Ankylosing spondylitis is a complex debilitating disease because its pathogenesis is not clear. This study aims at detecting some pathogenesis factors that lead to induce the disease. Chlamydia pneumoniae is one of these pathogenesis factors which acts as a triggering factor for the disease. The study groups included forty Iraqi Ankylosing spondylitis patients and forty healthy persons as a control group. Immunological and molecular examinations were done to detect Chlamydia. pneumoniae in AS group. The immunological results were performed by Enzyme-Linked Immunosorbent Assay (ELISA) to detect anti-IgG and anti-IgM antibodies of C. pneumoniae revealed that five of forty AS patients' samples (12.5%) were positive for anti-IgG and IgM C. pneumoniae antibodies compared to controls which revealed seronegative. Molecular detection included 16srRNA and HSP-70 genes were to ensure the serological examination for detection of bacteria in the five blood samples which were positive; therefore, these results improved that C. pneumoniae played a role in the pathogenesis of the disease
Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac
Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
... Show MoreOne of the most Interesting natural phenomena is clouds that have a very strong effect on the climate, weather and the earth's energy balance. Also clouds consider the key regulator for the average temperature of the plant. In this research monitoring and studying the cloud cover to know the clouds types and whether they are rainy or not rainy using visible and infrared satellite images. In order to interpret and know the types of the clouds visually without using any techniques, by comparing between the brightness and the shape of clouds in the same area for both the visible and infrared satellite images, where the differences in the contrasts of visible image are the albedo differences, while in the infrared images is the temperature d
... Show MoreDetection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with
... Show MoreClinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b
Background/Aim: Knee osteoarthritis is a frequently crippling chronic condition. Numerous pharmacological medications have been successfully utilised to treat knee osteoarthritis. This research aimed to compare the efficiency of metformin and serratiopeptidase in treating and preventing osteoarthritis development via distinct mechanisms. Methods: Between 1 January and 30 May 2019, a randomised-clinical-trial was done at Al-Kindy Hospital on 80 osteoarthritis patients, divided in two groups. Group I was given metformin 850 mg orally, whereas Group II was given serratiopeptidase 20 mg and metformin 850 mg orally. Parameters in these groups were compared with forty healthy normal controls. Results: Following treatment, patients in Grou
... Show MoreDetermination of the level of adipokines (obestatin, vaspin, tumor necrosis factor-? and interleukin-6)in hypo-and hyperthyroid patients from Educational Baghdad Hospital in Baghdad City was investigated. Fifty patients with hypothyroidism and Fifty patients with hyperthyroidism were selected. A control group of thirty euthyroid persons was included. Blood was collected by vein puncture and serum was separated and stored at –20C. Adipokines (obestatin, vaspin, tumor necrosis factor-? and interleukin-6) were estimated using ELISA method. The findings show a significant (p<0.05) increase in obestatin level in hypothyroid patients, while there is no significant difference in hyperthyroid patientsas compared with the euthyroid subjects.
... Show MoreDuring recent years, there has been an increasing interest in the investigation of the cytokines roles in pathogenesis of cancer, thus the study aimed at evaluating the level of tumor necrosis factor-alpha(TNF-?) in sera of Iraqi multiple myeloma (MM) patients. Beta 2-microglobulion (?2-m) was assessed to determine if there was any association between this cytokine and the level of ?2- m, as the latter is related to the stage of the disease. In addition, the age and gender were also taken into consideration. Furthermore, we investigated the relationship between IgG and TNF-? in sera of patients. 49 Iraqi patients (27 males and 22 females).The patients were also divided into two groups: the first group included (17) patients who were
... Show MoreThree hundred and fifty five patients with hepatitis were investigated in this study all cases gave negative result with HBs Ag , IgM-anti HCV , IgM-anti HEV, IgM-anti HDV and anti-HIV tests . The frequency of IgM-anti HAV was 113 and the percentage was 32 % in all ages but when these patients divided into five groups dependent on ages. The highest percentage of IgM-anti HAV was (45%) in age <10 and the percentage declined with age increase till to 9% in age >41 year.
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Background: The overproduction of thyroid hormones is known as hyperthyroidism. Increased susceptibility to caries and periodontal disease are two potential oral symptoms. The interleukin-6 (IL-6) was observed to significantly increased in the hyperthyroid group. According to multiple research, IL-6 dysregulation has been linked to a number of oral disorders, including periodontal diseases. The study aimed to evaluate periodontal health status in relation to IL6 among hyperthyroidism patients. Subjects and Methods: The sample was composed of 90 female patients aged 25-45 years attending endocrine disorder |