Selenium is naturally present in the human body, animals, and plants, and is one of the important elements in their growth and maintenance. Recently, the nanoform of selenium has attracted attention due to its low toxicity and a high degree of adsorption compared to its organic and inorganic forms. The current study aimed to examine the effect of Cress leaves (Lepidium sativum L.) extract in combination with selenium nanoparticles in alleviating polycystic ovary syndrome in letrozole-induced PCOS in adult female rats. Nonthermal or cold plasma was used in the synthesis of selenium nanoparticles. Subsequently, the produced nanoparticles were identified, the 30 rats were divided into 6 equal groups, the first group was healthy (negative contr

Background: Cigarette smoking is an important risk factor that has a clear strong association with the prevalence and severity of chronic periodontitis (CP). Salivary biochemical parameters may be affected by both smoking and CP together. Materials and methods: Eighty systematically healthy male patients were included in this study. They were grouped based on their periodontal and smoking status. Unstimulated whole saliva (UWS) was collected from all subject. Salivary flow rate (FR) was measured during sample collection. Parameters such as salivary pH, total protein (TP), albumin (Alb), total fucose (TF), protein bound fucose (PBF) and C-reactive protein (CRP) were estimated. Results: Salivary flow rate was not altered regarding to smoking

Learning Disabilities are described as a hidden and puzzling disability. Children with these difficulties have the potential to hide weaknesses in their performance because they are a homogenous group of disorders that consist of obvious difficulties in acquiring and using reading, writing, Mathematical inference. Thus, the research aims to identify the disabilities of academic learning in (reading, writing, mathematics), identify the problems of behavior (general, motor, social). Identify the relationship among behaviour problems. The research also aims to identify the counseling needs to reduce the behavioral problems. The researcher adopted the analytical descriptive method by preparing two main tools for measuring learning disabiliti

     This work is devoted to define new generalized gamma and beta functions involving the recently suggested seven-parameter Mittag-Leffler function, followed by a review of all related special cases. In addition, necessary investigations are affirmed for the new generalized beta function, including, Mellin transform, differential formulas, integral representations, and essential summation relations. Furthermore, crucial statistical application has been realized for the new generalized beta function.  

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

ABSTRACT: Protein isolate was achieved from local peeled non soaked pumpkins seeds by using petroleum ether with protein percentage of 53.15%. Protein isolate was used in manufacturing meat burger with two substitution10 and 20%. The shrinkage percentage for burger diameter was decreased from 25.5 to 16.6%, the sample with 10% substitution was distinguished in water holding capacity (WHC) which was 54.52%. Sensitive evaluation for these samples showed that the burger with 10% substitution was similar to the control.

Background: Age progression is regarded as a critical risk factor in morbidity and mortality because of a weakened immune system. Although various studies have dealt with electrolyte imbalance in COVID-19 patients, the outcomes of these studies were partially understood. Objective: The current study aims to determine some biochemical parameters in old Iraqi COVID-19 patients and highlight the outcomes according to the aging role in the development of COVID-19 by suggesting new mechanisms. Materials and methods: forty COVID-19 patients were enrolled in the current study and divided into two groups: Gm includes (20) men, and Gf includes  (20) women. The parameters (Na+, K+, Cl-, LDH, and Hb ) were determined in sera of patients and c

Papillary thyroid carcinoma (PTC) represents the most prevalent kind of thyroid gland cancer, making up around 80% of all occurrences of thyroid cancer. Evidence shows that Syndecan-1 (SDC-1) expression is lost in a number of benign and malignant epithelial neoplasms, although its expression profile in thyroid gland neoplasms is yet unknown. Therefore, the aim of this study was to assess SDC-1 expression in papillary thyroid carcinoma patients, as well as the relationship between age and gender and SDC-1 expression. To undertake a detailed investigation of SDC-1 in normal and malignant tissues, tissue sections were used to examine SDC-1 expression in 70 tissue samples, 50 distinct PTC (6 males and 44 females) and 20 normal tissue ty

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep