Background: Antimicrobial agents have been considered as having potential for the prevention of dental caries. This study aimed to test the effect of different concentrations of cardamom and black tea extracts on the sensitivity and growth of salivary mutans streptococci in comparison to chlorhexidine gluconate (0.2%) in vitro. Materials and methods: In this study. Mutans streptococci were isolated from saliva of 34 healthy people (aged between 22-40yrs). The bacteria was isolated, purifiedand diagnosed according to morphologicalcharacteristic and biochemical tests. Aqueous extracts of cardamom and black tea were prepared. Different concentrations of extracts were prepared and estimated in gm/ 100ml deionized water. The agar diffusion technique was used to determine the antibacterial activity of cardamom and tea extracts in which the inhibition of bacteria growth by different concentrations of extracts was measured by diameter of inhibition zone in millimeter. The viable count was measured in different concentrations for both types of extracts on comparison to chlorhexidine 0.2%. Results: The result showed that the mutans streptococci is more sensitive to tea extract than cardamom one, where the mean value of diameter of inhibition zone was higher by tea extract than cardamom type in all concentrations and chlorohexidine0.2% is more effective than both extracts. For viable count no statistical significant difference between two extract types at concentration of 40% but there are a high statistical significant difference for other concentrations, where the chlorhexidine is moreeffective than tea type and the last one is more effective than cardamom type with p value?0.05 . Conclusions: Cardamom and black tea have antibacterial effect against Mutans streptococci; the accused factor of dental caries.
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Solubility problem of many of effective pharmaceutical molecules are still one of the major obstacle in theformulation of such molecules. Candesartan cilexetil (CC) is angiotensin II receptor antagonist with very low water solubility and this result in low and variable bioavailability. Self- emulsifying drug delivery system (SEDDS) showed promising result in overcoming solubility problem of many drug molecules. CC was prepared as SEDDS by using novel combination of two surfactants (tween 80 and cremophore EL) and tetraglycol as cosurfactant, in addition to the use of triacetin as oil. Different tests were performed in order to confirm the stability of the final product which includes thermodynamic study, determination of self-emulsificat
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A new spectrophotometric method has been developed for the assay of olanzapine (OLN.) in pure and dosage forms. The method is based on the diazocoupling of (OLN.) with diazotized p-nitroaniline in alkaline medium to form a stable brown colored water-soluble azo dye with a maximum absorption at 405 nm. The variables that affect the completion of reaction have been carefully optimized. Beer’s law is obeyed over the concentration range of (0.5-45.0 μg.mL-1) with a molar absorptivity of 1.5777×104 L.mol-1.cm-1. The limit of detection was 0.3148 μg.mL-1 and Sandell’s sensitivity value was 0.0198 μg.cm-2. The propose
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A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration
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This case series aims to evaluate patients affected with post COVID‐19 mucormycosis from clinical presentation to surgical and pharmacological treatment to improve the disease prognosis.
This case series was conducted at a specialized surgery hospital in Baghdad Medical City for over 10 months. Fifteen cases who had mild to severe COVID‐19 infections followed by symptoms similar to aggressive periodontitis, such as mobility and bone resorption around the multiple maxillary teeth, were included in this case series.
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