Introduction and Aim: Cancers are a complex group of genetic illnesses that develop through multistep, mutagenic processes which can invade or spread throughout the body. Recent advances in cancer treatment involve oncolytic viruses to infect and destroy cancer cells. The Newcastle disease virus (NDV), an oncolytic virus has shown to have anti-cancer effects either directly by lysing cancer cells or indirectly by activating the immune system. The green fluorescent protein (GFP) has been widely used in studying the anti-tumor activity of oncolytic viruses. This study aimed to study the anticancer effect of a recombinant rNDV-GFP clone on NCI-H727 lung carcinoma cell line in vitro. Materials and Methods: The GFP gene was inserted to a NDV strain to create a recombinant NDV (rNDV- GFP) using reverse genetics technology. The MTT assay was used in evaluating the oncolytic effect of rNDV- GFP on the lung carcinoma NCI-H727 cells. Light and fluorescent microscopy was used to study the cytopathic effects of rNDV-GFP. Results: MTT assay showed that rNDV-GPF inhibited the NCI-H727 tumor cell death in a time-dependent manner. A significant inhibitory effect (78.3%) for rNDV-GPF on cancer cells was observed at 96h in comparison to rNDV (22.7%) and the cytotoxicity rate was directly proportional to the MOI used. Microscopic studies showed rNDV-GPF to induce cytopathic effect post 24 h of infection. Conclusion: The GFP-expressing recombinant NDV strains exhibited encouraging results in terms of tumor growth inhibition. Our research set the groundwork for employing recombinant NDV as an anticancer viral vector.
Some maps of the chaotic firefly algorithm were selected to select variables for data on blood diseases and blood vessels obtained from Nasiriyah General Hospital where the data were tested and tracking the distribution of Gamma and it was concluded that a Chebyshevmap method is more efficient than a Sinusoidal map method through mean square error criterion.
This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback
... Show MoreCopper with different concentrations doped with zinc oxide nanoparticles were prepared from a mixture of zinc acetate and copper acetate with sodium hydroxide in aqueous solution. The structure of the prepared samples was done by X-ray diffraction, atomic force microscopy (AFM) and UV-VIS absorption spectrophotometer. Debye-Scherer formula was used to calculate the size of the prepared samples. The band gap of the nanoparticle ZnO was determined by using UV-VIS optical spectroscopy.
The study aimed to identify the impact of the use of systemic approach in the collection of geographical material and cognitive motivation when fifth grade students of literary, experimental design researcher adopted a partial seizures, and telemetric to two unequal one experimental and the other officer.
The sample consisted of fifth grade literary students from secondary (inherent) for Boys in Baghdad (the Republic of Iraq. (By Mjootain, and the number of students of each group (30 students). And has rewarded the two groups, in the variables (chronological age, average scores half-year, degree IQ),
Promising researcher himself requirements of research to determine the scientific material and teaching plans and the formulation of
In the current research the absorption and fluorescence spectrum
of Coumarin (334) and Rhodamine (590) in ethanol solvent at
different concentration (10-3, 10-4, 10-5) M had been studied. The
absorption intensity of these dyes increases as the Concentration
increase in addition to that the spectrum was shifted towards the
longer wavelength (red shift). The energy transfer process has been
investigated after achievement this condition. The fluorescence peak
intensity of donor molecule was decrease and its bandwidth will
increases on the contrary of the acceptor molecule its intensity
increase gradually and its bandwidth decreases as the acceptor
concentration increase.
Abstract: In the current research the absorption and fluorescence spectrum of Coumarin (334) and Rhodamine (590) in ethanol solvent at different concentration (10-3, 10-4, 10-5) M had been studied. The absorption intensity of these dyes increases as the Concentration increase in addition to that the spectrum was shifted towards the longer wavelength (red shift). The energy transfer process has been investigated after achievement this condition. The fluorescence peak intensity of donor molecule was decrease and its bandwidth will increases on the contrary of the acceptor molecule its intensity increase gradually and its bandwidth decreases as the acceptor concentration increase.
In this paper, The transfer function model in the time series was estimated using different methods, including parametric Represented by the method of the Conditional Likelihood Function, as well as the use of abilities nonparametric are in two methods local linear regression and cubic smoothing spline method, This research aims to compare those capabilities with the nonlinear transfer function model by using the style of simulation and the study of two models as output variable and one model as input variable in addition t
... Show MoreThe present study addresses the behavior of gases in cultivation media as an essential factor to develop the relationship between the microorganisms that are present in the same environment. This relationship was explained via mass transfer of those gases to be a reasonable driving force in changing biological trends. Stripping and dissolution of oxygen and carbon dioxide in water and dairy wastewater were investigated in this study. Bubble column bioreactor under thermal control system was constructed and used for these processes. The experimental results showed that the removal of gases from the culture media requires more time than the dissolution. For example, the volumetric mass transfer coefficient for the removal
... Show MoreSelf-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin
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