Background: Rhinosinusitis is an inflammatory disorder that refers to inflammation of the nose and paranasal sinuses. Recent studies show that serum IL-33, periostin, ARGE and sST2 had the role in the pathogenesis of chronic rhinosinusitis as an easy, non-invasive and readily available (biomarker) for diagnosis of chronic rhinosinusitis. We tested for correlations of IL-33, periostin, ARGE and sST2 between acute and chronic rhinosinusitis in compare to healthy people. This study aimed to Measure serum levels of periostin, IL-33, sST2, and ARGE biomarkers in patients ARS and CRS. Materials and Methods: We collected serum of 30 patients with acute rhinosinusitis, 30 with chronic rhinosinusitis, and 30 controls to examine serum levels of IL-3

Diabetes mellitus type 2 (T2DM) is a chronic and progressive condition, which affects people all around the world. The risk of complications increases with age if the disease is not managed properly. Diabetic neuropathy is caused by excessive blood glucose and lipid levels, resulting in nerve damage. Apelin is a peptide hormone that is found in different human organs, including the central nervous system and adipose tissue. The aim of this study is to estimate Apelin levels in diabetes type 2 and Diabetic peripheral Neuropathy (DPN) Iraqi patients and show the extent of peripheral nerve damage. The current study included 120 participants: 40 patients with Diabetes Mellitus, 40 patients with Diabetic peripheral Neuropathy, and 40 healthy

The main objective of this research is to find out the effect of deviation in the aggregate gradients of asphalt mixtures from the Job Mix Formula (JMF) on the general mixture performance. Three road layers were worked on (wearing layer, binder layer, and base layer) and statistical analysis was performed for the data of completed projects in Baghdad city, and the sieve that carried the largest number of deviations for each layer was identified. No.8 sieve (2.36mm), No.50 sieve (0.3mm), and 3/8'' sieve (9.5mm) had the largest number of deviations in the wearing layer, the binder layer, and the base layer respectively. After that, a mixture called Mix 1, was made. This mixture was selected from a number of completed mixtures, and it

A reversed-phase HPLC method with fluorescence detection for the determination of the aflatoxins B1, B2, G1 and G2 in 42 animal feeds, comprising corn (16), soya bean meal (8), mixed meal (13), sunflower, wheat, canola, palm kernel, copra meals (1 each) was carried out. The samples were first extracted using acetonitrile:water (9:1), and was further cleaned-up using a multifunctional column. Optimum conditions for the extraction and chromatographic separation were investigated. By adopting an isocratic chromatographic system using a mobile phase comprising acetonitrile:methanol:water (8:27:65, v/v/v), the separation of the four aflatoxins was possible within 30 min. Recoveries for aflatoxins B1, B2, G1 and G2 were 98 ± 0.7%, 95 ± 1.0%, 94

This study aims to find the chemosensitive dysfunction incidence in COVID-19-positive patients and its recovery.

We collected the data from sixty-five patients, all COVID-19 positive, quarantined in-hospital between 5 April 2020 and 17 May 2020, by a questionnaire distributed in the quarantine ward.

Osteoporosis (OP) is a systemic skeletal disease characterized by low bone mineral density and deterioration of bone architecture, resulting in bone strength reduction and increased fracture susceptibility. Estrogen deficiency in post-menopausal women is possibly responsible for the instability between bone formation and resorption, which is managed by specific osteoclastogenic cytokines that may be leading to resorption. This study aims to estimation of the concentrations of interleukins −8, −17, −22, beside to certain parameters in blood serum and explained their roles in the development of osteoporosis pathogenicity in postmenopausal women. Materials and Methods A case-control study included 108 Iraqi postmenopausal women participa

To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip