Alopecia areata is considered as a major health problem, its importance is attributed to its
recent increased incidence in our population. Till now, there is no exact cause for alopecia areata
although researchers thought it's an autoimmune disease.
This clinical study was designed to evaluate the role of trace elements (zinc and copper) in patients
with alopecia areata. Twenty patients were diagnosed as having alopecia areata with an age range
(10-40 years) were involved in this study. Normal subjects of the same age group were also
evaluated as control. The level of serum Zn and Cu were measured by flame atomic absorption
spectrophotometry in both control and patient group. And the ratio of Zn/Cu was also estimated.
The results of patients group revealed that serum Zn level was significantly lower than those of
control (p<0.001), while serum Cu was significantly higher than that of control group (p=0.002).
Furthermore, Zn/Cu ratio of patients group was significantly lower than that of control subjects
(p<0.001). These results suggest the possible role of Zn and Cu level in alopecia areata. In addition
to that the utility of measuring Zn/ Cu ratios for the diagnosis of the disease over that of
determining the serum level of Zn or Cu alone since this ratio clearly reflects the severity of the
progress.
Objective: To find out the prevalence of anxiety and depression among Iraqi repatriated prisoners of Iran-Iraq war
(IRPOWs), and the relationship with some variables.
Methodology: A descriptive study was carried out from Oct. 18th, 2009 through Jan. 10th, 2010. A Snowball
sampling as a non-probability sampling technique was used to recruit 92 repatriates who had visited Ministry of
Human Rights. An instrument was constructed for this purpose. The constructed instrument consisted of six
demographic characteristics, and fourteen items to measure the level of anxiety and depression in prisoners of
war (POWs). Data were collected with using the constructed instrument and the process of the interview as means
for data col
According to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN). A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through
... Show MoreA group of amino derivatives [4-aminobenzenesulfonamide,4-amino-N¹ methylbenzenesulfonamide, or N¹-(4-aminophenylsulfonyl)acetamide] bound to carboxyl group of mefenamic acid a well known nonsteroidal anti-inflammatory drugs (NSAIDs) were designed and synthesized for evaluation as a potential anti-inflammatory agent. In vivo acute anti-inflammatory activity of the final compounds (9, 10 and 11) was evaluated in rat using egg-white induced edema model of inflammation in a dose equivalent to (7.5mg/Kg) of mefenamic acid. All tested compounds produced a significant reduction in paw edema with respect to the effect of propylene glycol 50% v/v (control group). Moreover, the 4-amino-N-methylbenzenesulfonamide derivative (c
... Show MoreThe drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the
Contracting cancer typically induces a state of terror among the individuals who are affected. Exploring how glucose excess, estrogen excess, and anxiety work together to affect the speed at which breast cancer cells multiply and the immune system’s response model is necessary to conceive of ways to stop the spread of cancer. This paper proposes a mathematical model to investigate the impact of psychological panic, glucose excess, and estrogen excess on the interaction of cancer and immunity. The proposed model is precisely described. The focus of the model’s dynamic analysis is to identify the potential equilibrium locations. According to the analysis, it is possible to establish four equilibrium positions. The stability analys
... Show MoreGeography of industry has been considered a branch of important economic geographical branches. This importance has been regarded as a reflection on the industrial sector contribution in economies of any state since they contribute into the total national product ; it also assimilates a huge number of labor hands . The industry of grains grinding has been considered as one of the main food industries having a main role in satisfying the need of the population from the foods. The industry is continued to use the food as daily meal . Here, it should predict the population in Baghdad and for every district until the end of 2025 and knowing either these grains grinders are able to meet and satisfy the needs of populations of flours, making s
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