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Anti-Bacterial Agents

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[Effect of enzybiotics on the healing of Staphylococcus aureus-infected skin wounds in a pig model].

Klinicka mikrobiologie a infekcni lekarstvi
INTRODUCTION: Staphylococcus aureus is a gram-positive, facultatively anaerobic coccus capable of causing infectious diseases in animals and humans. Especially dangerous are multidrug-resistant forms with poor or even no response to available treatme...

Using genomic data and machine learning to predict antibiotic resistance: A tutorial paper.

PLoS computational biology
Antibiotic resistance is a global public health concern. Bacteria have evolved resistance to most antibiotics, which means that for any given bacterial infection, the bacteria may be resistant to one or several antibiotics. It has been suggested that...

Explainable deep learning and virtual evolution identifies antimicrobial peptides with activity against multidrug-resistant human pathogens.

Nature microbiology
Artificial intelligence (AI) is a promising approach to identify new antimicrobial compounds in diverse microbial species. Here we developed an AI-based, explainable deep learning model, EvoGradient, that predicts the potency of antimicrobial peptide...

Artificial Neural Network-Based Validation, DFT, Thermal and Biological Evaluation of 4-Aminoantipyrine-Derived Ru(III) Complexes.

Applied biochemistry and biotechnology
New methodologies have been evaluated for validating analytical characterization with artificial neural networks (ANNs). Compared to previous machine learning models, these provide more accurate and automated results with high testing accuracy. The S...

ARGai 1.0: A GAN augmented in silico approach for identifying resistant genes and strains in E. coli using vision transformer.

Computational biology and chemistry
The emergence of infectious disease and antibiotic resistance in bacteria like Escherichia coli (E. coli) shows the necessity for novel computational techniques for identifying essential genes that contribute to resistance. The task of identifying re...

Phenotypic antibiotic resistance prediction using antibiotic resistance genes and machine learning models in Mannheimia haemolytica.

Veterinary microbiology
Mannheimia haemolytica is one of the most common causative agents of bovine respiratory disease (BRD); however, antibiotic resistance in this species is increasing, making treatment more difficult. Integrative-conjugative elements (ICE), a subset of ...

Kinetics, central composite design and artificial neural network modelling of ciprofloxacin antibiotic photodegradation using fabricated cobalt-doped zinc oxide nanoparticles.

Scientific reports
Cobalt-doped zinc oxide nanoparticles were fabricated and examined in this study as a potential photocatalyst for the antibiotic ciprofloxacin (CIPF) degradation when exposed to visible LED light. The Co-precipitation technique created Cobalt-doped z...

Trace detection of antibiotics in wastewater using tunable core-shell nanoparticles SERS substrate combined with machine learning algorithms.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Surface-enhanced Raman scattering (SERS) show great potential for rapid and highly sensitive detection of trace amounts of contamination from the environment in the surface aquatic ecosystem. The widespread use of antibiotics has resulted in serious ...

Measuring water pollution effects on antimicrobial resistance through explainable artificial intelligence.

Environmental pollution (Barking, Essex : 1987)
Antimicrobial resistance refers to the ability of pathogens to develop resistance to drugs designed to eliminate them, making the infections they cause more difficult to treat and increasing the likelihood of disease diffusion and mortality. As such,...

Optimal selection of machine learning algorithms for ciprofloxacin prediction based on conventional water quality indicators.

Ecotoxicology and environmental safety
The long-term presence of antibiotics in the aquatic environment will affect ecology and human health. Techniques for determining antibiotics are often time-consuming, labor-intensive and costly, and it is desirable to seek new methods to achieve rap...