Gingival crevicular fluid (GCF) may reflect the events associated with orthodontic tooth movement. Attempts have been conducted to identify biomarkers reflecting optimum orthodontic force, unwanted sequallea (i.e. root resorption) and accelerated tooth movement. The aim of the present study is to find out a standardized GCF collection, storage and total protein extraction method from apparently healthy gingival sites with orthodontics that is compatible with further high-throughput proteomics. Eighteen patients who required extractions of both maxillary first premolars were recruited in this study. These teeth were randomly assigned to either heavy (225g) or light force (25g), and their site specific GCF was collected at baseline and after 1hr, 1day, 7days, 14days, 21days and 28days post force application. Periostrips were used for GCF collection and subsequent phosphate buffered saline (PBS) was used for immediate protein elution with centrifugal speed of 10000rpm for 5min and stored at -80°C. Protein concentration was estimated using Bradford colorimetric assay. Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) was carried out to resolve the purity of proteins in the collected samples and the method of collection was validated by western immuno-blotting of alpha amylase salivary enzyme. The current collection, storage and protein extraction protocol showed the best protein recovery and purity with validated collection free of salivary contamination. In conclusion, tiny GCF volume from healthy sites and evaporation issues of such promising non-invasive fluid motivate us to investigate a standardized protocol enabling optimal preservation of GCF sample and the currently followed protocol may serve as a reference for future proteomic studies searching for GCF biomarkers in diagnosing and monitoring orthodontic tooth movement.
The laminar fluid flow of water through the annulus duct was investigated numerically by ANSYS fluent version 15.0 with height (2.5, 5, 7.5) cm and constant length (L=60cm). With constant heat flux applied to the outer duct. The heat flux at the range (500,1000,1500,2000) w/m2 and Reynolds number values were ≤ 2300. The problem was 2-D investigated. Results revealed that Nusselt number decrease and the wall temperature increase with the increase of heat flux. Also, the average Nusselt number increase as Re increases. And as the height of the annulus increase, the values of the temperature and the local and average Nusselt number increase.

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet
... Show MoreBackground: Whey protein is the green-yellow colored, liquid portion of the milk, and it is also called the cheese serum, it is obtained after the separation of curd, during the coagulation of the milk. It contains a considerable amount of α-helix pattern with an evenly distributed hydrophobic and hydrophilic as well as basic and acidic amino acids along with their polypeptide chain. The major whey protein constituents include β-lactoglobulin (β-LG),α-lactalbumin (α-LA), immunoglobulins (IG), bovine serum albumin (BSA), bovine lactoperoxidase (LP), bovine lactoferrin (BLF) and minor amounts of a glycol macro peptide (GMP). Osseointegration can be defined as a process that is immune driven which leads to the formatio
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