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Ability of gingival crevicular fluid volume, E‐cadherin, and total antioxidant capacity levels for predicting outcomes of nonsurgical periodontal therapy for periodontitis patients
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Abstract<sec><title>Objectives

To determine the potential of gingival crevicular fluid (GCF) volume, E‐cadherin and total antioxidant capacity (TAC) levels to predict the outcomes of nonsurgical periodontal therapy (NSPT) for periodontitis patients.

Background

NSPT is the gold‐standard treatment for periodontal pockets < 6 mm in depth, however, successful outcomes are not always guaranteed due to several factors. Periodontitis‐associated tissue destruction is evidenced by the increased level of soluble E‐cadherin and reduced antioxidants in oral fluids which could be used as predictors for success/failure of NSPT.

Materials and Methods

Patients with periodontitis (n = 24) were included in this clinical trial and full‐mouth periodontal charting was recorded for each patient. GCF samples from periodontal pockets with probing pocket depth (PPD) 4–6 mm from the interproximal surfaces of anterior and premolar teeth were obtained. These sites subsequently received NSPT and were clinically re‐evaluated after 1 and 3 months. Levels of GCF E‐cadherin and TAC levels were assayed using ELISA.

Results

All clinical periodontal parameters were significantly improved 3 months after completion of NSPT. These outcomes were associated with a significant decrease in E‐cadherin levels and GCF volume, while TAC levels were significantly increased in samples obtained in follow‐up appointments. Binary regression model analysis showed that PPD, GCF volume, E‐cadherin, and TAC levels could significantly (p < .05) predict the outcomes of NSPT. The cut‐off points for PPD, GCF volume, E‐cadherin and TAC were 5 mm, 4 × 10−3, 1267.97 pg/mL and 0.09 μmol/g, respectively.

Conclusion

NSPT improved clinical parameters along with increased antioxidants capacity and epithelial pocket lining integrity. Discrimination of favorable/unfavorable responsiveness of periodontally diseased sites to NSPT could be possible by using GCF volume, PPD, E‐cadherin and TAC level assessments.

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Thu Oct 01 2015
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   This research seeks to shed light on what you add intangible assets of benefit to the company and this antagonize pause for consideration because it makes the company in a good competitive position stimulates the rest of the companies to acquire those assets.

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Wed Oct 04 2023
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Antiviral medications may be the best choices for COVID-19 treatment until particular therapeutic treatments become available. Tamiflu (oseltamivir) is a neuraminidase inhibitor licensed for the management and defense against influenza types A and B. Oseltamivir-based medication combinations are currently being used to treat COVID-19 patients who also have the new coronavirus 1 SARS-CoV-2. 1 Oseltamivir administration was related with a less time spent in the hospital, quicker recovery 1 and discharge, and a decreased mortality rate. Docking is a modern computational method for identifying a hit molecule by assessing the binding ability of molecular medicines within the binding target pocket. In this work, we chose 21 ligand compounds that

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Wed Jul 01 2015
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تعد الانتخابات بمثابة الطريق المؤدي إلى الديمقراطية كونها النمط الأكثر شيوعاً لمشاركة المواطنين في الحياة السياسية للبلدان واختيار ممثليهم في المجالس التشريعية، حيث أن مطلب إجراء انتخابات حرة ونزيهة لم يعد مطلباً داخلياً فحسب بل مطلباً دولياً يصرّ المجتمع الدولي على الوفاء به وهذا يلقي على عاتق كل دولة أن تضع من الضمانات ما يكفل ممارسة هذه الانتخابات ب

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Crossref
Publication Date
Tue Jun 30 2015
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Indicators Trends Of Populaion Structure Composition In Iraq And Their Relationship With Dependency Rates For The Period (1986-2010).: Indicators Trends Of Populaion Structure Composition In Iraq And Their Relationship With Dependency Rates For The Period (1986-2010).
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Publication Date
Wed Mar 20 2024
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Advanced Machine Learning application for Permeability Prediction for (M) Formation in an Iraqi Oil Field
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Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

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