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Staphylococcus aureus

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Covalent Functionalization of Graphene Sheets with Different Moieties and Their Effects on Biological Activities.

ACS biomaterials science & engineering
The ongoing spread of multi-drug-resistant bacteria over the past few decades necessitates collateral efforts to develop new classes of antibacterial agents with different mechanisms of action. The utilization of graphene nanosheets has recently gain...

Synthesis and biological characterization of MnZnEuDyFeO nanoparticles by sonochemical approach.

Materials science & engineering. C, Materials for biological applications
Metallic nanoparticles (NPs) possess unique properties which makes them attractive candidates for various applications especially in field of experimental medicine and drug delivery. Many approaches were developed to synthesize divers and customized ...

Machine Learning in Mass Spectrometry: A MALDI-TOF MS Approach to Phenotypic Antibacterial Screening.

Journal of medicinal chemistry
Machine learning techniques can be applied to MALDI-TOF mass spectral data of drug-treated cells to obtain classification models which assign the mechanism of action of drugs. Here, we present an example application of this concept to the screening o...

Machine learning-driven electronic identifications of single pathogenic bacteria.

Scientific reports
A rapid method for screening pathogens can revolutionize health care by enabling infection control through medication before symptom. Here we report on label-free single-cell identifications of clinically-important pathogenic bacteria by using a poly...

Prediction of rifampicin resistance beyond the RRDR using structure-based machine learning approaches.

Scientific reports
Rifampicin resistance is a major therapeutic challenge, particularly in tuberculosis, leprosy, P. aeruginosa and S. aureus infections, where it develops via missense mutations in gene rpoB. Previously we have highlighted that these mutations reduce p...

MALDI-TOF MS platform combined with machine learning to establish a model for rapid identification of methicillin-resistant Staphylococcus aureus.

Journal of microbiological methods
MALDI-TOF MS is an effective potential tool to distinguish between MSSA and MRSA. By combining the ClinProTools3.0 software and manual grouping intervention, we proposed a model optimization method for the first time. The cross validation of the mode...

Integrated meta-analysis and machine learning approach identifies acyl-CoA thioesterase with other novel genes responsible for biofilm development in Staphylococcus aureus.

Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases
Biofilm forming Staphylococcus aureus is a major threat to the health-care industry. It is important to understand the differences between planktonic and biofilm growth forms in the pathogen since conventional treatments targeting the planktonic form...

iModulonDB: a knowledgebase of microbial transcriptional regulation derived from machine learning.

Nucleic acids research
Independent component analysis (ICA) of bacterial transcriptomes has emerged as a powerful tool for obtaining co-regulated, independently-modulated gene sets (iModulons), inferring their activities across a range of conditions, and enabling their ass...

Antibiofilm Activity of α-Amylase from Bacillus subtilis and Prediction of the Optimized Conditions for Biofilm Removal by Response Surface Methodology (RSM) and Artificial Neural Network (ANN).

Applied biochemistry and biotechnology
α-amylase is known to have antibiofilm activity against biofilms of both Gram positive and Gram-negative bacterial strains. Partially purified α-amylase from Bacillus subtilis was found to have inhibit biofilm formed by P. aeruginosa and S. aureus. T...