Introduction: Candida spp. has become increasingly resistant to antifungal drugs, with elevated MIC levels causing a negative medical impact and increasing the number of patients at risk of candidiasis. According to the CDC, about 7% of Candida blood samples show reduced susceptibility to fluconazole. Monitoring the antifungal resistance profile of Candida spp. is vital, as non-Albicans species may limit treatment options. Objective: Evaluate the antifungal effectiveness against clinical Candida spp. isolates of six antifungals: amphotericin B, fluconazole, voriconazole, itraconazole, caspofungin, and 5-fluorocytosine. Methods: 100 samples were collected from various clinical samples at the National Centre of Teaching Laboratories in Baghdad, Iraq, from May to December 2023. The effectiveness of six antifungals (fluconazole (FLC), itraconazole (ITR), voriconazole (VRC), amphotericin B (AMB), caspofungin (CAS), and 5-fluorocytosine (5-FC)) was tested using the MA120 Automated ID and AST System (Render) according to CLSI standards. Results: Out of 100 isolates, nine Candida species were identified: C. albicans (54%), C. glabrata (20%), C. dubliniensis (10%), C. tropicalis (6%), C. krusei (5%), C. parapsilosis (2%), and C. rugosa, C. lusitaniae, and C. kyfer (each 1%). The non-susceptible rates to the six antifungals were: 5-FC (42%), FLC (21% intermediate, 9% resistant), AMB (11%), ITR (8%), VRC (6%), CAS (4% intermediate, 1% resistant). Conclusion: We observed increased resistance rates to 5-FC, FLC, ITR, AMB, and VRC, but not to caspofungin. C. albicans showed a high 5-FC non-WT phenotype (72%) with elevated MIC values, while C. glabrata had a 7% non-WT rate against AMB. C. tropicalis and C. parapsilosis revealed limited susceptibility to azoles
In this article four samples of HgBa2Ca2Cu2.4Ag0.6O8+δ were prepared and irradiated with different doses of gamma radiation 6, 8 and 10 Mrad. The effects of gamma irradiation on structure of HgBa2Ca2Cu2.4Ag0.6O8+δ samples were characterized using X-ray diffraction. It was concluded that there effect on structure by gamma irradiation. Scherrer, crystallization, and Williamson equations were applied based on the X-ray diffraction diagram and for all gamma doses, to calculate crystal size, strain, and degree of crystallinity. I
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The diseases presence in various species of fruits are the crucial parameter of economic composition and degradation of the cultivation industry around the world. The proposed pear fruit disease identification neural network (PFDINN) frame-work to identify three types of pear diseases was presented in this work. The major phases of the presented frame-work were as the following: (1) the infected area in the pear fruit was detected by using the algorithm of K-means clustering. (2) hybrid statistical features were computed over the segmented pear image and combined to form one descriptor. (3) Feed forward neural network (FFNN), which depends on three learning algorithms of back propagation (BP) training, namely Sca
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