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Detection of Pan Braf in Thyroid Tumors in Iraqi Patients
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The B-type Raf kinase (BRAF) is a member of RAS\RAF\MEK\ERK pathway and this pathway can lead to increased cellular growth, invasion and metastasis. The mutated BRAF protein activates MAPK signaling pathway, results in abnormal cellular growth, apoptosis resistance, tumor progression and metastasis. Pan-BRAF is one of available BRAF monoclonal antibodies and shared by both the wild and mutant BRAF.BRAF status is mostly determined by DNA sequencing methods. In this investigation we assessed the monoclonal Pan BRAF specific antibody that can identify wild and mutant type proteins together in formalin-fixed paraffin-embedded thyroid tumor tissues by Immunohistochemistry (IHC). Archival thyroid samples from 43 iraqi patients were immunohistochemically tested with antibodies for BRAF. Out of 43 thyroid tissue cases, (23) were thyroid malignant,(12) benign, and (8) control cases(diagnosed as colloid goiter).The malignant tumors included Papillary Thyroid Carcinoma (PTC), Follicular Thyroid Carcinoma (FTC), Medullary Thyroid Carcinoma (MTC), Anaplastic Thyroid Carcinoma (ATC) and Hürthle cell cancer (HCC).Immunohistochemical staining for BRAF was performed for all specimens. Results of the study showed that Immunohistochemical expression of pan BRAF was significantly higher in malignant thyroid tumors as compared with adenomas and control cases (P<0.05). BRAF over-expression was detected in 5\12 of PTC, 3\5 MTC, 2\4 of FTCas well as all cases of HCC, ATC.Whereas it was detected in 4\12 of adenomas, and totally negative in control cases. No association was observed between BRAF and other clinicopathological traits. We conclude from this study that IHC using BRAF monoclonal antibody is a
successful way for checking of BRAF status in different thyroid tumors. IHC may be the alternative to molecular biology for the routine detection of this marker in patients with thyroid tumors.

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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Using ARIMA models to forecast the volume of cargo handled in Iraqi ports An applied study in the general company of Iraqi ports
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Time series is an important statistical method adopted in the analysis of phenomena, practices, and events in all areas during specific time periods and predict future values ​​contribute to give a rough estimate of the status of the study, so the study aimed to adopt the ARIMA models to forecast the volume of cargo handled and achieved in four ports (Umm Qasr Port, Khor Al Zubair Port, Abu Flus Port, and Maqal Port(, Monthly data on the volume of cargo handled for the years (2006-2018) were collected (156) observations. The study found that the most efficient model is ARIMA (1,1,1).

The volume of go

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Detection and Mitigation of Cache Pollution Attack Using Popularity Variation in Information Centric Networking Based on SDN
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      Information centric networking (ICN) is the next generation of internet architecture with its ability to provide in-network caching that make users retrieve their data efficiently regardless of their location. In ICN, security is applied to data itself rather than communication channels or devices. In-network caches are vulnerable to many types of attacks, such as cache poisoning attacks, cache privacy attacks, and cache pollution attacks (CPA). An attacker floods non-popular content to the network and makes the caches evict popular ones. As a result, the cache hit ratio for legitimate users will suffer from a performance degradation and an increase in the content’s retrieval latency. In this paper, a popularity variation me

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
A Tri-Gene Ontology Migration Operator for Improving the Performance of Meta-heuristics in Complex Detection Problems
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      Detecting protein complexes in protein-protein interaction (PPI) networks is a challenging problem in computational biology. To uncover a PPI network into a complex structure, different meta-heuristic algorithms have been proposed in the literature. Unfortunately, many of such methods, including evolutionary algorithms (EAs), are based solely on the topological information of the network rather than on biological information. Despite the effectiveness of EAs over heuristic methods, more inherent biological properties of proteins are rarely investigated and exploited in these approaches. In this paper, we proposed an EA with a new mutation operator for complex detection problems. The proposed mutation operator is formulated und

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Publication Date
Sun Jul 02 2023
Journal Name
Iraqi Journal Of Science
RT PCR Detection and Propagation of Respiratory Syncytial Virus in Human Lung Carcinoma Cells (A549) cell line
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In this study negative result of real-time reverse transcription-QPCR (RT-PCR) assay
tests of Influenza virus of nasal screetion and throat swap samples of Iraqi patients
hospitalized with signs and symptoms of an upper respiratory tract infection in Central
Republic Health Laboratory in Iraq were tested for Respiratory Syncytial Virus
infection by RT PCR .Positive samples was 4 out 0f 20 were used .Viral isolation was
done on a monolayer of 70-80% confluent Human Lung Carcinoma Cells (A549) cell
line and incubated at 33ºC for 4 days .Syncytia was observed in 3 positive samples.

