Osteoporosis (OP) is a systemic skeletal disorder that is characterized by reduced bone mass and micro-architectural deterioration of bone tissue, with a consequent increase in bone fragility and susceptibility to fracture. The most frequent osteoporotic fractures are fractures of the hip, wrist, and spine. The exact causes of OP are still unknown; several factors contribute to the disorder. Subjects and Methods: This study consists of patient groups, this group (Group A) was composed of 80 postmenopausal women with OP and osteopenia and the patient group was subdivided into two group; First group (GroupA1) was composed of 50 postmenopausal women with OP and the second group (Group A2) composed of (30) Postmenopausal Women with osteopenia. In addition, to control group (20), 5 mL of venous blood sample were collected from each patient and healthy control in the population study, and the blood sample was transferred to a clean gel tube, left at room temperature for at least 30 minutes for clotting, then centrifuged for 5–10 minutes at 3000 rpm. Then, separated and divided into aliquots to obtain the serum, then its kept frozen at -20°C until analysis. The obtained serum was used to measure IL17A, FGF21, CXC12, calcium, and alkaline Phosphatase (ALP). Measurement of IL17A, FGF21 and CXC12 levels were performed by ELISA. The total calcium and serum ALK were measured by spectrophotometric-based method. Results: Serum levels of IL17A, FGF21 and CXC12 are significantly increased in Group A and subgroup (A1 and A2). Serum levels of total calcium and ALP are non-significant in Group A and sub group patients. Significant negative correlation between serum levels of IL17A and T score, FGF21 and T score, CXC12 and T score, IL 17A and Z score, IL17A and Calcium. Conclusions: Serum levels of IL17A, FGF21 and CXC12 is significantly increased in Group A and subgroup patients. Serum levels of total calcium and ALP are non-significant in Group A and sub group patients. Significant negative correlation exists between serum levels of IL17A and T score, FGF21 and T score, CXC12 and T score in Groups A and A1.
In this research, CNRs have been synthesized using pyrolysis of plastic waste(pp) at 1000 ° C for one hour in a closed reactor made from stainless steel, using magnesium oxide (MgO) as a catalyst. The resultant carbon nano rods were purified and characterized using energy dispersive X-ray spectroscopy (EDX), X-ray powder diffraction (XRD). The surface characteristics of carbon rods were observed with the Field emission scanning electron microscopy (FESEM). The carbon was evenly spread and had the highest concentration from SEM-EDX characterization. The results of XRD and FESEM have shown that carbon Nano rods (CNRs) were present in Nano figures, synthesized at 1000 ° C and with pyrolysis temperature 400° C. One of t
... Show MoreThe presence of antibiotic residues such as ciprofloxacin (CIPR) in an aqueous environment is dangerous when their concentrations exceed the allowable. Therefore, eliminating these residues from the wastewater becomes an essential issue to prevent their harm. In this work, the potential of efficient adsorption of ciprofloxacin antibiotics was studied using eco-friendly ZSM-5 nanocrystals‑carbon composite (NZC). An inexpensive effective natural binder made of the sucrose-citric acid mixture was used for preparing NZC. The characterization methods revealed the successful preparation of NZC with a favorable surface area of 103.739 m2/g, and unique morphology and functional groups. Investigating the ability of NZC for adsorbing CIPR antibioti
... Show MoreHypothesis CO2 geological storage (CGS) involves different mechanisms which can store millions of tonnes of CO2 per year in depleted hydrocarbon reservoirs and deep saline aquifers. But their storage capacity is influenced by the presence of different carboxylic compounds in the reservoir. These molecules strongly affect the water wetness of the rock, which has a dramatic impact on storage capacities and containment security. However, precise understanding of how these carboxylic acids influence the rock’s CO2-wettability is lacking. Experiments We thus systematically analysed these relationships as a function of pressure, temperature, storage depth and organic acid concentrations. A particular focus was on identifying organic acid conce
... Show MoreObjectives: The present study aimed to assess the compulsion among health care providers during the pandemic of COVID-19.
Methodology: a descriptive design was used in the present study. This study was conducted from October 10th, 2020 through May 20th, 2021. The study was conducted on a probability (convenient) sample of 248 physicians and nurses who work at Baghdad Teaching hospital in Baghdad city. The instrument was used in this study is the COVID Stress Scale-Arabic version (CSS).
Results: The result of this study showed that 42 % of HCPs had moderate symptoms and 36% of them had mild compulsive symptoms, and
... Show MoreThe objective of this work is to investigate the performance of a conventional three phase induction motor supplied by unbalanced voltages. An effort to study the motor steady state performance under this disturbance is introduced. Using per phase equivalent circuit analysis with the concept of symmetrical components approach, the steady state performance is theoretically calculated. Also, a model for the induction motor with the MATLAB/Simulink SPS tools has been implemented and steady state results were obtained. Both results are compared and show good correlation as well. The simulation model is introduced to support and enhance electrical engineers with a complete understanding for the steady state performance of a fully loaded induc
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show More