Background: Eucalyptus extracts and derivatives are natural substances with potent antimicrobial properties. This study investigated the in- vitro effects of non-nutritive sweeteners on the antifungal activity of alcoholic and aqueous Eucalyptus extracts against Candida albicans, a common oral pathogen. Materials and Method: Ten isolates of Candida albicans were isolated from dental students’ salivary samples. The alcoholic and aqueous extracts were prepared from fresh Eucalyptus leaves using maceration. The sensitivity of Candida albicans isolates to various concentrations of Eucalyptus extracts ranging from 50 to 250 (mg/mL) was evaluated via agar well diffusion method, while the agar streaking method was used to assess the minimum fungicidal concentration (MFC). In addition, the effect of non-nutritive sweeteners on the MFC of the extracts was investigated. Results: The Eucalyptus extract-sensitive Candida albicans isolates showed an increase in inhibitory zone width with increasing extract concentration. Regarding their antifungal effectiveness, clear disparities were observed among extract concentrations. Against Candida albicans, the MFC for Eucalyptus alcoholic extract was 75 mg/mL, but the MFC for Eucalyptus aqueous extract was 200 mg/mL. Notably, 15% stevia and 5% sucralose did not affect the antifungal effects of the Eucalyptus alcoholic extract. The antifungal effectiveness of the aqueous Eucalyptus extract against Candida albicans was unaffected by stevia and sucralose concentrations of up to 1%. Conclusion: Significant antimicrobial action against Candida albicans is shown in Eucalyptus extracts. Results indicated that stevia and sucralose at specific quantities could be utilized as sweeteners for Eucalyptus extracts in an efficient manner without impairing the extracts’ antifungal activity.
The study aims to display the scientific benefit offered by modern electronic programs for various scientific research methods, while determining the positive scientific role played by these programs in modernizing the methodologies and logic of scientific thinking, especially with the rapid development of the sciences and their curricula.
These programs link accurately with scientific results. The importance of the study is to provide practical mechanisms to highlight the scientific projection of the electronic programs in various steps of scientific research.
A case study was used for Tropes version 8.4, which analyzes written, audio and visual semantic texts and presents a set of statistical results that facilitate the difficult
There are main methods of scientific research, and that the researcher's choice of the appropriate methodology for scientific research is one of the most important rules on which the researcher must rely in order to prepare scientific research properly. There is no doubt that the methodology of scientific research is of great importance that they all agree on the preparation of accurate scientific research. Scientific research is an organized research that does not come by chance, but comes as a result of the activity of the mind. It is theoretical because it relies on theories for the purposes of perceiving the proportions and relationships between things, and everyone is subjected to testing and experiment.
Receipt date:06/23/2020 accepted date:7/15/2020 Publication date:12/31/2021
This work is licensed under a Creative Commons Attribution 4.0 International License
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Document source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing
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