Emerging Technologies, Recent Developments, and Novel Applications for Drug Metabolite Identification

2015 ◽  
Vol 15 (9) ◽  
pp. 865-874 ◽  
Author(s):  
Wenjie Lu ◽  
Youzhi Xu ◽  
Yinglan Zhao ◽  
Xiaobo Cen
2020 ◽  
Vol 128 (06/07) ◽  
pp. 358-374 ◽  
Author(s):  
Josef Köhrle ◽  
Keith H. Richards

AbstractThe wide spectrum of novel applications for the LC-MS/MS-based analysis of thyroid hormone metabolites (THM) in blood samples and other biological specimen highlights the perspectives of this novel technology. However, thorough development of pre-analytical sample workup and careful validation of both pre-analytics and LC-MS/MS analytics, is needed, to allow for quantitative detection of the thyronome, which spans a broad concentration range in these biological samples.This minireview summarizes recent developments in advancing LC-MS/MS-based analytics and measurement of total concentrations of THM in blood specimen of humans, methods in part further refined in the context of previous achievements analyzing samples derived from cell-culture or tissues. Challenges and solutions to tackle efficient pre-analytic sample extraction and elimination of matrix interferences are compared. Options for automatization of pre-analytic sample-preparation and comprehensive coverage of the wide thyronome concentration range are presented. Conventional immunoassay versus LC-MS/MS-based determination of total and free THM concentrations are briefly compared.


2022 ◽  
pp. 163-186
Author(s):  
Shaojin Wang ◽  
Yvan Llave ◽  
Fanbin Kong ◽  
Francesco Marra ◽  
Ferruh Erdoğdu

2011 ◽  
Vol 19 (1) ◽  
pp. 1-36 ◽  
Author(s):  
Tom Froese ◽  
Ezequiel A. Di Paolo

There is a small but growing community of researchers spanning a spectrum of disciplines which are united in rejecting the still dominant computationalist paradigm in favor of the enactive approach. The framework of this approach is centered on a core set of ideas, such as autonomy, sense-making, emergence, embodiment, and experience. These concepts are finding novel applications in a diverse range of areas. One hot topic has been the establishment of an enactive approach to social interaction. The main purpose of this paper is to serve as an advanced entry point into these recent developments. It accomplishes this task in a twofold manner: (i) it provides a succinct synthesis of the most important core ideas and arguments in the theoretical framework of the enactive approach, and (ii) it uses this synthesis to refine the current enactive approach to social interaction. A new operational definition of social interaction is proposed which not only emphasizes the cognitive agency of the individuals and the irreducibility of the interaction process itself, but also the need for jointly co-regulated action. It is suggested that this revised conception of ‘socio-cognitive interaction’ may provide the necessary middle ground from which to understand the confluence of biological and cultural values in personal action.


Bioanalysis ◽  
2017 ◽  
Vol 9 (16) ◽  
pp. 1265-1278 ◽  
Author(s):  
Pooja Sukhdev Dhurjad ◽  
Vamsi Krishna Marothu ◽  
Rajeshwari Rathod

2016 ◽  
Vol 33 (5) ◽  
pp. 5-8 ◽  
Author(s):  
Peter Fernandez

Purpose This is the second of a two-part series on artificial intelligence (AI). The first column summarized some of the basic concepts necessary to understand AI and why recent developments indicate that it is poised to radically transform an array of emerging technologies. Design/methodology/approach This column will assume some basic knowledge of AI, to more fully explore how this technology is likely to impact libraries in the future in the areas of search, educational technology and logistics. Findings At its core, AI is a group of technologies that attempts to enable computers to solve problems in more dynamic ways than they previously have been able to do. Often, these efforts are conceptualized as replicating human intelligence in their functionality, even if they often use radically different underlying methods. Originality/value One key difference is that computers have inherent advantages over humans in absorbing and processing certain types of data. As a result, what can be done once a computer is capable of making more complex inferences can be truly remarkable, particularly when AI is used to empower humans in accomplishing otherwise tedious or difficult tasks.


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