Leishmania species are the causative agent of a tropical disease known as leishmaniasis. Previous studies on the old world species Leishmania major, showed that the amastigotes form which resides inside the macrophage of the vertebrate host, utilize host’s sphingolipids for survival and proliferation. In this study, gene expression of serine palmitoyltransferase (SPT) subunit two (MmLCB2) of the mouse macrophage cell line (RAW264.7), which is the first enzyme in the de novo sphingolipid biosynthesis, was detected in both infected and non-infected macrophages. This was detected under condition where available sphingolipid was reduced, with the new world species Leishmania mexicana. Results of qPCR analysis showed that there was no difference in the expression of MmLCB2 in infected and non-infected macrophages, under normal and serum-reduced media, suggesting that host sphingolipid did not up-regulated during infection. This can be concluded as a difference between the Old and New world Leishmania on the level of host-parasite interaction.
Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD
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Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob
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AA Noaimi, BM Fadheel, Saudi medical journal, 2008 - Cited by 25
One of most the important compounds which have active hydrogen (substrate) is the thiols which used in a wide field in preparation of Mannich bases . A large number of Mannich bases have been prepared as a biologically active compound (pharmaceutical, pesticides, bactericidal, fungicidal and tuberculostatic) and in order to correlate their structure and reactivity with their pharmacological activity such as . It has been reported that the reaction is easily proceeded by using primary and secondary amine beside formaldehyde. But when we tried the reaction of thiols as substrate and formaldehyde and succinimide instead of amine, the reaction did not proceed to give Mannich base but product were methylenene – bis – sulfide . Mann
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