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Salivary E‐cadherin as a biomarker for diagnosis and predicting grade of periodontitis
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Abstract<sec><title>Objectives

To determine the abilities of salivary E‐cadherin to differentiate between periodontal health and periodontitis and to discriminate grades of periodontitis.

Background

E‐cadherin is the main protein responsible for maintaining the integrity of epithelial‐barrier function. Disintegration of this protein is one of the events associated with the destructive forms of periodontal disease leading to increase concentration of E‐cadherin in the oral biofluids.

Materials and Methods

A total of 63 patients with periodontitis (case) and 35 periodontally healthy subjects (control) were included. For each patient, periodontal parameters including bleeding on probing (BOP), probing pocket depth (PPD), and clinical attachment level (CAL) were recorded. Concentration of salivary E‐cadherin was determined by ELISA. Receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to determine the diagnostic potentials of E‐cadherin.

Results

Level of salivary E‐cadherin was significantly higher in periodontitis cases than controls. The ROC analysis showed that salivary E‐cadherin exhibits excellent sensitivity and specificity (AUC 1.000) to differentiate periodontal health from periodontitis with a cutoff concentration equal to 1.325 ng/mL. The AUCs of E‐cadherin to differentiate grade A from grade B and C periodontitis were 0.731 (cutoff point = 1.754 ng/mL) and 0.746 (cutoff point = 1.722 ng/mL), respectively. However, the AUC of salivary E‐cadherin to differentiate grade B from grade C periodontitis was lower (0.541). Additionally, BOP and PPD were significantly and positively correlated with the concentration of salivary E‐cadherin.

Conclusion

Salivary E‐cadherin exhibited excellent sensitivity and specificity to differentiate periodontitis from a healthy periodontium. The level of accuracy of E‐cadherin was also sufficient to recognize grade A periodontitis from grade B and C periodontitis.

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Comparison between Linear and Non-linear ANN Models for Predicting Water Quality Parameters at Tigris River
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In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.

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Publication Date
Mon Dec 22 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Immunohistochemical expression of D2-40, VEGF and PCNA as biological markers of lymphangiogenesis, angiogenesis and proliferation in pleomorphic adenoma of salivary gland origin
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Background: Pleomorphic adenoma is the most common benign salivary gland tumor and shows a pronounced morphological complexity and diversity; for this The immunoprofiles and clinical course of PA differed according to cellular differentiation. Therefore, it is important to assess potential biomarkers in diagnostic and therapeutic trials. This study evaluates the immunohistochemical expression of D2-40, VEGF and PCNA as markers of lymphangiogenesis, angiogenesis and proliferation of PA and their correlation with clinicpathological parameters and with each other. Materials and Methods: Twenty five formalin – fixed, paraffin – embedded tissue blocks were included in this study. After histopathological reassessment of haematoxylin & eosin

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering
Development of Regression Models for Predicting Pavement Condition Index from the International Roughness Index
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Flexible pavements are considered an essential element of transportation infrastructure. So, evaluations of flexible pavement performance are necessary for the proper management of transportation infrastructure. Pavement condition index (PCI) and international roughness index (IRI) are common indices applied to evaluate pavement surface conditions. However, the pavement condition surveys to calculate PCI are costly and time-consuming as compared to IRI. This article focuses on developing regression models that predict PCI from IRI. Eighty-three flexible pavement sections, with section length equal to 250 m, were selected in Al-Diwaniyah, Iraq, to develop PCI-IRI relationships. In terms of the quantity and severity of eac

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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Artificial neural network model for predicting the desulfurization efficiency of Al-Ahdab crude oil
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Publication Date
Mon Jul 01 2019
Journal Name
Iop Conference Series: Materials Science And Engineering
Optical Diagnosis of Prostate Cancer
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Publication Date
Thu Jul 06 2017
Journal Name
Al-mustansiriyah Journal Of Science
Modification the ELISA Kit for diagnosis of Psedudomonas aeruginosa and comparing its with ordinary ELSA Kit
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Publication Date
Fri Nov 20 2020
Journal Name
Agriculture
Predicting Phosphorus and Potato Yield Using Active and Passive Sensors
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Applications of remote sensing are important in improving potato production through the broader adoption of precision agriculture. This technology could be useful in decreasing the potential contamination of soil and water due to the over-fertilization of agriculture crops. The objective of this study was to assess the utility of active sensors (Crop Circle™, Holland Scientific, Inc., Lincoln, NE, USA and GreenSeeker™, Trimble Navigation Limited, Sunnyvale, CA, USA) and passive sensors (multispectral imaging with Unmanned Arial Vehicles (UAVs)) to predict total potato yield and phosphorus (P) uptake. The experimental design was a randomized complete block with four replications and six P treatments, ranging from 0 to 280 kg P ha−1, as

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Publication Date
Tue Jan 01 2013
Journal Name
Journal Of The College Of Languages (jcl)
A Study in Tess of the D’Urbervilles as A Call for Liberal Education for Women
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Amongst the literary writers who used their art to direct the attention towards the issue of woman and her rights in a proper life is the English poet and novelist Thomas Hardy (1840-1928), who has been praised for his “openness to the feminine principle” 1 as Irving Howe put it. Hardy’s wide readings have changed his way of dealing with and thinking about so many critical issues which started to float on the surface of the English society during the mid and late of the 19th century. His readings for a number of writers, who seem of huge impact on his writings as he later admits that – “[his] pages show harmony of view with

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Publication Date
Mon Dec 22 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Periodontitis among a Group of Type TwoDiabetic Patientsin Relation to Risk of Vascular Disease
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Background: Type two diabetic patients have higher risk of cardiovascular and periodontal disease. Furthermore, patients with more severe periodontal disease have higher incidence of cardiovascular disease. This study aimed to assess the association between periodontal health status and the risk of vascular disease in type 2 diabetic patients. Materials and Methods: One hundred type 2 diabetes mellitus patients and fifty apparently healthy males were enrolled in this study. Oral examinations conducted were; plaque Index, calculus index, gingival index, probing pocket depth, and clinical attachment level. For the assessment of vascular risk, arterial stiffness index was used. Results: According to arterial stiffness index, type 2 diabetic p

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Publication Date
Sat Aug 09 2025
Journal Name
Scientific Reports
Machine learning models for predicting morphological traits and optimizing genotype and planting date in roselle (Hibiscus Sabdariffa L.)
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Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

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