Polycystic ovarian syndrome (PCOS) is a well-known endocrinopathy and one of the most frequent endocrine-reproductive-metabolic syndromes in women, which can result in reduced fertility. While the actual cause is unknown, PCOS is regarded as a complicated genetic characteristic with a great degree of variability. Moreover, hormones and immune cells, including both innate and acquired immune cells, are thought to interact in PCOS. Chronic low-grade inflammation raises the risk of autoimmune disease. The study's purpose is to investigate the chemokine monocyte chemoattractant protein-1 (MCP-1) and fertility hormones in samples of women patients with polycystic ovary syndrome (PCOS) in the City of Medicine. Sixty PCOS women comprise 30 healthy control women; their average age was 20–40 years, and their weight ranged from 60 to 100 kg. The results showed an increase in the level of MCP1 in PCOS patients, but this increase was not significant (P<0.05), which was not influenced by BMI or fertility hormones. As well as elevated fertility hormones, this study, when compared to controls as well as patients with PCOS, showed a significant increase in the level of testosterone (14.63 ±2.30 nmol/L) while in control women (0.627 ±0.04), LH hormone in patients and control group (6.54 ±0.51 mIU/mL), and 2.93 ±0.18, respectively. Prolactin hormone was increased in PCOS patients (16.27 ±1.25 ng/mL) when compared to the control group \ (12.85 ±0.62). There was no significant difference in FSH hormone in women with PCOS (5.27 ±0.28 mIU/mL) compared with the control group (5.59 ±0.18).
The research aims to build a list of digital citizenship axes and standards and indicators emanating from them, which should be included in the content of the computer textbook scheduled for second grade intermediate students in Iraq, and the analysis of the above mentioned book according to the same list using the descriptive analytical method ((method of content analysis)). The research community and its sample consisted of the content of the computer textbook scheduled for the second year intermediate students for the academic year 2018-2019, and the research tool was built in its initial form after reference to a set of specialized literature and previous studies that dealt with topics related to digital citizenship, and the authenticit
... Show MoreBackground: Radiopacity is one of the prerequisites for dental materials, especially for composite restorations. It's essential for easy detection of secondary dental caries as well as observation of the radiographic interface between the materials and tooth structure. The aim of this study to assess the difference in radiopacity of different resin composites using a digital x-ray system. Materials and methods: Ten specimens (6mm diameter and 1mm thickness) of three types of composite resins (Evetric, Estelite Sigma Quick,and G-aenial) were fabricated using Teflon mold. The radiopacity was assessed using dental radiography equipment in combination with a phosphor plate digital system and a grey scale value aluminum step wedge with thickness
... Show MoreIn this work, the switching nonlinear dynamics of a Fabry-Perot etalon are studied. The method used to complete the solution of the differential equations for the nonlinear medium. The Debye relaxation equations solved numerically to predict the behavior of the cavity for modulated input power. The response of the cavity filled with materials of different response time is depicted. For a material with a response time equal to = 50 ns, the cavity switches after about (100 ns). Notice that there is always a finite time delay before the cavity switches. The switch up time is much longer than the cavity build-up time of the corresponding linear cavity which was found to be of the order of a few round-trip ti
... Show MoreBackground: Atrioventricular nodal reentrant tachycardia (AVNRT) is the commonest regular supraventricular tachyarrhythmia. Ablation in the area of slow pathway (SP) has been successfully implemented in every day clinical electrophysiological practice for more than 20 years. Although the procedure is generally regarded as effective and safe, data on long-term effects and predictors of success or failure are incomplete.
<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
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