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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
Fri Dec 07 2018
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Effects of Aldosterone, Osteoprotegerin and Fibroblast Growth Factor-23 and Some Biochemical Markers in Chronic Kidney Disease Patients (Stage II-IV) among Patients with or without Cardiovascular Events
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Chronic Kidney Disease (CKD) is a public health problem and many studies support the link between kidney dysfunction and cardiovascular events.  Aldosterone has been shown for decades that a plasma aldosterone concentration is elevated in CKD. Whilst, Osteoprotegerin (OPG), after its capacity to protect bone, also osteoprotegerin is elevated in patients with chronic kidney disease (CKD), where it could predict the deterioration of kidney function, cardiovascular, vascular events and all-cause mortality. On the other hand, fibroblast growth factors (FGFs), in patients with CKD, its levels seem to increase progressively as kidney function worsens. The aim of the present study is to assess the correlations between serum osteoprotegerin

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Publication Date
Thu Jun 30 2016
Journal Name
Al-kindy College Medical Journal
Detection similarity and differences between Uropathogenic Escherichia coli isolated from recurrent urinary tract infections and bladder cancer patients
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Background: Urinary tract infections (UTIs) and their complications such as Bladder cancer (Bl. C.) are a health growing problem worldwide. Objective: To shed light on this subject, present study was done to investigate relationship between recurrent urinary tract infection (RUTI) due to Escherichia coli (E. coli) and Bl. C.Type of study: Cross-sectional study. Methods: This study included 130 patients with RUTI, 50 patients with Bl. C. and 50 control of both sexes (aged 7-85 years) attending Al-Zahra Teaching Hospital in Al-Kut/Wassit governorate and Al-Harery Teaching Hospital of specialized surgeries/Baghdad. The patients were divided into two groups: the first group (n=130) included those who were suffering from recurrent UTI without

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Publication Date
Thu Jun 11 2026
Journal Name
Journal Of Baghdad College Of Dentistry
The study of tempromandibular joint disorders and anti-cyclic citrullinated peptide antibodies in serum and saliva of patients with rheumatoid arthritis
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Background: Rheumatoid arthritis is an autoimmune disease that affects mainly the synovial membranes and articular structures and is characterized by chronic, systemic inflammation involving multiple joints.Being a synovial joint, the Temporomandibular Joint is subject to the same disorders affecting other synovial joints, including RA.Beside it was considered as a specific serological marker for diagnosing RA disease ,antibodies to cyclic citrullinated peptide have proven to be associated with joints destruction, though; it may play a potential role in the prediction of the disease severity. Materials and Methods: Sixty nine individuals (69) were enrolled in this study, forty nine (49) were patients diagnosed with Rheumatoid Arthritis, a

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Publication Date
Mon Jul 24 2023
Journal Name
Research Journal Of Pharmacy And Technology
Comparison of the effects of Methotrexate and Etanercept on RANKL and OPG as Bone Metabolism Biomarkers in patients with Rheumatoid Arthritis
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Rheumatoid arthritis is an autoimmune diseasecharacterized by chronic inflammationthat affects joints and cartilage. Bone complications such asRA-relatedosteoporosis are one of the most extra-articular manifestations. Many inflammatory mediators are released during RA disease pathophysiology; these mediators stimulate osteoclast genesis of bone by direct effects on RANKL and OPG. The study aimedto measure RANKL, OPG in RA patients treated with Etanercept only and other groups treated with Methotrexate onlyat baseline and after three months to evaluate bone state. An observational case-control prospective study was done on 30 RA patients who received MTX, 30 RA patients who received ETN, and 30 healthy,age-matched control groups. The

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Publication Date
Sat Dec 24 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Occurrence of Quinolone-Resistance Genes in Ciprofloxacin-Resistant Salmonella Enterica Serotype Typhi Isolated form Blood Sample of Patients with Typhoid Fever
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Salmonella is approved as a common foodborne pathogen, causing major health problems throughout the world particularly in low‐ and middle‐income countries. Low-level fluoroquinolone resistance is conferred by both chromosomal and plasmid-encoded resistance, this research was carried out look into the occurrence rate of qnrA,qnrB and qnrS genes  in  Salmonella enterica serotype Typhi Cipr  ofloxacin-resistant insulate from blood samples of patients with typhoid fever. Fifteen Salmonella enterica serotype Typhi isolated previously from patients with typhoid fever were included in this study. All bacterial isolates were confirmed to have ciprofloxacin

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Publication Date
Wed Dec 14 2016
Journal Name
Journal Of Baghdad College Of Dentistry
Oral Health Status among Group of Patients with Juvenile Idiopathic Arthritis According to Duration of Illness and Age Group in Iraq
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Background: Juvenile idiopathic arthritis (JIA) is a chronic disease of childhood. Increased prevalence of periodontal disease and dental caries in juvenile idiopathic arthritis is due to difficulties in executing good oral hygiene. This study was conducted to assess oral health status in patients with Juvenile idiopathic arthritis according to age and duration of illness. Materials and methods: A research was conducted among Juvenile idiopathic arthritis patients attending Baghdad Teaching Hospital with different age and both gender, underwent a clinical evaluation of their dental and oral condition. Diagnosis of dental caries was done according to the criteria of WHO (1997). Dental plaque, gingival condition, calculus were assessed by PI/

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Publication Date
Thu Mar 30 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Relationship between Uric Acid Concentration and Some of Plasma Lipids in Patients with C. V. Disease in General Hospital of Al-Nasseriya
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         Cardiovascular disorders  are  refer to the class of diseases that involve the heart or blood vessels (arteries and veins). While the term technically refers to any disease that affects the cardiovascular system. Cholesterol is classified as a sterol (a contraction of steroid and

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Publication Date
Tue Mar 01 2016
Journal Name
Journal Of Pharmaceutical Sciences
Development and Evaluation of Biodegradable Particles Coloaded With Antigen and the Toll-Like Receptor Agonist, Pentaerythritol Lipid A, as a Cancer Vaccine
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Publication Date
Sat Dec 01 2012
Journal Name
Iraqi Journal Of Physics
A computer experiment to study the charging process of dust grains in negative ion plasma
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This work presents a computer studying to simulate the charging process of a dust grain immersed in plasma with negative ions. The study based on the discrete charging model. The model was developed to take into account the effect of negative ions on charging process of dust grain.
The model was translated to a numerical calculation by using computer programs. The program of model has been written with FORTRAN programming language to calculate the charging process for a dust particle in plasma with negative ion, the time distribution of a dust charge, number charge equilibrium and charging time for different value of ηe (ratio of number density of electron to number density of positive ion).

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

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