Scrophularia. striata from Scrophulariacea family has been used in Iranian folk medicine for the treatment of infectious diseases. In this study we evaluated the synergistic effect of S. striata hydroalcoholic extract (SSE) and commercially available antibiotics against P. aeroginosa and Methicillin- resistant Staphylococcus aureus (MRSA). The resazurin-based microdilution method was used to determine the minimum inhibitory concentration (MIC) values of plan extract and standard antibiotics. The interaction between standard antibiotics and SSE was evaluated by using checkerboard method. The results of this study revealed that SSE enhance the antibacterial activity of antibiotics. The combination of SSE and Vancomycin had synergistic to additive effects against MRSA. SSE in combination with Gentamicin had synergistic to additive effects against P. aeruginosa. The interaction between Ceftazidime and SSE was additive against P. aeruginosa. The best result was the synergistic effect between SSE and Piperacillin-Tazobactam against P. aeruginosa. In conclusion the results of this research indicated that S. striata has the potential to enhance the antibacterial activity of antibiotics and could be a source to the designing new compounds with synergistic effect in combination with standard antibiotics.
1,3,4-oxadizole and pyrazole derivatives are very important scaffolds for medicinal chemistry. A literature survey revealed that they possess a wide spectrum of biological activities including anti-inflammatory and antitumor effects.
To describe the synthesis and evaluation of two classes of new niflumic acid (NF) derivatives, the 1,3,4-oxadizole derivatives (compounds 3 and (4A-E) and pyrazole derivatives (compounds 5 and 6), as EGFR tyrosine kinase inhibitors in silico and in vitro.
The designed compounds were synthesized using convent
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
An improved Metal Solar Wall (MSW) with integrated thermal energy storage is presented in this research. The proposed MSW makes use of two, combined, enhanced heat transfer methods. One of the methods is characterized by filling the tested ducts with a commercially available copper Wired Inserts (WI), while the other one uses dimpled or sinusoidal shaped duct walls instead of plane walls. Ducts having square or semi-circular cross sectional areas are tested in this work.
A developed numerical model for simulating the transported thermal energy in MSW is solved by finite difference method. The model is described by system of three governing energy equations. An experimental test rig has been built and six new duct configurations have b
Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall
... Show MoreA Ligand (ECA) methyl 2-((1-cyano-2-ethoxy-2-oxoethyl)diazenyl)benzoate with metals of (Co2+, Ni2+, Cu2+) were prepared and characterization using H-NMR, atomic absorption spectroscopy, ultra violet (UV) visible, magnetic moments measurements, bioactivity, and Molar conductivity measurements in soluble ethanol. Complexes have been prepared using a general formula which was suggested as [M (ECA)2] Cl2, where M = (Cobalt(II), Nickel(II) and Copper(II), the geometry shape of the complexes is octahedral.