scholarly journals Conducting polymer-based sensors for food and drug analysis

2021 ◽  
Vol 29 (4) ◽  
pp. 544-558
Author(s):  
Chia-Hsin Lin ◽  
Jia-Hui Lin ◽  
Chien-Fu Chen ◽  
Yoshihiro Ito ◽  
Shyh-Chyang Luo
Planta Medica ◽  
2013 ◽  
Vol 79 (05) ◽  
Author(s):  
PE Balbas ◽  
JE Briones ◽  
JA Camposano ◽  
DI Carrido ◽  
KM Convento ◽  
...  

2016 ◽  
Vol 4 (2) ◽  
pp. 1
Author(s):  
KUMAR RAJIV ◽  
SHARMA SHUCHI ◽  
DHIMAN NARESH ◽  
PATHAK DINESH ◽  
◽  
...  

Author(s):  
Zhixian Liu ◽  
Qingfeng Chen ◽  
Wei Lan ◽  
Jiahai Liang ◽  
Yiping Pheobe Chen ◽  
...  

: Traditional network-based computational methods have shown good results in drug analysis and prediction. However, these methods are time consuming and lack universality, and it is difficult to exploit the auxiliary information of nodes and edges. Network embedding provides a promising way for alleviating the above problems by transforming network into a low-dimensional space while preserving network structure and auxiliary information. This thus facilitates the application of machine learning algorithms for subsequent processing. Network embedding has been introduced into drug analysis and prediction in the last few years, and has shown superior performance over traditional methods. However, there is no systematic review of this issue. This article offers a comprehensive survey of the primary network embedding methods and their applications in drug analysis and prediction. The network embedding technologies applied in homogeneous network and heterogeneous network are investigated and compared, including matrix decomposition, random walk, and deep learning. Especially, the Graph neural network (GNN) methods in deep learning are highlighted. Further, the applications of network embedding in drug similarity estimation, drug-target interaction prediction, adverse drug reactions prediction, protein function and therapeutic peptides prediction are discussed. Several future potential research directions are also discussed.


2020 ◽  
Vol 16 ◽  
Author(s):  
Huseyin Senturk ◽  
Hakan Karadeniz ◽  
Arzum Erdem

: Regarding to the development of nanomaterials, they could be widely used in electrochemical drug analysis due to their unique physical and chemical properties. Herein, we presented a general perspective to different nanomaterials based electrochemical approaches developed for drug analysis, that were performed in the last decade while summarizing their advantages with further applications.


Author(s):  
Dr. Jyothi B. ◽  
Dr. M. V. Sobagin ◽  
Dr. M.C. Patil

Background: Abhra Sindoora[1] (ABS) is a unique Rasa Yoga with having more potent and indication in Tridoshahara, Swasa, Kasa etc. It is one of the important classical Kupipakva Rasayana containing Hingulotha Parada (purified mercury), Shuddha Gandhaka (purified sulfur) and Dhanyabhraka in 1:1:1 proportion. Aim: Pharmaceutico-Analytical study of Abhra Sindoora. Materials and Methods: Hingulotha Parada (purified mercury), Shuddha Gandhaka (purified sulfur) and Dhanyabhraka are used to prepare Kajjali and lavigated with Vatankura (leaf buds of Ficus bengalensis), Swarasa (juice) and Arka (Calotrapis procera) ksheera (milk). This Kajjali is processed by Kupipakva method. Results and Conclusion: The current trend in applied instrumental medical research encourages good medical practice, clinical and research based drug analysis. The main aim of analytical study is to find out working standards for the formulations and safe use of therapeutics. Abhra Sindoora was prepared in 48 hours with 28% yield. It was also characterized by using modern instrumental analysis like XRD, SEMEDX, EDXRF, FTIR and PARTICLE ANALYSIS. The SEM analysis evaluated that prepared Abhra Sindoora has particles in nanometers, least being 14.87nm. SEMEDX study confirmed the presence of C, O, Si, S, K, and HgM. XRD study confirmed the presence of Hg3.00S3.00 in hexagonal crystal system. The EDXRF analysis evaluated the presence of K, Ca, Ti, Mn, Fe, S, Br and Hg. FTIR analysis shows organic compounds with functional groups like secondary amines, Nitro, Carboxylic acids, Bromine, Esters, Alkines, and Iodides etc.


Sign in / Sign up

Export Citation Format

Share Document