AIMC Topic: Fungi
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A critical review on occurrence, speciation, mobilization, and toxicity of per- and polyfluoroalkyl substances in the soil-microbe-plant system and bioremediation strategies.
Journal of hazardous materials
Aug 15, 2025
Per- and polyfluoroalkyl substances (PFAS) are a group of recalcitrant anthropogenic compounds that are extensively utilized for numerous industrial applications globally. Despite such vast utilization, PFAS accumulation in the soils and sediments wi...
The Biogeography of Soil Bacteria in Australia Exhibits Greater Resistance to Climate Change Than Fungi.
Global change biology
Jun 1, 2025
Soil microorganisms are crucial to ecosystem health, and their composition and distribution are shaped by a range of environmental factors. However, the effects of accelerating climate change on soil microbiomes remain under-explored. This study exam...
DeepMBEnzy: An AI-Driven Database of Mycotoxin Biotransformation Enzymes.
Journal of agricultural and food chemistry
May 28, 2025
Mycotoxins are toxic fungal metabolites that pose significant health risks. Enzyme biotransformation is a promising option for detoxifying mycotoxins and for elucidating their intracellular metabolism. However, few mycotoxin-biotransformation enzymes...
New Strategies and Artificial Intelligence Methods for the Mitigation of Toxigenic Fungi and Mycotoxins in Foods.
Toxins
May 7, 2025
The proliferation of toxigenic fungi in food and the subsequent production of mycotoxins constitute a significant concern in the fields of public health and consumer protection. This review highlights recent strategies and emerging methods aimed at p...
AI in fungal drug development: opportunities, challenges, and future outlook.
Frontiers in cellular and infection microbiology
Jan 1, 2025
The application of artificial intelligence (AI) in fungal drug development offers innovative strategies to address the escalating threat of fungal infections and the challenge of antifungal resistance. This review evaluates the current landscape of f...
From patterns to prediction: machine learning and antifungal resistance biomarker discovery.
Canadian journal of microbiology
Jan 1, 2025
Fungal pathogens significantly impact human health, agriculture, and ecosystems, with infections leading to high morbidity and mortality, especially among immunocompromised individuals. The increasing prevalence of antifungal resistance (AFR) exacerb...
Superficial Fungal Infections and Artificial Intelligence: A Review on Current Advances and Opportunities: REVISION.
Mycoses
Jan 1, 2025
BACKGROUND: Superficial fungal infections are among the most common infections in world, they mainly affect skin, nails and scalp without further invasion. Superficial fungal diseases are conventionally diagnosed with direct microscopy, fungal cultur...
Fungal names: a comprehensive nomenclatural repository and knowledge base for fungal taxonomy.
Nucleic acids research
Jan 6, 2023
Fungal taxonomy is a complex and rapidly changing subject, which makes proper naming of fungi challenging for taxonomists. A registration platform with a standardized and information-integrated database is a powerful tool for efficient research on fu...
A NLP Pipeline for the Automatic Extraction of Microorganisms Names from Microbiological Notes.
Studies in health technology and informatics
Oct 27, 2021
According to the "Istituto Superiore di Sanita'" (ISS), hospital infections are the most frequent and serious complication of health care. This constitutes a real health emergency which requires incisive and joint action at all levels of the local an...
Comprehensive assessment of machine learning-based methods for predicting antimicrobial peptides.
Briefings in bioinformatics
Sep 2, 2021
Antimicrobial peptides (AMPs) are a unique and diverse group of molecules that play a crucial role in a myriad of biological processes and cellular functions. AMP-related studies have become increasingly popular in recent years due to antimicrobial r...
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