Molecular Detection of Dermatophytes and Nondermatophytes in Onychomycosis in Antalya, Turkey.

BACKGROUND: Onychomycosis is a chronic nail infection, and dermatophytes, yeasts, and nondermatophytic molds may be the causative agents. This study aimed to determine the etiological agents of onychomycosis by using conventional and molecular methods. METHODS: Between June 2020 and July 2021, 37 patients with a presumptive diagnosis of onychomycosis and mycological evidence (culture and/or EUROArray Dermatomycosis assay) were included in the study. Organisms detected in cultured nail specimens were identified by combined phenotypic characteristics and by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). An EUROarray Dermatomycosis assay was used for molecular detection of fungal pathogens. RESULTS: The EUROArray Dermatomycosis assay was positive for a single fungal target in 23 samples, and 14 samples were positive by culture. The most common pathogen was Trichophyton rubrum in both methods. Coinfection was detected in 14 samples by using molecular methods, and Trichophyton rubrum and Fusarium solani (9 samples) were the most common pathogens detected together. Trichophyton spp., nondermatophyte molds, and Candida spp. were detected in 33 (89.2%), 16 (43.2%), and 6 (16.2%) samples, respectively, when the two methods were evaluated together. CONCLUSIONS: Our results revealed that fungal culture allows the diagnosis of onychomycosis, but it is not as sensitive as the EUROArray Dermatomycosis test, especially in patients receiving antifungal therapy.

An observation tool for instructor and student behaviors to measure in-class learner engagement: a validation study.

BACKGROUND: Efforts are made to enhance in-class learner engagement because it stimulates and enhances learning. However, it is not easy to quantify learner engagement. This study aimed to develop and validate an observation tool for instructor and student behaviors to determine and compare in-class learner engagement levels in four different class types delivered by the same instructor. METHODS: Observer pairs observed instructor and student behaviors during lectures in large class (LLC, n=2) with third-year medical students, lectures in small class (LSC, n=6) and case-based teaching sessions (CBT, n=4) with fifth-year students, and problem-based learning (PBL) sessions (~7 hours) with second-year students. The observation tool was a revised form of STROBE, an instrument for recording behaviors of an instructor and four randomly selected students as snapshots for 5-min cycles. Instructor and student behaviors were scored 1-5 on this tool named 'in-class engagement measure (IEM)'. The IEM scores were parallel to the degree of behavior's contribution to active student engagement, so higher scores were associated with more in-class learner engagement. Additionally, the number of questions asked by the instructor and students were recorded. A total of 203 5-min observations were performed (LLC 20, LSC 85, CBT 50, and PBL 48). RESULTS: Interobserver agreement on instructor and student behaviors was 93.7% (κ=0.87) and 80.6% (κ=0.71), respectively. Higher median IEM scores were found in student-centered and problem-oriented methods such as CBT and PBL. A moderate correlation was found between instructor and student behaviors (r=0.689). CONCLUSIONS: This study provides some evidence for validity of the IEM scores as a measure of student engagement in different class types.