Evaluation of serum levels of Proinflammatory Cytokines IL-8, IL-17, and IL-22 in Helicobacter pylori infection and their association with the degree of gastritis histopathology in a sample of Iraqi patients

Gastritis can be defined as histological inflammation of the gastric mucosa. It can be classified according to the time course of the disease as acute or chronic, histological findings, anatomic location, and pathological mechanisms. The objective of this study was to evaluation of serum levels of the proinflammatory cytokines IL-8, IL-17 and IL-22 in Helicobacter pylori infection and their association with the degree of gastritis histopathology in a sample of Iraqi patients. The case-control prospective study consists of 60 patients who attended the Gastrointestinal Tract Center at Al-Kindy Teaching Hospital during the period from December 2019 to April 2020. In addition, the control group included 60 apparently healthy individuals. Biopsies from the gastric antrum and/or body mucosa were used to assess the severity of chronic inflammation, neutrophil infiltration, atrophy, intestinal metaplasia. Serum samples were obtained to determine H. pylori infection, circulating interleukin (IL)-8, IL-17, and IL-22. Results showed that the Patients’ ages with gastritis ranged from 18-75 years. The body mass index revealed that 33.33% of the patients were obese and 35% of them were overweight. Most of the patients with active chronic gastritis and superficial chronic gastritis had positive titers for anti-H. pylori IgG antibody (167.89 ± 3.18 IU/ml) and (150.74± 1.45 IU/ml) respectively, which was significantly different from the control group (4.36 ± 0.29 IU/ml) (P=0.0001). Histopathological analysis showed that all subjects experienced chronic inflammation, while neutrophil infiltration was found 36.66% and there was significant association between serum levels of IL-8, IL-17, and IL-22 with a degree of chronic inflammation and neutrophils infiltration. In conclusion, the most common cause of gastritis was H. pylori with histopathological lesions, showing neutrophils infiltration and chronic gastric mucosal inflammation associated with increased levels of IL-8, IL-17, and IL-22 in serum

Comparative study of DC/AC inverter control techniques for three phase grid connected PV system

The goal of this project is to develop and analyze a three-phase grid-connected photovoltaic (PV) system with a 250KW power capacity with expandable property. The PI, Slide, and MPC methodologies are used to test three distinct inverter current control techniques. The dynamic performances of the three inverter control techniques are virtually comparable under grid connected working conditions, although the dynamic performances of the traditional PI control technique are slightly better and smoother than the other two inverter control techniques. The unity power factor criterion was reached by all techniques. The output power levels obtained using the sliding mode inverter control method are higher than those obtained using the PI and MPC methods. MPC's DC link voltage readings are also consistent and match the intended voltage levels

An optimized skin texture model using gray-level co-occurrence matrix

Texture analysis is devised to address the weakness of color-based image segmentation models by considering the statistical and spatial relations among the group of neighbor pixels in the image instead of relying on color information of individual pixels solely. Due to decent performance of the gray-level co-occurrence matrix (GLCM) in texture analysis of natural objects, this study employs this technique to analyze the human skin texture characteristics. The main goal of this study is to investigate the impact of major GLCM parameters including quantization level, displacement magnitudes, displacement direction and GLCM features on skin segmentation and classification performance. Each of these parameters has been assessed and optimized using an exhaustive supervised search from a fairly large initial feature space. Three supervised classifiers including Random Forest, Support Vector Machine and Multilayer Perceptron have been employed to evaluate the performance of the feature space subsets. Evaluation results using Edith Cowan University (ECU) dataset showed that the proposed texture-assisted skin detection model outperformed pixelwise skin detection by significant margin. The proposed method generates an F-score of 91.98, which is satisfactory, considering the challenging scenario in ECU dataset. Comparison of the proposed texture-assisted skin detection model with some state-of-the-art skin detection models indicates high accuracy and F-score of the proposed model. The findings of this study can be used in various disciplines, such as face recognition, skin disorder and lesion recognition, and nudity detection

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population