Geometric mean MIC – mycolab.ai

Identification and antifungal susceptibility patterns of reference yeast strains to novel and conventional agents: a comparative study using CLSI, EUCAST and Sensititre YeastOne methods

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Researchers compared three different laboratory methods for testing how well antifungal drugs work against common yeast infections. They tested 22 different yeast strains including Candida species using CLSI, EUCAST, and Sensititre YeastOne methods. The methods showed strong agreement overall, but some newer antifungal drugs like ibrexafungerp showed more variation between methods. The findings suggest these methods are reliable for guiding treatment decisions, but further standardization is needed for newer drugs.

Molecular epidemiology, diversity, and antifungal susceptibility profiles of clinical and environmental mucorales: a five-year multicenter study in Iran (2018–2023)

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This research examined dangerous mold infections (Mucormycosis) that became more common after COVID-19. Scientists identified the types of molds causing these infections in Iran by testing 116 patient samples and 65 soil samples from across the country. They tested these molds against 13 different antifungal medications to find which drugs work best. The results showed that amphotericin B and posaconazole were the most effective medications, and patient samples were more susceptible to these drugs than environmental soil samples.

Research Keyword: Geometric mean MIC

Identification and antifungal susceptibility patterns of reference yeast strains to novel and conventional agents: a comparative study using CLSI, EUCAST and Sensititre YeastOne methods

Molecular epidemiology, diversity, and antifungal susceptibility profiles of clinical and environmental mucorales: a five-year multicenter study in Iran (2018–2023)