Chronic Rat Toxicity Prediction of Chemical Compounds Using Kernel Machines

Author(s):  
Georg Hinselmann ◽  
Andreas Jahn ◽  
Nikolas Fechner ◽  
Andreas Zell
Author(s):  
GONGDE GUO ◽  
DANIEL NEAGU

A robust method, fuzzy kNNModel, for toxicity prediction of chemical compounds is proposed. The method is based on a supervised clustering method, called kNNModel, which employs fuzzy partitioning instead of crisp partitioning to group clusters. The merits of fuzzy kNNModel are two-fold: (1) it overcomes the problems of choosing the parameter ε — allowed error rate in a cluster and the parameter N — minimal number of instances covered by a cluster, for each data set; (2) it better captures the characteristics of boundary data by assigning them with different degrees of membership between 0 and 1 to different clusters. The experimental results of fuzzy kNNModel conducted on thirteen public data sets from UCI machine learning repository and seven toxicity data sets from real-world applications, are compared with the results of fuzzy c-means clustering, k-means clustering, kNN, fuzzy kNN, and kNNModel in terms of classification performance. This application shows that fuzzy kNNModel is a promising method for the toxicity prediction of chemical compounds.


Author(s):  
R. Courtoy ◽  
L.J. Simar ◽  
J. Christophe

Several chemical compounds induce amine liberation from mast cells but do not necessarily provoque the granule expulsion. For example, poly-dl-lysine induces modifications of the cellular membrane permeability which promotes ion exchange at the level of mast cell granules. Few of them are expulsed but the majority remains in the cytoplasm and appears less dense to the electrons. A cytochemical analysis has been performed to determine the composition of these granules after the polylysine action.We have previously reported that it was possible to demonstrate polyanions on epon thin sections using a cetylpyridinium ferric thiocyanate method. Organic bases are selectively stained with cobalt thiocyanate and the sulfhydryle groups are characterized with a silver methenamine reaction. These techniques permit to reveal the mast cell granule constituents, i.e. heparin, biogenic amines and basic proteins.


Author(s):  
E. I. Alessandrini ◽  
M. O. Aboelfotoh

Considerable interest has been generated in solid state reactions between thin films of near noble metals and silicon. These metals deposited on Si form numerous stable chemical compounds at low temperatures and have found applications as Schottky barrier contacts to silicon in VLSI devices. Since the very first phase that nucleates in contact with Si determines the barrier properties, the purpose of our study was to investigate the silicide formation of the near noble metals, Pd and Pt, at very thin thickness of the metal films on amorphous silicon.Films of Pd and Pt in the thickness range of 0.5nm to 20nm were made by room temperature evaporation on 40nm thick amorphous Si films, which were first deposited on 30nm thick amorphous Si3N4 membranes in a window configuration. The deposition rate was 0.1 to 0.5nm/sec and the pressure during deposition was 3 x 10 -7 Torr. The samples were annealed at temperatures in the range from 200° to 650°C in a furnace with helium purified by hot (950°C) Ti particles. Transmission electron microscopy and diffraction techniques were used to evaluate changes in structure and morphology of the phases formed as a function of metal thickness and annealing temperature.


Author(s):  
Jenan Mohammed Ubaid ◽  
Abeer Fauzi Al-Rubaye ◽  
Imad Hadi Hameed

Methanolic extract of bioactive compounds of Trogoderma granarium was assayed. GC-MS analysis of Trogoderma granarium revealed the existence of the Pentanoic acid , 1,1-dimethylpropyl ester , (1H)-Pyrimidinone , 5-chloro-4,6- diphenyl, Cyclobutanemethanol , α-methyl- , Nitro-2-methyl-1,3-propanediol , Hydroxylamine ,O-(2-methylpropyl)- , Uridine , 2',3'-O-(phenylmethylene)- ,Acetic acid ,2-benzoylthio-,2-oxo-2-phenylethyl ester , methylpropyl)- , Uridine , 2',3'-O-(phenylmethylene)- , 5'-(4-methylbenzenesulfo , Indolinol , 1-benzoyl-, Benzeneethanol , β-methyl-,(s)- , Acetic acid ,2-benzoylthio-,2-oxo-2-phenylethyl ester , Phenacyl thiocyanate , Deoxy-L-ribose-2,5-dibenzoate , Methenamine , Alanine , N-methyl-n-propargyloxycarbonyl-, decyl ester , Benzoyl chloride , Thiophene-2-ol , benzoate , Ethanone , -(5- nitrotetrazol-2-yl)-1-phenyl- , 2,5-Dimethylhexane-2,5-dihydroperoxide , Benzamide , N-(3-benzylthio-1,2,4-thiadiazol- 5-yl)- , Methyl p-(2-phenyl-1-benzimidazolyl)benzoate , Methyl-2-phenoxyethylamine , Pentaborane(11) , cis-Methoxy- 5-trans-methyl-1R-cyclohexanol , Nitro-1-phenyl-3-(tetrahydropyran-2-yloxy)propan-1-one , cis-Methoxy-5-transmethyl-1R-cyclohexanol. Trogoderma granarium produce many important secondary metabolites with high biological activities.


2019 ◽  
Author(s):  
Qiannan Duan ◽  
Jianchao Lee ◽  
Jinhong Gao ◽  
Jiayuan Chen ◽  
Yachao Lian ◽  
...  

<p>Machine learning (ML) has brought significant technological innovations in many fields, but it has not been widely embraced by most researchers of natural sciences to date. Traditional understanding and promotion of chemical analysis cannot meet the definition and requirement of big data for running of ML. Over the years, we focused on building a more versatile and low-cost approach to the acquisition of copious amounts of data containing in a chemical reaction. The generated data meet exclusively the thirst of ML when swimming in the vast space of chemical effect. As proof in this study, we carried out a case for acute toxicity test throughout the whole routine, from model building, chip preparation, data collection, and ML training. Such a strategy will probably play an important role in connecting ML with much research in natural science in the future.</p>


Author(s):  
Sabreen A Kamal ◽  
Ishraq A Salih ◽  
Hawraa Jawad Kadhim ◽  
Zainab A Tolaifeh

Red rose or roselle (beauty rose ) is natively known as red tea belong to Malvaceae, it is flowers use traditionally for antihypertensive hepato protective, anticancer,antidiabetic,antibacterial, cytotoxicity and antidiarreal, By preparing red tea from it's flower. In this study, we extract chemical compounds by using two solvent which are Ethanol, Ethyl acetate. so we can extract Anthocyanin which is responsible for red colour of flower with many chemical compounds. then study the effect of these extracts on 5 genera from Enterobacteriacaea which can cause diarrheae (Shigella, Salmonella, Escherichia coli, Proteus and Klebsiella ) by preparing 3 concentrations for each solvent (250, 500, 750 ) mg/ml, and control then compare with two antibiotic (Azereonam 30 mg/ml and Bacitracin 10 mg/ml ) these extracts revealed obvious inhibition zone in bacterial growth.


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