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Expression of programmed death ligand 1 in patients with triple‑negative breast cancer: Association with clinicopathological parameters
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The utilization of targeted therapy for programmed death ligand 1 (PD‑L1) has emerged as a prominent focus in contemporary clinical trials, particularly in the context of immune checkpoint inhibitors. The prognostic significance of the expression of PD‑L1 in invasive mammary cancer remains a subject of discussion in clinical oncology, requiring further exploration, despite its recognition as a biomarker for responsiveness to anti‑PDL1 immunotherapy. The present study was conducted to investigate the immunohistological expression of PD‑L1 in women with triple‑negative breast cancer (TNBC), with a particular focus for searching for the associated clinical and pathological characteristics. The present retrospective study examined the immunohistochemical expression of PD‑L1 in 40 formalin‑fixed paraffin‑embedded blocks provided by core needle biopsies from women with TNBC. Data analysis was performed by comparing PDL1 expression with histological grade, the presence or the absence of calcification, the presence or the absence of necrosis and axillary lymph node status at presentation. The positivity of PD‑L1 expression was found in 24 (60%) of the total number of samples. The mean number of PD‑L1 positive samples was 37.8333±21.857. There was a non‑statistically significant association between PD‑L1 positivity, histological grade and the presence of tissue necrosis. A statistically significant association was found between PD‑L1 positivity and the presence of calcification and positive axillary lymph node status at presentation. On the whole, the present study demonstrates that PD‑L1 expression is present at a relatively high prevalence rate in TNBC; thus, it is rational to examine PD‑L1 expression in women with TNBC.

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Publication Date
Sat Jun 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Anodic Polarization of Mild Steel in Saturated C a(OH)2 Contaminated with NaCl in Presence of NaNO2
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The corrosion  behavior  of mild sleet  in saturated  aerated  and de-aerated  Ca(OH)2 solution  was  investigated  using electrochemical measurements. The work was carried out with small coupons immersed in solutions containing different quantities of NaCl in presence of various NaN02 concentrations as corrosion inhibitors. It has been found thal:(1 ) In presence  of NaCl,  the time required  to reach O2  evolution potential  in de-aerated  Ca(OH)2 polarized  at  10μA/cm 2 is function of inhibitor concentration and it becomes lass as NaN02 increases compared with zero presence indicating the effectiveness of N

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Publication Date
Wed Dec 01 2010
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
IDENTIFICATION OF PATHOGENIC FUNGI ASSOCIATED WITH WATER HYACINTH IN SELECTED REGIONS IN THE MIDDLE AND SOUTH OF IRAQ
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To identify the fungi associated with water hyacinth (Eichhornia crassipes [Mart.] Solms), an aquatic weed, which presents in Tigris river from Baghdad south ward. Five regions from middle and south of Iraq (Al-Noumanya, Saeid Bin-Jubier, Al-Azizia, Al-Reyfay and Al-Hay) were selected for this study. Twelve fungal species were isolated. Alternaria alternata, Acremonium sp and Cladsporium herbarum, were the most frequently species (91.66 % ,50 % and 25 %) respectively. The fungi Alternaria alternata, Acremonium sp. and Phoma eupyrena were more aggressive to water hyacinth as (91.66%,83,33%, and 75%) in pathogenicity test.

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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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Publication Date
Thu Dec 01 2022
Journal Name
Advances In Cancer Biology - Metastasis
CX3CL1 as potential immunotherapeutic tool for bone metastases in lung cancer: A preclinical study
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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
Sat Nov 01 2014
Journal Name
Journal Of Cosmetics, Dermatological Sciences And Applications
Frictional melanosis of rubbing thighs in Iraqi patients
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KE Sharquie, AA Noaimi, AA Hajji, Journal of Cosmetics, Dermatological Sciences and Applications, 2014 - Cited by 5

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Publication Date
Sun Mar 04 2018
Journal Name
Baghdad Science Journal
Detection of Chlamydia pneumoniae in Ankylosing Spondylitis Patients
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Ankylosing spondylitis is a complex debilitating disease because its pathogenesis is not clear. This study aims at detecting some pathogenesis factors that lead to induce the disease. Chlamydia pneumoniae is one of these pathogenesis factors which acts as a triggering factor for the disease. The study groups included forty Iraqi Ankylosing spondylitis patients and forty healthy persons as a control group. Immunological and molecular examinations were done to detect Chlamydia. pneumoniae in AS group. The immunological results were performed by Enzyme-Linked Immunosorbent Assay (ELISA) to detect anti-IgG and anti-IgM antibodies of C. pneumoniae revealed that five of forty AS patients' samples (12.5%) were positive for anti-IgG and IgM C. pneu

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Publication Date
Sat Nov 01 2014
Journal Name
American Journal Of Dermatology And Venereology
The Status of Malignant Melanoma in Iraqi Patients
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KE Sharquie, A Noaimi, W Al-Janabi, American Journal of Dermatology and Venereology, 2014 - Cited by 4

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Publication Date
Tue Jan 01 2019
Journal Name
Revista De Chimie
Synthesis, Characterization and Antibacterial Activity from Mixed Ligand Complexes of 8-Hydroxyquinoline and Tributylphosphine for Some Metal Ions
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Co+2, Ni+2, Cu+2 as well Zn+2 compounds mixed ligand from 8-hydroxyquinoline(8-HQ) also tributylphosphine (PBu3) have been attended at aquatic ethyl alcohol for (1:2:2) (M:8-HQ:PBu3). Produced complexes have been identified by utilizing atomic absorption flame, FT-IR as well UV-Vis spectrum manners also magnetic susceptibility as well as conductivity methods. At addendum antibacterial efficiency from the ligands as well complexes oboist three species about bacteria have been as well examined. Ligands and their complexes show good bacterial efficiencies. Of the gained datum the octahedral geometry was proposed into whole prepared complexes

Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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