solation of candida spp. From cancer patients who suffered oral candidiasis due to immunodeficiency

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

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

<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

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

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

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

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