AIMC Topic: Staphylococcus aureus
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Mapping quorum sensing onto neural networks to understand collective decision making in heterogeneous microbial communities.
Physical biology
Jul 19, 2017
Microbial communities frequently communicate via quorum sensing (QS), where cells produce, secrete, and respond to a threshold level of an autoinducer (AI) molecule, thereby modulating gene expression. However, the biology of QS remains incompletely ...
Adherence of staphylococcus aureus to catheter tubing inhibition by quaternary ammonium compounds.
The Pan African medical journal
Sep 29, 2016
INTRODUCTION: is a Gram positive bacterium which is responsible for a wide range of infections. This pathogen has also the ability to adhere to biotic or abiotic surface such as central venous catheter (CVC) and to produce a biofilm. The aim of this...
Hybrid Network Model for "Deep Learning" of Chemical Data: Application to Antimicrobial Peptides.
Molecular informatics
Mar 10, 2016
We present a "deep" network architecture for chemical data analysis and classification together with a prospective proof-of-concept application. The model features a self-organizing map (SOM) as the input layer of a feedforward neural network. The SO...
New Derivatives of Pyridoxine Exhibit High Antibacterial Activity against Biofilm-Embedded Staphylococcus Cells.
BioMed research international
Dec 29, 2015
Opportunistic bacteria Staphylococcus aureus and Staphylococcus epidermidis often form rigid biofilms on tissues and inorganic surfaces. In the biofilm bacterial cells are embedded in a self-produced polysaccharide matrix and thereby are inaccessible...
Choose wisely: Network, ontology and annotation resources for the analysis of Staphylococcus aureus omics data.
International journal of medical microbiology : IJMM
Feb 14, 2015
Staphylococcus aureus (S. aureus) is a prominent human and livestock pathogen investigated widely using omic technologies. Critically, due to availability, low visibility or scattered resources, robust network and statistical contextualisation of the...
Antibacterial, Antifreezing, and Tough Electronic Skin Based on a Tanned Collagen Fiber Network for Underwater Grabber Application.
ACS applied materials & interfaces
Jul 9, 2025
The environment of underwater salvage is very special, and many factors such as real-time water conditions, the depth of salvage, and the complexity of underwater conditions could greatly affect the smooth progress of the salvage process. How to accu...
Preparation of Active On-Demand Antibacterial Hydrogel Epidermis Electrodes Based on Flora Balance Strategy for Intelligent Prostheses.
ACS applied materials & interfaces
Jun 25, 2025
Hydrogel epidermis electrodes have demonstrated remarkable potential for stable electrophysiological signal acquisition in the field of intelligent prostheses. However, current hydrogel electrodes face challenges in providing on-demand antibacterial ...
Active capture-directed bimetallic nanosubstrate for enhanced SERS detection of Staphylococcus aureus by combining strand exchange amplification and wavelength-selective machine learning.
Biosensors & bioelectronics
Jun 15, 2025
Staphylococcus aureus (S. aureus) is the leading risk factor for food safety and human health. Herein, a novel wavelength-selective machine learning -driven adaptive strand exchange amplification (SEA)/SERS biosensor was developed for rapid detection...
Femtosecond Laser Treatment of Ti Surfaces: Antibacterial Mechanisms and Deep Learning-Based Surface Recognition.
ACS biomaterials science & engineering
Jun 9, 2025
Bacterial infections have been demonstrated to cause the premature failure of implants. A reliable strategy for preserving biocompatibility is to physically modify the implant surface, without using chemicals, to prevent bacterial adhesion. This stud...
Prediction of bloodstream infection using machine learning based primarily on biochemical data.
Scientific reports
May 20, 2025
Early diagnosis of bloodstream infection (BSI) is crucial for informed antibiotic use. This study developed a machine learning approach for early BSI detection using a comprehensive dataset from Rigshospitalet, Denmark (2010-2020). The dataset includ...
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