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
Damage Detection and Assessment of Stiffness and Mass Matrices in Curved Simply Supported Beam Using Genetic Algorithm
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In this study, a genetic algorithm (GA) is used to detect damage in curved beam model, stiffness as well as mass matrices of the curved beam elements is formulated using Hamilton's principle. Each node of the curved beam element possesses seven degrees of freedom including the warping degree of freedom. The curved beam element had been derived based on the Kang and Yoo’s thin-walled curved beam theory. The identification of damage is formulated as an optimization problem, binary and continuous genetic algorithms
(BGA, CGA) are used to detect and locate the damage using two objective functions (change in natural frequencies, Modal Assurance Criterion MAC). The results show the objective function based on change in natural frequency i

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
A Tri-Gene Ontology Migration Operator for Improving the Performance of Meta-heuristics in Complex Detection Problems
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      Detecting protein complexes in protein-protein interaction (PPI) networks is a challenging problem in computational biology. To uncover a PPI network into a complex structure, different meta-heuristic algorithms have been proposed in the literature. Unfortunately, many of such methods, including evolutionary algorithms (EAs), are based solely on the topological information of the network rather than on biological information. Despite the effectiveness of EAs over heuristic methods, more inherent biological properties of proteins are rarely investigated and exploited in these approaches. In this paper, we proposed an EA with a new mutation operator for complex detection problems. The proposed mutation operator is formulate

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Publication Date
Thu Dec 22 2022
Journal Name
Chemistry &amp; Chemical Technology
Turbidimetric Determination of Mebeverine Hydrochloride in Pharmaceutical Formulations Using Two Consecutive Detection Zones under Continuous Flow Conditions
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A simple, low cost and rapid flow injection turbidimetric method was developed and validated for mebeverine hydrochloride (MBH) determination in pharmaceutical preparations. The developed method is based on forming of a white, turbid ion-pair product as a result of a reaction between the MBH and sodium persulfate in a closed flow injection system where the sodium persulfate is used as precipitation reagent. The turbidity of the formed complex was measured at the detection angle of 180° (attenuated detection) using NAG dual&Solo (0-180°) detector which contained dual detections zones (i.e., measuring cells 1 & 2). The increase in the turbidity of the complex was directly proportional to the increase of the MBH concentration

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Publication Date
Sat Apr 30 2022
Journal Name
Iraqi Journal Of Science
Detection of Shallow Cavities Using 3D Resistivity Technique in a Small Site Near Haditha City, Western Iraq
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     Iraqi western desert is characterized by a widespread karst phenomenon and caves. Euphrates formation (Lower Miocene) includes enormous sinkholes and cavities within carbonate rocks that usually cause severe damages to any kind of engineering facilities built over it. 3D resistivity imaging techniques were used in detecting this kind of cavities in complicated lithology. The 3D view was fulfilled by collating seven 2D imaging lines. The 2D imaging survey was carried out by Dipole-dipole array with (n) factor and electrode spacing (a) of 6 and 2m respectively. The horizontal slices of the 3D models give a good subsurface picture. There are many caves in all directions (x, y, z). They reveal many small caves near the surface. Thes

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Publication Date
Sun Dec 25 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Detection of Epicatechin in Camellia sinensis Leaves by Thin Layer Chromatography and High Performance Liquid Chromatography Techniques
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    The current study performed in order to detect and quantify epicatechin in two tea samples of Camellia sinensis (black and green tea) by thin layer chromatography (TLC) and high performance liquid chromatography (HPLC). Extraction of epicatechin from black and green tea was done by using two different methods: maceration (cold extraction method) and decoction (hot extraction method) involved using three different solvents which are  absolute ethanol, 50% aqueous ethanol and water  for both extraction methods using room temperature and direct heat respectively. Crude extracts of two tea samples that obtained from two methods were fractionated by using two solvents with different polarity (chloroform and

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Publication Date
Mon Feb 01 2016
Journal Name
Swarm And Evolutionary Computation
Improving the performance of evolutionary multi-objective co-clustering models for community detection in complex social networks
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