Research Keyword: fungal-fungal interactions

Automatic classification of fungal-fungal interactions using deep learning models

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Researchers developed a computer artificial intelligence system that can automatically analyze images of fungal interactions to identify strains that could help control harmful crop diseases. Instead of having humans manually examine thousands of fungal culture plates—a slow and subjective process—the AI system can now classify the interactions between beneficial fungi and plant pathogens with 95% accuracy. This breakthrough significantly speeds up the search for natural alternatives to synthetic pesticides, supporting sustainable agriculture and food security.

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Coexistence of Malassezia Species and Microsporum canis in the Lesions of Adult with Tinea Capitis

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A 60-year-old woman developed unusual hair loss and scalp inflammation that looked like dandruff but was actually a fungal infection caused by multiple fungi working together. Doctors found three different fungi in her scalp samples: one dermatophyte and two Malassezia species. Lab experiments showed that the Malassezia fungi actually helped the main disease-causing fungus grow better, which explains why the condition looked different from typical cases. After three months of antifungal medication, her symptoms cleared and her hair grew back.

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Carbon substrates utilization determine antagonistic fungal-fungal interactions among root-associated fungi

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Scientists studied how different fungi in plant roots compete with disease-causing fungi. They found that fungi with different eating habits (carbon substrate preferences) fight off plant pathogens in different ways. Some fungi that eat many types of food produced toxic compounds to kill pathogens, while others competed directly for food. This discovery could help farmers use beneficial fungi to naturally protect crops from diseases.

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