AIMC Topic: Antifungal Agents

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Coupling machine learning and epidemiological modelling to characterise optimal fungicide doses when fungicide resistance is partial or quantitative.

Journal of the Royal Society, Interface Apr 19, 2023
Increasing fungicide dose tends to lead to better short-term control of plant diseases. However, high doses select more rapidly for fungicide resistant strains, reducing long-term disease control. When resistance is qualitative and complete-i.e. resi...
Mycoses Models, Biological Drug Resistance, Fungal Humans Machine Learning Antifungal Agents
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Impact of ANN in Revealing of Viral Peptides.

BioMed research international Aug 8, 2022
All organisms contain antimicrobial peptides (AMPs), which are a critical component of the innate immune system. These chemicals have the ability to suppress the growth of a variety of fungi, bacteria, and viruses. Because AMPs interact with structur...
Computer Simulation Peptides Antifungal Agents Neural Networks, Computer Algorithms
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Machine learning approach for predicting the antifungal effect of gilaburu (Viburnum opulus) fruit extracts on Fusarium spp. isolated from diseased potato tubers.

Journal of microbiological methods Nov 19, 2021
This work addresses the mathematical model building to detect the diameter of the inhibition zone of gilaburu (Viburnum opulus L.) extract against eight different Fusarium strains isolated from diseased potato tubers. Gilaburu extracts were obtained ...
Machine Learning Algorithms Antioxidants Viburnum Fusarium Plant Extracts Disk Diffusion Antimicrobial Tests Food Microbiology Solanum tuberosum Antifungal Agents
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Leveraging machine learning essentiality predictions and chemogenomic interactions to identify antifungal targets.

Nature communications Nov 11, 2021
Fungal pathogens pose a global threat to human health, with Candida albicans among the leading killers. Systematic analysis of essential genes provides a powerful strategy to discover potential antifungal targets. Here, we build a machine learning mo...
Kinetochores Machine Learning Genome-Wide Association Study Systems Biology Candida albicans Antifungal Agents
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Comparison of the Antifungal Efficacy of Four Concentrations of (Muña) Essential Oil against An Study.

The journal of contemporary dental practice Nov 1, 2021
AIM AND OBJECTIVE: This paper aims to compare the antifungal efficacy of four concentrations of essential oil (MEO) against ATCC 10231.
Fluconazole Microbial Sensitivity Tests Oils, Volatile Candida albicans Antifungal Agents
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Lemongrass-Incorporated Tissue Conditioner with Adjustable Inhibitory Effect Against Candida albicans: An In Vitro Study.

The International journal of prosthodontics Oct 5, 2021
PURPOSE: To develop and assess lemongrass-incorporated tissue conditioners (LG-TCs) with a potent and long-lasting inhibitory effect against Candida albicans cultures to control the accumulation of fungi.
Nystatin Tissue Conditioning, Dental Candida albicans Oils, Volatile Antifungal Agents Water Cymbopogon
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Application of Design of Experiments® Approach-Driven Artificial Intelligence and Machine Learning for Systematic Optimization of Reverse Phase High Performance Liquid Chromatography Method to Analyze Simultaneously Two Drugs (Cyclosporin A and Etodolac) in Solution, Human Plasma, Nanocapsules, and Emulsions.

AAPS PharmSciTech May 13, 2021
The objectives of current investigation are (1) to find out wavelength of maximum absorbance (λ) for combined cyclosporin A and etodolac solution followed by selection of mobile phase suitable for the RP-HPLC method, (2) to define analytical target p...
Antifungal Agents Chromatography, High Pressure Liquid Emulsions Algorithms Research Design Cyclosporine Nanocapsules Chromatography, Reverse-Phase Etodolac Humans Neural Networks, Computer Artificial Intelligence Machine Learning
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Deep-learning based repurposing of FDA-approved drugs against dihydrofolate reductase and molecular dynamics study.

Journal of biomolecular structure & dynamics Apr 21, 2021
causes the fatal fungal bloodstream infection in humans called Candidiasis. Most of the species are resistant to the antifungals used to treat them. Drug-resistant poses very serious public health issues. To overcome this, the development of effec...
Tetrahydrofolate Dehydrogenase Humans Benzodioxoles Rifampin Folic Acid Antagonists Candidiasis Aminopyridines Candida albicans Antifungal Agents Lactams, Macrocyclic Cyclopropanes Sulfonamides Molecular Dynamics Simulation Molecular Docking Simulation Drug Approval Drug Repositioning Deep Learning United States Food and Drug Administration United States Proline
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Machine learning approach for predicting Fusarium culmorum and F. proliferatum growth and mycotoxin production in treatments with ethylene-vinyl alcohol copolymer films containing pure components of essential oils.

International journal of food microbiology Dec 3, 2020
Fusarium culmorum and F. proliferatum can grow and produce, respectively, zearalenone (ZEA) and fumonisins (FUM) in different points of the food chain. Application of antifungal chemicals to control these fungi and mycotoxins increases the risk of to...
Food Microbiology Antifungal Agents Mycotoxins Machine Learning Fusarium Oils, Volatile Polyvinyls
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Piperidine based 1,2,3-triazolylacetamide derivatives induce cell cycle arrest and apoptotic cell death in .

Journal of advanced research Nov 10, 2020
The fungal pathogen , is a serious threat to public health and is associated with bloodstream infections causing high mortality particularly in patients with serious medical problems. As this pathogen is generally resistant to all the available clas...
Microbial Sensitivity Tests Apoptosis Cell Survival Humans Public Health DNA Damage Candida Triazoles Drug Resistance, Fungal Acetamides Candidiasis Piperidines Cell Cycle Checkpoints Antifungal Agents
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