Objective: To conduct a standardized method for cavity preparation on the palatal surface of rat maxillary molars and to introduce a standardized method for tooth correct alignment within the specimen during the wax embedding procedure to better detect cavity position within the examined slides. Materials and methods: Six male Wistar rats, aged 4-6 weeks, were used. The maxillary molars of three animals were sectioned in the frontal plane to identify the thickness of hard tissue on the palatal surface of the first molar which was (250-300µm). The end-cutting bur (with a cutting head diameter of 0.2mm) was suitable for preparing a dentinal cavity (70-80µm) depth. Cavity preparation was then performed using the same bur on the tooth

Objective: To conduct a standardized method for cavity preparation on the palatal surface of rat maxillary molars and to introduce a standardized method for tooth correct alignment within the specimen during the wax embedding procedure to better detect cavity position within the examined slides. Materials and methods: Six male Wistar rats, aged 4-6 weeks, were used. The maxillary molars of three animals were sectioned in the frontal plane to identify the thickness of hard tissue on the palatal surface of the first molar which was (250-300µm). The end-cutting bur (with a cutting head diameter of 0.2mm) was suitable for preparing a dentinal cavity (70-80µm) depth. Cavity preparation was then performed using the same bur on the tooth surf

Non-Small Cell Lung Cancer (NSCLC) accounts for about 84% of all lung cancer types diagnosed so far. Every year, regardless of gender, the NSCLC targets many communities worldwide. 5-Fluorouracil (5-FU) is a uracil-analog anticancer compound. This drug tends to annihilate multiple tumour cells. But 5-FU's most significant obstacle is that it gets very easily metabolized in the blood, which eventually leads to lower anticancer activity. Therfore a perfect drug delivery system is needed to overcome all the associated challenges.

In this experiment, an attempt was made to prepare 5-FU loaded poly lactic-co-glycolic acid  nanoparticles using solvent evaporation method and subsequently observed the effect of molecular weight of poly l

The bourgeoisie groups derived great advantages from the system upon which the Fatimids built up their Regime out the land-tax and other taxes against a fixed sum . The surpulus revenue was the prophet of the farmers . A striking feature of the Fatimid was freedom of enterprise .All sectors of economic life were free-crafts , industry and trade . The government interfered in the trade in victuals only so far to in order to guarantee the supply of wheat to the big towns
The Egyptian Bourgeoisie enjoyed also the great prosperity which was produced among other reasons by the inflationary system of Fatimid economy .
The maintenance of gold dinar being almost pure and of full weight was only possible because Egypt steadily received cons

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Background: techniques of image analysis have been used extensively to minimize interobserver variation of immunohistochemical scoring, yet; image acquisition procedures are often demanding, expensive and laborious. This study aims to assess the validity of image analysis to predict human observer’s score with a simplified image acquisition technique. Materials and methods: formalin fixed- paraffin embedded tissue sections for ameloblastomas and basal cell carcinomas were immunohistochemically stained with monoclonal antibodies to MMP-2 and MMP-9. The extent of antibody positivity was quantified using Imagej® based application on low power photomicrographs obtained with a conventional camera. Results of the software were employed