Disease: invasive mold infections

Evaluation of the combined efficacy of inhibitors of heat shock protein 90 and calcineurin with commonly used antifungals against Aspergillus, Rhizopus, and Fusarium isolates

Scientists tested combinations of common antifungal medications with special inhibitor drugs that target fungal stress-response systems. When combined, these drugs worked better together against dangerous mold infections like Aspergillus and Rhizopus, especially those that are resistant to standard treatments. The combinations rarely caused harmful interactions and often enhanced the antifungal effects, suggesting this approach could improve treatment of serious mold infections.

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Performance of the VITEK® MS system for the identification of filamentous fungi in a microbiological laboratory in Chile

Researchers tested a fast machine called VITEK® MS for identifying dangerous mold infections in patients. The machine correctly identified over 91% of fungal samples, which is much better than waiting weeks for traditional laboratory methods. This technology could help doctors start treatment much faster for patients with serious mold infections, potentially saving lives.

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Performance of the VITEK® MS system for the identification of filamentous fungi in a microbiological laboratory in Chile

This study tested a new laboratory technology called VITEK® MS for quickly identifying mold infections in patients. Researchers tested the system on 67 mold samples representing 35 different species. The technology successfully identified over 91% of the mold samples accurately without any misidentifications, making it a reliable tool for hospitals to quickly determine what type of mold is causing an infection so doctors can prescribe the right antifungal medication.

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Performance of the VITEK® MS system for the identification of filamentous fungi in a microbiological laboratory in Chile

This study tested a rapid fungal identification system called VITEK® MS in a Chilean hospital laboratory. The system uses mass spectrometry technology to identify mold species quickly and accurately, often within 48-72 hours. Results showed the system correctly identified over 91% of fungal samples without any mistakes, making it a valuable tool for diagnosing serious fungal infections in hospitalized patients.

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