The biomarker significance of three chemokines (CXCL8, CXCL10 and CXCL16) was evaluated in sera of 45 breast cancer (BC) and 28 benign breast lesion (BBL) patients, as well as 20 control women. Clinical stage and tumor expression of estrogen (ER), progesterone (PgR) and human epidermal growth factor receptor-2 (HER-2) receptors were considered in this evaluation. The results demonstrated that CXCL8, CXCL10 and CXCL16 showed a significant increased median in BC and BBL patients compared to control (CXCL8: 47.3 and 25.7 vs. 15.0; CXCL10: 37.6 and 30.7 vs. 13.1; CXCL16; 27.9 and 25.2 vs. 19.2 pg/ml, respectively). The increased levels of CXCL8 and CXCL16 were more pronounced in triple-negative and HER-2 positive p

Background: Acute coronary syndrome (ACS) is a common disease, and a major determinant of morbidity and mortality in all races. The pleiotropic effects of the receptor activator of nuclear factor-kappa B ligand (RANKL) such as modulation of cell survival, mineralization and inflammation, make it an interesting candidate mediator in the progression and destabilization of atherosclerotic lesions.Objectives: This study was performed to investigate the role of RANKL in the pathogenesis of ACS.Methods: The levels of RANKL were measured by ELISA method in sera of 60 ACS patients, 31 patients with unstable angina (UA) and 29 patients with myocardial infarction (MI) in comparison with 20 apparently healthy controls.Results: Current data indicate

Ceruloplasmin (Cp) is one of the acute phase protein, in this review ,we studied the level of ceruloplasmin with copper (Cu) and iron in 90 patients with coronary heart diseas ( those patients are divided into three groups, whom are stable angina , unstable angina and myocardial infarction compared with 30 healthy volunteers) and the roles of them as diagnostic and prognostic tools.The diagnosis was attend by a clinical examination carried out by the consult medical staff in Ibn AL-Nafis hospital. The result: ceruloplasmin recorded a significantly(p<0.05)higher level in all patient groups compared with the control, so this result supports the hypothesis that a high serum ceruloplasmin level is a risk factor for coronary heart di

Academic chemical laboratories (ACL) are considered public places  the employees come in contact with a variety of pollutants. The aim of the current study was to detect heavy metals levels in the indoor air of ACL in two universities in Baghdad city and assess their levels in the academic employees’ scalp hair as biomarkers. Air samples inside ACL were collected to detect Fe, Cd, Zn, Pb and Cu. Scalp hair samples were collected from 40 adult chemical laboratory employees aged 30-60 years, who worked 5 days/week for 6 hours a day. Personal information relating to employees such as age, duration of exposure, smoking habit and sex, was collected as a questionnaire. The results of this study concluded that academic laboratory employ

The present study aimed to shed light on the urine HSP70 concentration of patients with urinary bladder carcinoma UBC and control subjects as new urinary biomarker. The second aim was to associate this protein concentration with UBC stage and grade in patients with UBC. A direct ELISA was used to quantify urine HSP concentrations in 58 patients with urinary bladder carcinoma UBC with different grades (G) and stages (T) all malignant of them was transitional cell carcinoma (TCC) type , 15 from patients with urinary Bladder disorders other than cancer UBD and 15 healthy subjects(control) . Urine concentrations of HSP70 were elevated in patients with UBC compared to those without UBC (healthy and UBD, P< 0.5). There was a high signifi

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of