Leishmaniosis is a tropical neglected parasitic disease that is endemic in many countries, including Middle East, with no existing effective vaccines. The bite of female sand-fly transmits the causative agent, Leishmania spp., to humans. High toxicity, resistance and treatment failure of the available chemotherapy against visceral leishmaniosis demands the investigation of new anti-leishmanial compounds. Lupeol is a form of triterpene isolated from several medicinal plants and possesses an antimicrobial property. In this study, cytotoxic effect of lupeol was screened against the mammalian amastigotes form and insect promastigote form of Leishmania donovani, following three cycles of incubation at different concentrations by MTT assay. Results revealed the in vitro anti-leishmanial effect of lupeol on both forms of the parasite where significant decline in promastigotes and amastigotes growth was observed. This was conducted along three times of follow up (24, 48, 72) hours, in comparison to the classical sodium stibogluconate treatment. Cell viability was calculated and the minimum IC50 was detected after 48 hours for amastigotes and 24 hours for promastigotes, 12.125 µM, 102.78 µM, respectively. Given the severity of visceral leishmaniosis and the toxicity of conventional chemotherapies, the anti-leishmanial activity of lupeol suggested a promising compound for additional clinical trials
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The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T
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Background: Male infertility is a global concern and it tends to increase due to miscellaneous factors, such as environmental toxins and genetic and lifestyle choices. The aryl hydrocarbon receptor (AHR) has recently attracted attention due to its involvement in male infertility mechanisms and impact on sperm production and function. AHR, a versatile receptor expressed in various tissues, including the testes, regulates the genes involved in spermatogenesis. AHR activation is associated with cell cycle regulation and chromatin condensation during spermatogenesis. Objectives: This study aimed to investigate the influence of AHR activation on blood-testis barrier (BTB) integrity, focusing on the role of tight junction protein-1 (TJP1)
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In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.
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This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio
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A remarkable correlation between chaotic systems and cryptography has been established with sensitivity to initial states, unpredictability, and complex behaviors. In one development, stages of a chaotic stream cipher are applied to a discrete chaotic dynamic system for the generation of pseudorandom bits. Some of these generators are based on 1D chaotic map and others on 2D ones. In the current study, a pseudorandom bit generator (PRBG) based on a new 2D chaotic logistic map is proposed that runs side-by-side and commences from random independent initial states. The structure of the proposed model consists of the three components of a mouse input device, the proposed 2D chaotic system, and an initial permutation (IP) table. Statist
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