Background: Green Tea is made from the leaf of the plant “Camellia sinensisâ€. Green tea is reported to contain thousands of bioactive ingredients including catechins which have shown great promise for having antimicrobial effects. Periodontal diseases represent one of the most prevalent diseases around the world and the main etiologic factor behind it, is plaque accumulation, in addition certain kinds of bacteria have been detected frequently in subjects suffering from periodontitis, Several studies suggested that the outcome of periodontal treatment is better if particular pathogens including Aggregatibacteractinomycetemcomitans can no longer be detected after therapy. Materials and Methods: plaque samples were collected from 20 patients suffering from chronic periodontitis with probing pocket depth of at least 6 mm, Aggregatibacteractinomycetemcomitans (A.A) was isolated and diagnosed according to morphological characteristics and biochemical tests. Green tea leaves were extracted by using water and alcohol. The first experiment involved testing the sensitivity of A.A to different concentrations of the extracts using agar well diffusion method,the second experiment involved determination of the minimum inhibitory concentration and then determination of the minimum bactericidal concentration of the extract against the bacteria, laboratory analysis of green tea extracts using high pressure liquid chromatography (HPLC) was performed. Results: Both green tea extracts were effective in inhibition of Aggregatibacteractinomycetemcomitans using agar well diffusion method, 90% and 100% concentrations of alcoholic extract showed larger inhibition zones than chlorhexidinegluconate 0.2% with statistically significant difference, CHX showed higher inhibition zones than all aqueous extract concentrations.The MIC (minimum inhibitory concentration) of alcoholic green tea extract that inhibit Aggregatibacteractinomycetemcomitans growth was 60%, The MIC of aqueous green tea extract that inhibits Aggregatibacteractinomycetemcomitans growth was 70%.The MBC (minimum bactericidal concentration) of alcoholic green tea extract that killsAggregatibacteractinomycetemcomitans was 80%, the MBC of aqueous green tea extract that kills Aggregatibacteractinomycetemcomitans growth was 90%. HPLC analysis of aqueous and alcoholic green tea extracts revealed that alcoholic extract contained higher concentration of EGCG while aqueous extract had higher content of catechin and epicatechin. Conclusion: Green tea extracts were effective against Aggregatibacteractinomycetemcomitans, alcoholic green tea extract showed inhibition ability more than the aqueous green tea extract and more than CHX and it showed bactericidal activity at 80%,90% and 100% concentrations.
This research focuses on the synthesis of carbon nanotube (CNT) and Poly(3-hexylthiophene) (P3HT) (pristine polymer) with Ag doped (CNT/ P3HT@Ag) nanocomposite thin films to be utilised in various practical applications. First, four samples of CNT solution and different ratios of the polymer (P3HT) [0.1, 0.3, 0.5, and 0.7 wt.%] are prepared to form thin layer of P3HT@CNT nanocomposites by dip-coating method of Ag. To investigate the absorption and conductivity properties for use in various practical applications, structure, morphology, optical, and photoluminescence properties of CNT/P3HT @Ag nanocomposite are systematically evaluated in this study. In this regard, the UV/Vis/NIR spectrophotometer in the wavelength range of 350 to 7
... Show MoreThe main objective of this paper is to study the behavior of Non-Prismatic Reinforced Concrete (NPRC) beams with and without rectangular openings either when exposed to fire or not. The experimental program involves casting and testing 9 NPRC beams divided into 3 main groups. These groups were categorized according to heating temperature (ambient temperature, 400°C, and 700°C), with each group containing 3 NPRC beams (solid beams and beams with 6 and 8 trapezoidal openings). For beams with similar geometry, increasing the burning temperature results in their deterioration as reflected in their increasing mid-span deflection throughout the fire exposure period and their residual deflection after cooling. Meanwhile, the existing ope
... Show MoreInfrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was
... Show MoreThis paper deals with calculate stresses in Knee-Ankle-Foot-Orthosis as a result of the effect vibration during gait cycle for patient wearing KAFO .Experimental part included measurement interface pressure between KAFO and leg due to action muscles and body weigh on Orthosis. also measurement acceleration result from motion of defected leg by accelerometer .Results of Experimental part used input in theoretical part so as to calculate stresses result from applying pressure and acceleration on KAFO by engineering analysis program ANSYS 14.Resultes show stresses values in upper KAFO greater than lower KAFO that is back to muscles more effective in thigh part lead to recoding pressure higher than pressure in shank part.
With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi
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