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Microbial Sensitivity Tests

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Antimicrobial Activity Classification of Imidazolium Derivatives Predicted by Artificial Neural Networks.

Pharmaceutical research
PURPOSE: This study assesses the Multilayer Perceptron (MLP) neural network, complemented by other Machine Learning techniques (CART, PCA), in predicting the antimicrobial activity of 140 newly designed imidazolium chlorides against Klebsiella pneumo...

Combining deep learning and droplet microfluidics for rapid and label-free antimicrobial susceptibility testing of colistin.

Biosensors & bioelectronics
Efficient tools for rapid antibiotic susceptibility testing (AST) are crucial for appropriate use of antibiotics, especially colistin, which is now often considered a last resort therapy with extremely drug resistant Gram-negative bacteria. Here, we ...

Determination of minimum inhibitory concentrations using machine-learning-assisted agar dilution.

Microbiology spectrum
UNLABELLED: Effective policy to address the global threat of antimicrobial resistance requires robust antimicrobial susceptibility data. Traditional methods for measuring minimum inhibitory concentration (MIC) are resource intensive, subject to human...

Machine learning and genetic algorithm-guided directed evolution for the development of antimicrobial peptides.

Journal of advanced research
INTRODUCTION: Antimicrobial peptides (AMPs) are valuable alternatives to traditional antibiotics, possess a variety of potent biological activities and exhibit immunomodulatory effects that alleviate difficult-to-treat infections. Clarifying the stru...

Machine Learning Accelerates De Novo Design of Antimicrobial Peptides.

Interdisciplinary sciences, computational life sciences
Efficient and precise design of antimicrobial peptides (AMPs) is of great importance in the field of AMP development. Computing provides opportunities for peptide de novo design. In the present investigation, a new machine learning-based AMP predicti...

Anticandidal effectiveness of greenly synthesized zinc oxide nanoparticles against candidal pathogens.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
Drug resistance of pathogenic candidal strains to conventional antifungal agents represents a significant health issue contributing to high morbidity worldwide. Hence, the aim of the current study focused on evaluating the antifungal and synergistic ...

TB-DROP: deep learning-based drug resistance prediction of Mycobacterium tuberculosis utilizing whole genome mutations.

BMC genomics
The most widely practiced strategy for constructing the deep learning (DL) prediction model for drug resistance of Mycobacterium tuberculosis (MTB) involves the adoption of ready-made and state-of-the-art architectures usually proposed for non-biolog...

inhibition of biofilm and virulence factor production in azole-resistant strains of isolated from diabetic foot by stabilized tin (IV) oxide nanoparticles.

Frontiers in cellular and infection microbiology
The advent of nanotechnology has been instrumental in the development of new drugs with novel targets. Recently, metallic nanoparticles have emerged as potential candidates to combat the threat of drug-resistant infections. Diabetic foot ulcers (DFUs...

Effect of palladium(II) complexes on NorA efflux pump inhibition and resensitization of fluoroquinolone-resistant : and approach.

Frontiers in cellular and infection microbiology
leads to diverse infections, and their treatment relies on the use of antibiotics. Nevertheless, the rise of antibiotic resistance poses an escalating challenge and various mechanisms contribute to antibiotic resistance, including modifications to d...

Deciphering complex antibiotic resistance patterns in through whole genome sequencing and machine learning.

Frontiers in cellular and infection microbiology
INTRODUCTION: Helicobacter pylori (H.pylori, Hp) affects billions of people worldwide. However, the emerging resistance of Hp to antibiotics challenges the effectiveness of current treatments. Investigating the genotype-phenotype connection for Hp us...