A large number of natural or synthetic dyes have been removed from both national and international lists of permitted food colors because of their mutagenic or carcinogenic activity. Therefore, this study aimed to use the Random Amplified Polymorphic DNA-Based Polymerase Chain Reaction (RAPD-PCR) assay as a feasible method to evaluate the ability of some food colors as genotoxin-induced DNA damage and mutations. Lactiplantibacillus plantarum was used as a bioindicator to determine the genotoxic effects by RAPD-PCR using M13 primer after treatment with some synthetic dyes currently used as food color additives, including Sunset Yellow, Carmoisine, and Tartrazine. Besides qualitative analysis, the bioinformatic GelJ software was used for cluster analysis to compare DNA fingerprints before and after treatment. The bacteria treated with the food colors showed the presence of polymorphism represented by DNA changes in the RAPD patterns, including variation in bands intensity, disappearance of normal bands, and appearance of new bands compared with the non-treated control. The GelJ program confirmed the presence of genetic variations between the bacteria treated with different concentrations of the food dyes and the bacteria without treatment. The RAPD approach can be applied for the detection of DNA damage and mutations induced by genotoxic compounds. Furthermore, L. plantarum and M13 are suitable as in vitro screening tools for detecting of potential genotoxicity of numerous compounds.
<p>Energy and memory limitations are considerable constraints of sensor nodes in wireless sensor networks (WSNs). The limited energy supplied to network nodes causes WSNs to face crucial functional limitations. Therefore, the problem of limited energy resource on sensor nodes can only be addressed by using them efficiently. In this research work, an energy-balancing routing scheme for in-network data aggregation is presented. This scheme is referred to as Energy-aware and load-Balancing Routing scheme for Data Aggregation (hereinafter referred to as EBR-DA). The EBRDA aims to provide an energy efficient multiple-hop routing to the destination on the basis of the quality of the links between the source and destination. In
... Show MoreBackground: Loss of tooth structure may be due to tooth to tooth contact and presence of abrasive components in the work environment. The aim of study was planned to evaluate the occurrence of dental attrition among Cement factory workers. Material and Method: The Sample included all workers chronically exposed to cement dust in the EL-Kubaisa cement factory (95 workers). A comparative group of workers (97) were non-exposed to cement dust was selected. All workers were males in gender with age range (25-55) years. The assessment of tooth wear was based on the criteria of smith and knight, 1984. Results: The maximum tooth wear score for exposed workers was 84.2% while non exposed workers was 38.1%,with statistical differences between two g
... Show MoreIn aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we
... Show MoreWildfire 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
... Show MoreRecently emerging pandemic SARS CoV-2 conquered our world since December 2019. Continuous efforts have been done to find out effective immunization and precise treatment stetratigies A way from therapeutic options that were tried in SARS CoV-2, an increased attention is directed to predict natural products and mainly phytochemicals as collaborative measures for this crisis. In this review, most of the mentioned compounds specially flavonoids (biacalin, hesperidin, quercetin, luteolin,, and phenolic (resveratrol, curcumin, and theaflavin) exert their effect through interfering with the action of one or more of this proteins (spike protein, papain like protease, 3 chymotrypsin like cysteine protease, and RNA dependent RNA
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The current research aims to identify the level of partnership between school and community agencies to improve secondary school outcomes for students with intellectual disabilities and develop strategies that help enhance community partnerships between schools and agencies. The researcher used the qualitative research approach; he utilized the interviews as a tool for data collection. The sample of research included (12) participants: three female school leaders, three male-school leaders, three female-school supervisors, and three male-school supervisors in schools that have programs for students with intellectual disabilities in Riyadh. The results of the study showed that the level of partnership bet
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