Background: Due to the variations in tooth anatomy and size among different populations, this study aimed to compare the mesiodistal width of primary second molars in Iraqi children with the mesiodistal width of stainless-steel crowns from different companies. Materials and Methods: This cross-sectional study was conducted on 220 intact maxillary and mandibular primary second molars selected from boys and girls’ Iraqi children aged 8-9 years collected from different primary schools in Baghdad city. The mesiodistal dimensions of the selected teeth and the available maxillary and mandibular stainless-steel crowns from three different companies were measured by using a 3-D scanner, and then the whole measurements were calculated usin

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Different frequency distributions models were fitted to the monthly data of raw water Turbidity at water treatment plants (WTPs) along Tigris River in Baghdad. Eight water treatment plants in Baghdad were selected, with raw water turbidity data for the period (2008-2014). The frequency distribution models used in this study are the Normal, Log-normal, Weibull, Exponential and two parameters Gamma type. The Kolmogorov-Smirnov test was used to evaluate the goodness of fit. The data for years (2008-2011) were used for building the models. The best fitted distributions were Log-Normal (LN) for Al-Karkh, Al-Wathbah, Al-Qadisiya, Al- Dawrah and, Al-Rashid WTPs. Gamma distribution fitted well for East Tigris and Al-Karamah WTPs. As for Al-

Different frequency distributions models were fitted to the monthly data of raw water Turbidity at water treatment plants (WTPs) along Tigris River in Baghdad. Eight water treatment plants in Baghdad were selected, with raw water turbidity data for the period (2008-2014). The frequency distribution models used in this study are the Normal, Log-normal, Weibull, Exponential and two parameters Gamma type. The Kolmogorov-Smirnov test was used to evaluate the goodness of fit.  The data for years (2008-2011) were used for building the models. The best fitted distributions were Log-Normal (LN) for Al-Karkh, Al-Wathbah, Al-Qadisiya, Al-Dawrah and, Al-Rashid WTPs. Gamma distribution fitted well for East Tigris and Al-Karamah

both strongly associated with vascular and metabolic complications. Endothelin-1 is a potent vasoconstrictor that plays a key role in vascular tone regulation and endothelial function. Objective: To evaluate serum Endothelin-1 levels, lipid profile parameters (total cholesterol, LDL-C, VLDL-C, HDL-C, triglycerides), and HbA1c in patients with type 2 diabetes and essential hypertension compared with healthy controls, in order to assess their association with vascular injury and metabolic risk. Methods: A case-control study was conducted in the Department of Biochemistry, College of Medicine, University of Baghdad. Between November 2024 and February 2025, a sample of patients were recruited from Baghdad Teaching Hospital and Ibn Al-Bi

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att