Background: Secretory Immunoglobulin A (SIgA) is a subclass of Immunoglobulin A (IgA), It is an antibody that plays an important role in mucosal immunity. It is the main immunoglobulin found in mucous secretions from mammary glands, tear glands and salivary glands, every pathologic process in the body involves the immune system, and periodontal inflammation is one of them and is not an exception. Material and methods: this study was consisted of 60 healthy male participants of an age ranged between (35-50) years old ; 25 of them with generalized moderate chronic periodontists(Clinical Attachment Loss equal to 3-4mm at ≥ 30% of the sites; 20 participants with plaque induced gingivitis and 15 participants had clinically healthy periodontium as control group. oral examination include Plaque Index, Gingival Index, Probing Pocket Depth and Clinical Attachment Level were conducted for all participants four sites were examined for each tooth (labial ,lingual, mesial and distal), 2ml of unstimulated whole saliva was collected from all participants to measure Secretory Immunoglobulin A in µg /ml by Enzyme-linked immunosorbent assay technique. Results: salivary IgA(sIgA) mean was (356.3) µg /ml for the chronic periodontitis patients; while it was 202 µg /ml for plaque induced gingivitis patients and it was 129.2 µg /ml for the control group. Highly significant differences among the three group were recorded (P-value <0.001). For chronic periodontitis patients, the Plaque Index Gingival Index scores were positively highly significant correlated with Secretory Immunoglobulin A level in saliva. The Probing Pocket Depth scores were positively and significantly associated with Secretory Immunoglobulin A level. The Clinical Attachment Level scores were positively but non significant associated with Secretory Immunoglobulin A level. For the gingivitis and the control group they were positive non significant association between the periodontal parameters and the Secretory Immunoglobulin A level in saliva. Conclusion: there is a correlation between Secretory Immunoglobulin A level in saliva and the periodontal health status.
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Neuron-derived neurotrophic factor [NENF], a human plasma neurotrophic factor, also increases neurotrophic activity in conjunction with Parkinson's disease-related proteins in Neudesin. Although Neudesin (neuron-derived neurotrophic secreted protein) is a member of the membrane-associated progesterone receptor (MAPR) protein subclass, it is not evolutionary related to the other members of the same family. The expression of Neudesin is found in both brain and spinal cord from embryonic stages to adulthood, as w Neudesin levels in Parkinson's patients with osteoporosis disease and Parkinson's patients without osteoporosis disease, as well as the relationship between Neudesin levels, Anthropometric and Clinical Features (Age, Gender, BMI) and
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The purpose of this paper is to apply different transportation models in their minimum and maximum values by finding starting basic feasible solution and finding the optimal solution. The requirements of transportation models were presented with one of their applications in the case of minimizing the objective function, which was conducted by the researcher as real data, which took place one month in 2015, in one of the poultry farms for the production of eggs
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Thyroid hormones (TH) regulate the metabolic processes required for normal development and growth; also, to organizemetabolism in adults, any defect in thyroid function leads to abnormality in thyroid hormones level. The current study hasbeen designed to find the relationship between retinol-binding protein-4 and progranulin in the serum of Iraqi women withhypothyroidism and hyperthyroidism, also, to study whether these patients are exposed to a risk of developing diabetes mellitus,and PGRN may be a biomarker in detection early stage of diabetes mellitus.Materials and Methods: in this study, serum samples were obtained from 50 Iraqis women patients, [25 patients withhypothyroidism (G2) and 25 patients with hyperthyroidism (G3)] in addition
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Oral carcinoma is the 6th most common cancer in the world. MicroRNAs are small non-coding single stranded RNAs. They have been shown to be capable of altering mRNA expression; thus some are oncogenic or tumor suppressive in nature. The salivary microRNA-31 has been proposed as a sensitive marker for oral malignancy since it was abundant in saliva more than in plasma. A total of 55 whole saliva samples were collected from 35 cases diagnosed with OC their ages and gender matched with 20 healthy subjects. TaqManq RT-PCR was performed for RNA samples. Mean age was 52.23+13.73 years in cases (range:17-70 years) with male predominance represented 69%. Risk of smoking and alcoholism was highly significant. The median fold change of miR-31 was sign
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To determine the association between cigarette smoking and oxidative stress, a study was conducted in the period from January 2020 to April 2021, at College of Medicine, Al-Nahrain University, Baghdad, Iraq. The Enzyme-linked immunosorbent assay (ELISA) technique was utilized for measurement the antioxidant enzymes including: Glutathione superoxide (GPX) and catalase (CAT) and the biomarker of lipid peroxidation Malondialdehyde (MDA). Also, the gene expression of Nrf2 and HO-1were determined by using RT-PCR technique. The results indicate lower level of both GPX and CAT (p ≤ 0.001) in smokers compared with non-smokers. While the result of MDA indicate higher level in smokers (p≤0.001) compared with nonsmokers. The Nrf2 and HO-1 gene exp
... Show MoreA comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered. Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution. We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large). And Bayes estimators for the parameter is derived under a squared erro
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