AIMC Topic: Pseudomonas aeruginosa

Clear Filters Showing 21 to 30 of 63 articles

Nonionic surfactant Tween 80-facilitated bacterial transport in porous media: A nonmonotonic concentration-dependent performance, mechanism, and machine learning prediction.

Environmental research
The surfactant-enhanced bioremediation (SEBR) of organic-contaminated soil is a promising soil remediation technology, in which surfactants not only mobilize pollutants, but also alter the mobility of bacteria. However, the bacterial response and und...

Machine learning identification of Pseudomonas aeruginosa strains from colony image data.

PLoS computational biology
When grown on agar surfaces, microbes can produce distinct multicellular spatial structures called colonies, which contain characteristic sizes, shapes, edges, textures, and degrees of opacity and color. For over one hundred years, researchers have u...

Rapid Discrimination of ST175 Isolates Involved in a Nosocomial Outbreak Using MALDI-TOF Mass Spectrometry and FTIR Spectroscopy Coupled with Machine Learning.

Transboundary and emerging diseases
The goal of this study was to evaluate matrix-assisted laser desorption ionization-iime of flight mass spectrometry (MALDI-TOF MS) and Fourier-transform infrared spectroscopy (FTIR-S) as diagnostic alternatives to DNA-based methods for the detection ...

The Microorganism Detection System (SDM) for microbiological control of cosmetic products.

Annals of agricultural and environmental medicine : AAEM
The Microorganism Detection System (SDM) is a new solution using artificial intelligence, unique on the international scale, to correctly identify and count microorganisms, with particular emphasis on specificlisted microorganisms (Document of Standa...

Genome-Wide Mutation Scoring for Machine-Learning-Based Antimicrobial Resistance Prediction.

International journal of molecular sciences
The prediction of antimicrobial resistance (AMR) based on genomic information can improve patient outcomes. Genetic mechanisms have been shown to explain AMR with accuracies in line with standard microbiology laboratory testing. To translate genetic ...

Decreased neutrophil-mediated bacterial killing in COVID-19 patients.

Scandinavian journal of immunology
The coronavirus disease COVID-19 was first described in December 2019. The peripheral blood of COVID-19 patients have increased numbers of neutrophils which are important in controlling the bacterial infections observed in COVID-19. We sought to eval...

A first perturbome of Pseudomonas aeruginosa: Identification of core genes related to multiple perturbations by a machine learning approach.

Bio Systems
Tolerance to stress conditions is vital for organismal survival, including bacteria under specific environmental conditions, antibiotics, and other perturbations. Some studies have described common modulation and shared genes during stress response t...

QSAR Models for Active Substances against Using Disk-Diffusion Test Data.

Molecules (Basel, Switzerland)
is a Gram-negative bacillus included among the six "ESKAPE" microbial species with an outstanding ability to "escape" currently used antibiotics and developing new antibiotics against it is of the highest priority. Whereas minimum inhibitory concent...

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...