021 ◽  
pp. 122867
Author(s):  
Maarten Degreef ◽  
Eleanor M. Berry ◽  
Kristof E.K. Maudens ◽  
Alexander L.N. van Nuijs
2008 ◽  
Vol 7 (11) ◽  
pp. 4982-4991 ◽  
Author(s):  
Chunxiu Hu ◽  
Judith van Dommelen ◽  
Rob van der Heijden ◽  
Gerwin Spijksma ◽  
Theo H. Reijmers ◽  
...  

1988 ◽  
Vol 102 ◽  
pp. 243-246
Author(s):  
J.T. Costello ◽  
W.G. Lynam ◽  
P.K. Carroll

AbstractThe dual laser-produced plasma technique for the study of ionic absorption spectra has been developed by the use of two Q-switched ruby lasers to enable independent generation of the absorbing and back-lighting plasmas. Optical pulse handling is used in the coupling cicuits to enable reproducible pulse delays from 250 nsec. to 10 msec, to be achieved. At delay times > 700 nsec. spectra of essentially pure neutral species are observed. The technique is valuable, not only for obtaining the neutral spectra of highly refractory and/or corrosive materials but also for studying behaviour of ionic species as a function of time. Typical spectra are shown in Fig. 1.


Author(s):  
Yurii F. Ivanov ◽  
S. Yu. Filimonov ◽  
Yu. A. Denisova ◽  
O. V. Ivanova ◽  
I. A. Ikonnikova ◽  
...  

2018 ◽  
Vol 2 (2) ◽  
pp. 70-82 ◽  
Author(s):  
Binglu Wang ◽  
Yi Bu ◽  
Win-bin Huang

AbstractIn the field of scientometrics, the principal purpose for author co-citation analysis (ACA) is to map knowledge domains by quantifying the relationship between co-cited author pairs. However, traditional ACA has been criticized since its input is insufficiently informative by simply counting authors’ co-citation frequencies. To address this issue, this paper introduces a new method that reconstructs the raw co-citation matrices by regarding document unit counts and keywords of references, named as Document- and Keyword-Based Author Co-Citation Analysis (DKACA). Based on the traditional ACA, DKACA counted co-citation pairs by document units instead of authors from the global network perspective. Moreover, by incorporating the information of keywords from cited papers, DKACA captured their semantic similarity between co-cited papers. In the method validation part, we implemented network visualization and MDS measurement to evaluate the effectiveness of DKACA. Results suggest that the proposed DKACA method not only reveals more insights that are previously unknown but also improves the performance and accuracy of knowledge domain mapping, representing a new basis for further studies.


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