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G Protein-Coupled Receptors: Undervalued Targets for Cancer Therapy
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Despite the G protein-coupled receptors (GPCRs) being the largest family of signalling proteins at the surface of cells, their potential to be targeted in cancer therapy is still under-utilised. This review highlights the contribution of these receptors to the process of oncogenesis and points to some likely challenges that might be encountered in targeting them. GPCR-signalling pathways are often complex and can be tissue-specific. Cancer cells hijack these communication networks to their proliferative advantage. The role of selected GPCRs in the different hallmarks of cancer is examined to highlight the complexity of targeting these receptors for therapeutic benefit. Our increasing knowledge of the mechanisms governing the molecular functions of GPCRs may help to identify new targets to treat specific types of cancers.

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Publication Date
Wed Jan 01 2020
Journal Name
Plant Archive
Isolation of candida spp. From cancer patients who suffered oral candidiasis due to immunodeficiency
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solation of candida spp. From cancer patients who suffered oral candidiasis due to immunodeficiency

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Publication Date
Fri Apr 29 2022
Journal Name
Iraqi Journal Of Agricultural Sciences
RECURRENT OF TMPRSS2 GENETIC POLYMORPHISM AND ITS ROLE IN IRAQI PATIENTS WITH PROSTATE CANCER
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The role of transmembrane protease serine 2(TMPRSS2) in prostate carcinogenesis relies on overexpression of ETS transcription factors. The aim of this article was to investigate the association of TMPRSS2 polymorphism (rs12329760 (C\T)) with prostate cancer (PCa) in sample of Iraqi patients. One hundred and two individuals were involved in this study for the period from February – 2019 to February – 2020. The sample type was formalin fixed paraffin embedded tissue samples (FFPE), which involved  fifty-six samples of pre-diagnosed patients with prostate cancer, aged between 48 and 86 years, and forty-six samples were found to be controls (healthy group) dependent on Prostate Gland integrity, which is the same age as in a group o

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Cytotoxic effects of new synthesis heterocyclic derivatives of Amoxicillin on some cancer cell lines
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A new Schiff base [I] was prepared by refluxing Amoxicillin trihydrate and 4-Hydroxy- 3,5-dimethoxybenzaldehyde in aqueous methanol solution using glacial acetic acid as a catalyst. The new 1,3-oxazepine derivative [II] was obtained by Diels- Alder reaction of Schiff base [I] with phthalic anhydride in dry benzene. The reaction of Schiff base [I] with thioglycolic acid in dry benzene led to the formation of thiazolidin-4-one derivative [III]. While the imidazolidin-4-one [IV] derivative was produced by reacting the mentioned Schiff base [I] with glycine and triethylamine in ethanol for 9 hrs. Tetrazole derivative [V] was synthesized by refluxing Schiff base [I] with sodium azide in dimethylformamid DMF. The structure of synthesized compound

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Determination Oxidant - Antioxidant Enzyme and some Trace Elements in Breast Cancer in Baghdad City
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level of effectiveness of Glutathione - S - Transferees (GST), Glutathione peroxides (GPX),Malondialdehyde (MDA) the product of lipid peroxidation and some trace elements ( zinc,seleinum,iron ,copper ) had been measured in sera of (50) women with breast disease.which had been divided to : Control group (25),The first group (A) benign breast tumors (25),the second group (B) breast cancer (25). The results showed a clear moral high level of Glutathione - S - Transferees (GST), Glutathione peroxidase (GPX) , and Malondialdehyde (MDA) level in breast cancer group while a slight increase were observed in the levels of these enzymes and(MDA) in benign breast group. A significant reduction was evident in the levels of selenium and zinc

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Distinguishing Shapes of Breast Cancer Masses in Ultrasound Images by Using Logistic Regression Model
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The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Using the Logistic Regression Model in Studding the Assistant Factors to Diagnose Bladder Cancer
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The cancer is one of the biggest health problems that facing the world . And  the bladder cancer has a special place among the most spread cancers in Arab countries specially in Iraq and Egypt(2) . It is one of the diseases which can be treated and cured if it is diagnosed early . This research is aimed at studying the assistant factors that diagnose bladder cancer such as (patient's age , gender , and other major complains of hematuria , burning or pain during urination and micturition disorders) and then determine which factors are the most effective in the possibility of diagnosing this disease by using the statistical model (logistic regression model) and depending on a random sample of (128) patients . After

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Publication Date
Mon Feb 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Comparative study of logistic regression and artificial neural networks on predicting breast cancer cytology
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<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

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Publication Date
Wed Jan 01 2020
Journal Name
Gastric And Breast Cancer
The 21-gene oncotype DX offers more accurate treatment decisions in early breast cancer
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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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Publication Date
Thu Dec 15 2022
Journal Name
Bionatura
NDRG1 is being investigated as a possible bladder cancer biomarker in the Iraqi population.
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With 549,393 new cases recorded in 2018, bladder cancer is one of the most common malignancies worldwide. Urinary bladder cancer is the cause of about 3 percent of all new cancer diagnoses and 2.1 percent of all cancer deaths. This study aims to evaluate the efficiency of the N-myc downstream-regulated gene 1(NDRG1) as a biomarker for bladder cancer patients in the Iraqi population. One hundred individuals in the case-control study were enrolled and divided into two groups. The first group included 50 patients diagnosed with a bladder mass and investigated by undergoing cystoscopy examination for transurethral resection of bladder tumor (TURB). The second group included 50 healthy individuals who had normal bladder tissue. The resul

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