scholarly journals Prediction of the antimicrobial activity of quaternary ammonium salts against Staphylococcus aureus using artificial neural networks

2021 ◽  
pp. 103233
Author(s):  
Anna Badura ◽  
Jerzy Krysiński ◽  
Alicja Nowaczyk ◽  
Adam Buciński
Keyword(s):  
Neural Networks ◽  
Staphylococcus Aureus ◽  
Antimicrobial Activity ◽  
Artificial Neural Networks ◽  
Quaternary Ammonium ◽  
Quaternary Ammonium Salts ◽  
Ammonium Salts ◽  
Artificial Neural

scholarly journals Biological Activity of Quaternary Ammonium Salts and Their Derivatives

Pathogens ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 459 ◽  
Author(s):  
Dobrawa Kwaśniewska ◽  
Ying-Lien Chen ◽  
Daria Wieczorek
Keyword(s):  
Antimicrobial Activity ◽  
Biological Activity ◽  
Quaternary Ammonium ◽  
Quaternary Ammonium Salts ◽  
Ammonium Salts ◽  
Food Spoilage ◽  
Biocidal Activity ◽  
Positive Role ◽  
Current State ◽  
Potential Use

Besides their positive role, microorganisms are related to a number of undesirable effects, including many diseases, biodeterioration and food spoilage, so when their presence is undesired, they must be controlled. Numerous biocides limiting the development of microorganisms have been proposed, however, in this paper the biocidal and inhibitory activity of quaternary ammonium salts (QASs) and their zwitterionic derivatives is addressed. This paper presents the current state of knowledge about the biocidal activity of QAS and their derivatives. Moreover, the known mechanisms of antimicrobial activity and the problem of emerging resistance to QAS are discussed. The latest trends in the study of surfactants and their potential use are also presented.

Antimicrobial Activity of Quaternary Ammonium Salts of Some Saturated Heterocycloalkyl Amines [1]

1979 ◽  
Vol 34 (5-6) ◽  
pp. 485-486 ◽  
Author(s):  
Ivan Lacko ◽  
Ferdinand Devínsky ◽  
Ľudovít Krasnec ◽  
Dušan Mlynarčik
Keyword(s):  
Antimicrobial Activity ◽  
Quaternary Ammonium ◽  
Alkyl Chain ◽  
Heterocyclic Ring ◽  
Substantial Effect ◽  
Quaternary Ammonium Salts ◽  
Heterocyclic Amines ◽  
Ammonium Salts ◽  
Activity Change ◽  
Inhibition Concentration

Abstract N,N-Dialkyl Ammonium Salts of Saturated Heterocyclic Amines, Antimicrobial Activity Antimicrobial activity of N-alkyl-N-dodecylpiperidinium bromides and N-ethyl-N-dodecylheterocycloalkyl ammonium bromides (pyrrolidine, morpholine, perhydroazepine) deter­ mined on grampositive and gramnegative bacteria, yeasts and moulds, presented as minimum inhibition concentration (MIC). Comparison of the effect of change of structure: lenghtening of alkyl chain, change of heterocyclic ring. Change in the lenght of alkyl chain markedly affects the antimicrobial activity, change of heterocyclic ring has no substantial effect. The most active compounds were N-heptyl-and N-hexyl-N-dodecylpiperidinium bromides.

ChemInform Abstract: Antimicrobial Agents. Part 6. Synthesis and Antimicrobial Activity of Some New Benzofuran Quaternary Ammonium Salts.

ChemInform ◽  
2010 ◽  
Vol 22 (31) ◽  
pp. no-no
Author(s):  
C. V. R. SASTRY ◽  
O. P. BANSAL ◽  
B. LAL ◽  
S. C. CHATURVEDI ◽  
J. S. SRINIVAS ◽  
...  
Keyword(s):  
Antimicrobial Activity ◽  
Quaternary Ammonium ◽  
Antimicrobial Agents ◽  
Quaternary Ammonium Salts ◽  
Ammonium Salts

scholarly journals Implementasi Jaringan Saraf Tiruan Sebagai Alat Bantu Deteksi Bakteri Staphylococcus Aureus Pada Sayuran

2020 ◽  
Vol 1 (3) ◽  
pp. 258
Author(s):  
Ali Rahmad Pohan
Keyword(s):  
Neural Networks ◽  
Image Processing ◽  
Staphylococcus Aureus ◽  
Image Segmentation ◽  
Artificial Neural Networks ◽  
Image Quality ◽  
Bacterial Detection ◽  
Image Characteristics ◽  
Reduce Image Quality ◽  
Artificial Neural

This study aims to aid bacterial detection through bacterial imagery in vegetables to help identify Staphylococcus aureus bacteria in vegetables. Input to the software is the image of bacteria in vegetables. Bacterial image is processed by grayscaling, thresholding and image segmentation processing methods so that the image characteristics that represent bacteria in vegetables are obtained. One technique that can be used as a tool to observe Staphylococcus aureus is to use artificial neural networks and combine them with image processing. Artificial neural networks function as information processing by inferring information from data that has been received and as a decision maker for data that has been studied. Image processing is the science of manipulating images, which includes techniques to improve or reduce image quality. The detection process using software that has been built can be done well. The process is carried out by matching the value of the exercise cutra backpropagation vector with the image to be detected.

scholarly journals Application of Artificial Intelligence to the Prediction of the Antimicrobial Activity of Essential Oils

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Mathieu Daynac ◽  
Alvaro Cortes-Cabrera ◽  
Jose M. Prieto
Keyword(s):  
Neural Networks ◽  
Antimicrobial Activity ◽  
Artificial Neural Networks ◽  
Essential Oils ◽  
Maximum Error ◽  
Antimicrobial Activities ◽  
Output Data ◽  
Chemical Variability ◽  
Artificial Neural ◽  
Disk Susceptibility

Essential oils (EOs) are vastly used as natural antibiotics in Complementary and Alternative Medicine (CAM). Their intrinsic chemical variability and synergisms/antagonisms between its components make difficult to ensure consistent effects through different batches. Our aim is to evaluate the use of artificial neural networks (ANNs) for the prediction of their antimicrobial activity.Methods.The chemical composition and antimicrobial activity of 49 EOs, extracts, and/or fractions was extracted from NCCLS compliant works. The fast artificial neural networks (FANN) software was used and the output data reflected the antimicrobial activity of these EOs against four common pathogens:Staphylococcus aureus, Escherichia coli, Candida albicans, andClostridium perfringensas measured by standardised disk diffusion assays.Results.ANNs were able to predict >70% of the antimicrobial activities within a 10 mm maximum error range. Similarly, ANNs were able to predict 2 or 3 different bioactivities at the same time. The accuracy of the prediction was only limited by the inherent errors of the popular antimicrobial disk susceptibility test and the nature of the pathogens.Conclusions.ANNs can be reliable, fast, and cheap tools for the prediction of the antimicrobial activity of EOs thus improving their use in CAM.

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