The pancreatic ductal adenocarcinoma (PDAC), which represents over 90% of pancreatic cancer cases,
has the highest proliferative and metastatic rate in comparison to other pancreatic cancer compartments. This
study is designed to determine whether small nucleolar RNA, H/ACA box 64 (snoRNA64) is associated with
pancreatic cancer initiation and progression. Gene expression data from the Gene Expression Omnibus (GEO)
repository have shown that snoRNA64 expression is reduced in primary and metastatic pancreatic cancer as
compared to normal tissues based on statistical analysis of the in Silico analysis. Using qPCR techniques,
pancreatic cancer cell lines include PK-1, PK-8, PK-4, and Mia PaCa-2 with different levels of snoRNA64,
including PK-1, PK-8, PK-4, and Mia PaCa-2. The level of expression is correlated with the cell line epithelial
or mesenchymal characteristics. Cell lines displaying epithelial characteristics such as PK-1, PK-8 show high
levels of snoRNA64 meanwhile, cell lines displaying mesenchymal characteristics such as PK-4, Mia PaCa-2
show low levels of snoRNA64. The level of expression is correlated with the cell line epithelial or
mesenchymal characteristics. After knocking down the PK-8 with high snoRNA64 expression, the epithelial
markers E. cadherin (E-cad) and Cytokeratin-8 (CK-8) are decreased, while mesenchymal markers Vimentin
(Vim), Cytokeratin-19 (CK-19), Metalloprotease -2 (MMP-2), and Metalloprotease-3 (MMP-3) are activated.
Those changes suggest that PK-8 responding to the snoRNA64 knock down protocol and increase in
mesenchymal function. Together, snoRNA64 expression may participate in epithelial to mesenchymal
transition (EMT) and mesenchymal to epithelial transition (MET), in which during metastasis these processes
are crucial. In addition, snoRNA64 may be considered as a potential diagnostic biomarker for both early and
invasive stages of PDAC. And due to its gradual expression decreases, it may be considered a barrier in tumor
progression.
Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. T
... Show MoreStatement of the Problem. The use of orthodontic fixed appliances may adversely affect oral health leading to demineralizing lesions and the development of gingival problems. Aims of the Study. The study aimed to coat orthodontic archwires with chlorhexidine hexametaphosphate nanoparticles (CHX-HMP NPs) and to evaluate the elusion of CHX from CHX-HMP NPs. Materials and Methods. A solution of CHX-HMP nanoparticles with an overall concentration of 5 mM for both CHX and HMP was prepared, characterized (using atomic force microscope and Fourier transformation infrared spectroscopy), and used to coat orthodontic stainless steel (SSW) and NiTi archwires (NiTiW). The coated segments were characterized (using scanning electron microscopy
... Show MoreMany isolated rural communities are located in regions where there is an abundant and reliable supply of solar energy, but where the distance to the nearest power station is many tens or even hundreds of kilometre. It is therefore mainly in these areas that rural electrification is now being provided by PV generators. since Stand-Alone PV generator can offer the most cost-effective and reliable option for providing power needed in remote places. Accordingly these isolated rural canters are fitted with PV for lighting, a refrigerator, a television and socket to supply kitchen appliances
Objective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using
... Show MoreThe Research aims to determine role of The Intellectual capital in the performance of small and medium enterprises , to achieve this goal through a researcher from the theoretical literature and studies related to the construction of the scheme shows the hypothetical relationship between the variables, which was adopted by the independent variable intellectual capital, distributed four variable are:( human capital, structure capital ,customer capital, innovation capital) as well as four variable (the financial perspective, the customer perspective, process perspective ,the learning & growth perspective) The study were getting to many results as bellow :the intellectual capital in the small and intermediate p
... Show MoreAlpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images
Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration
... Show MoreThe Web Design Quality Index, known as WDQI, was applied to assess the quality of websites for six Iraqi universities, namely Basra University, Mosul, Muthanna, Samarra, Dijla University College, and Al-Isra University College. The results of the index showed that the universities of Basra and Dijla University College had the highest value, at 71.07 and 70.39, respectively. Its final evaluation metric was that the website of these two universities needed a slight improvement. As for the rest of the other universities, the final values of the index ranged from 64.72-69.71. When the final values of the index are displayed on the final evaluation scale, it appears that the websites of the four universities need many improvements. The study
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