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The Endocannabinoid Anandamide Attenuates Acute Respiratory Distress Syndrome by Downregulating miRNA that Target Inflammatory Pathways
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Acute respiratory distress syndrome (ARDS) is defined as a type of respiratory failure that is caused by a variety of insults such as pneumonia, sepsis, trauma and certain viral infections. In this study, we investigated the effect of an endocannabinoid, anandamide (AEA), on ARDS induced in the mouse byStaphylococcusEnterotoxin B (SEB). Administration of a single intranasal dose of SEB in mice and treated with exogenous AEA at a dose of 40 mg/kg body weight led to the amelioration of ARDS in mice. Clinically, plethysmography results indicated that there was an improvement in lung function after AEA treatment accompanied by a decrease of inflammatory cell infiltrate. There was also a significant decrease in pro-inflammatory cytokines IL-2, TNF-α, and IFN-γ, and immune cells including CD4+T cells, CD8+T cells, Vβ8+T cells, and NK+T cells in the lungs. Concurrently, an increase in anti-inflammatory phenotypes such as CD11b + Gr1+ Myeloid-derived Suppressor Cells (MDSCs), CD4 + FOXP3 + Tregs, and CD4+IL10 + cells was observed in the lungs. Microarray data showed that AEA treatment in ARDS mice significantly altered numerous miRNA including downregulation of miRNA-23a-3p, which caused an upregulation of arginase (ARG1), which encodes for arginase, a marker for MDSCs, as well as TGF-β2, which induces Tregs. AEA also caused down-regulation of miRNA-34a-5p which led to induction of FoxP3, a master regulator of Tregs. Transfection of T cells using miRNA-23a-3p or miRNA-34a-5p mimics and inhibitors confirmed that these miRNAs targeted ARG1, TGFβ2 and FoxP3. In conclusion, the data obtained from this study suggests that endocannabinoids such as AEA can attenuate ARDS induced by SEB by suppressing inflammation through down-regulation of key miRNA that regulate immunosuppressive pathways involving the induction of MDSCs and Tregs.

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Publication Date
Mon Jan 01 2018
Journal Name
Communications In Computer And Information Science
Automatically Recognizing Emotions in Text Using Prediction by Partial Matching (PPM) Text Compression Method
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In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

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Publication Date
Sat Oct 01 2011
Journal Name
Iraqi Journal Of Physics
Effect of annealing on superconducting properties of Bi1.6Pb0.4Sr2Ca2Cu2.2Zn0.8O10 thin films by pulsed laser deposition
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Superconducting thin films of Bi1.6Pb0.4Sr2Ca2Cu2.2Zn0.8O10 system were prepared by depositing the film onto silicon (111) substrate by pulsed laser deposition. Annealing treatment and superconducting properties were investigated by XRD and four probe resistivity measurement. The analysis reveals the evolution of the minor phase of the films 2212 phase to 2223 phase, when the film was annealed at 820 °C. Also the films have superconducting behavior with transition temperature ≥90K.

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Publication Date
Mon Jan 01 2024
Journal Name
Fifth International Conference On Applied Sciences: Icas2023
A modified Mobilenetv2 architecture for fire detection systems in open areas by deep learning
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This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Distinguishing Shapes of Breast Cancer Masses in Ultrasound Images by Using Logistic Regression Model
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The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

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Publication Date
Tue Jan 02 2018
Journal Name
International Journal Of Science And Research
Mathematical Modelling of Zinc Removal from Wastewater by Using Nanofiltration and Reverse Osmosis Membranes
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The present work aimed to study the efficiency of nanofiltration (NF) and reverse osmosis (RO) process for treatment of heavy metals wastewater contains zinc. In this research, the salt of heavy metals were zinc chloride (ZnCl2) used as feed solution.Nanofiltration and reverse osmosis membranes are made from polyamide as spiral wound module. The parameters studied were: operating time (0 – 70 min), feed concentrations for zinc ions (10 – 300 mg/l), operating pressure (1 – 4 bar).The theoretical results showed, flux of water through membrane decline from 19 to 10.85 LMH with time. Flux decrease from 25.84 to 10.88 LMH with the increment of feed concentration. The raise of pressure, the flux increase for NF and RO membranes.The maximum

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Publication Date
Fri Feb 20 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Force decay of orthodontic elastomeric chains by using three different mechanisms simulating canine retraction
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Background: The ideal force-delivery system must: provide optimal tooth moving forces that elicit the desired effects, be comfortable and hygienic for the patient, require minimal operator manipulation and patient cooperation and provide rapid tooth movement with minimal mobility during orthodontic therapy, the elastomeric chains have the greatest potential to fulfill these requirements. Materials and Methods: This in vitro study was designed to determine the effect of three different mechanisms for canine retraction : (6-3 , 6-5-3 and chain loop ) on the load relaxation behavior of three types of elastomeric chains : (maximum clear , maximum silver and extreme silver) from the same company (Ortho Technology company) with two different bran

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Publication Date
Mon Mar 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Microstructure and Some Properties of Aluminum-Silicon Matrix Composites Reinforced by Alumina or Chromia
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In this work, yttrium oxide particles (powder) reinforced AL-Si matrix composites (Y2O3/Al-Si) and Chromium oxide particles reinforced AL-Si matrix composites (Cr2O3/AL-Si) were prepared by direct squeeze casting. The volume percentages of yttrium oxide used are (4, 8.1, 12.1, 16.1 vol %) and the volume percentages of the chromium oxide particles used are (3.1, 6.3, 9.4, 12.5 vol. %). The parameters affecting the preparation of Y2O3/Al-Si and Cr2O3/AL-Si composites by direct squeeze casting process were studied. The molten Al-Si alloy with yttrium oxide particles or with chromium oxide particles was stirred again using an electrical stirrer at speed 500 rpm  and the molten alloy was  poured  into the squeeze die cavity. Th

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Publication Date
Mon Nov 15 2021
Journal Name
Egyptian Journal Of Chemistry
Green Synthesis by Zygophyllum Coccineum Leaves Extract for Preparing ZnO Nanoparticles, and Characteristics Study.
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Publication Date
Fri Dec 01 2023
Journal Name
Baghdad Science Journal
Control Pepper Fusarium Wilting by biocontrol agent Trichoderma harzianum and Chelated Iron Fe-EDDHA
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Sweet pepper (Capsicum annuum L.) is an economically important vegetable crop. Wilt disease caused by Fusarium oxysporum f. sp. capsici is a specific pathogen that affects the pepper. Four isolates of F. oxysporum f. sp. capsici Fo3, Fo6, Fo7 and Fo8 were obtained from diseased pepper plants that were collected from different pepper fields in Baghdad. Fo6 isolate that has high pathogenicity to pepper seeds, Trichoderma harzianum (Th) was tested in vitro against F. oxysporum f. sp. capsici showed a high inhibition rate for the isolate Fo6, the concentration of chelated iron Fe-EDDHA 0.5% reduced the radial growth of Fo6 whi

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Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
Calculating Surface Roughness for a Large Scale SEM Images by Mean of Image Processing
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