Antimicrobial susceptibility of tinea capitis in children from Egypt

Background: Dermatophytic fungi of genera Trichophyton and Microsporum are the most important fungal species causing tinea capitis. Choice of treatment for tinea capitis is determined by the species of fungus. Aim: The aim of the study was to investigate the most prevalent fungal species causing tinea capitis in children from Egypt and the most useful antifungal agent for treatment. Patients and Methods: A total of 100 patients diagnosed clinically with tinea capitis were included in the study. Samples were collected and sent to the microbiology and immunology laboratory for sample processing and fungal identification by routine laboratory techniques. A study of antifungal susceptibility to chosen antifungal medications (fluconazole, ketoconazole, clotrimazole, miconazole, amphotericin, caspofungin, itraconazole, terbinafine, and griseofulvin) was done by minimum inhibitory concentration technique. Results: Our analysis revealed that Microsporum canis is the most commonly isolated strain. Amphotericin was the most effective antifungal agent followed by terbinafine. The most sensitive strain to fluconazole and griseofulvin is Microsporum gypseum, while Microsporum audouinii was mostly responsive to terbinafine. Conclusion: Identification and evaluation of the antifungal susceptibility of the pathogenic species in a certain geographic region is important to achieve a good clinical response

The odd lindley power rayleigh distribution: properties, classical and bayesian estimation with applications

In this paper, we propose and investigate the odd Lindley Power Rayleigh (OLPR) distribution, which is derived by combining the odd Lindley-G family and power Rayleigh distribution. The proposed distribution, which is comparable to the Lindley distribution, Rayleigh distribution and other Rayleigh generalizations have the desirable attribute of allowing greater flexibility than some of its well known extensions. A comprehensive account of the mathematical and statistical properties along with the estimation of parameters using classical and Bayesian estimation methodologies is presented. An extensive simulation study is carried out to assess the behaviour of estimators based on their biases and mean square errors. Finally, we consider two practical real-life applications, we observe that the proposed model outperforms other competing models using the Akaike information criterion (AIC), the Bayesian information criterion (BIC), Anderson-Darling (A*), Cramer-von Mises (W*) and other goodness-of-fit measures