Breaking barriers in Candida spp. detection with Electronic Noses and artificial intelligence.

The timely and accurate diagnosis of candidemia, a severe bloodstream infection caused by Candida spp., remains challenging in clinical practice. Blood culture, the current gold standard technique, suffers from lengthy turnaround times and limited sensitivity. To address these limitations, we propose a novel approach utilizing an Electronic Nose (E-nose) combined with Time Series-based classification techniques to analyze and identify Candida spp. rapidly, using culture species of C. albicans, C.kodamaea ohmeri, C. glabrara, C. haemulonii, C. parapsilosis and C. krusei as control samples. This innovative method not only enhances diagnostic accuracy and reduces decision time for healthcare professionals in selecting appropriate treatments but also offers the potential for expanded usage and cost reduction due to the E-nose's low production costs. Our proof-of-concept experimental results, carried out with culture samples, demonstrate promising outcomes, with the Inception Time classifier achieving an impressive average accuracy of 97.46% during the test phase. This paper presents a groundbreaking advancement in the field, empowering medical practitioners with an efficient and reliable tool for early and precise identification of candidemia, ultimately leading to improved patient outcomes.

Experimental white piedra: a robust approach to ultrastructural analysis, scanning electron microscopy and etiological discoveries.

White piedra is a fungal infection characterized by nodules comprised of Trichosporon species and restricted to the extrafollicular portion of the hair shaft. The diagnosis is based on clinical and mycological characteristics, and must be confirmed with a precise identification of the etiological agent. This research aimed to develop an in vitro infection model of white piedra and analyze its morphological and ultra-structural aspects. In the process, hair infection was induced using eight isolates of the genus Trichosporon maintained in the Culture Collection Micoteca URM. The ITS and IGS1 regions were sequenced for taxonomic confirmation. Scanning Electron Microscope (SEM) was performed at the Strategic Center for Northeast Technologies (CETENE). The scanning electron microscope was equipped with an Energy Dispersion Spectrometer (EDS). The Trichosporon isolates were identified as Trichosporon asahii (6) and Trichosporon montevideense (2) by internal transcript spacer (ITS) region and intergenic spacer 1 region (IGS1) sequencing. All eight strains were used to induce the in vitro hair infection, and nodules formed after the incubation period. Temperature variations and high humidity were not observed to be related to the development of this hair disease. The main chemical constituents detected in the nodules were carbon, nitrogen and oxygen, as well as a low level of sulfur. The absence of calcium, combined with the low level of sulfur, might explain the soft nature of the white piedra nodules. This study demonstrated that several Trichosporon species may be responsible for causing white piedra.