Acute Respiratory Distress Syndrome (ARDS) causes up to 40% mortality in humans and is difficult to treat. ARDS is also one of the major triggers of mortality associated with coronavirus-induced disease (COVID-19). We used a mouse model of ARDS induced by Staphylococcal enterotoxin B (SEB), which triggers 100% mortality, to investigate the mechanisms through which Δ9-tetrahydrocannabinol (THC) attenuates ARDS. SEB was used to trigger ARDS in C3H mice. These mice were treated with THC and analyzed for survival, ARDS, cytokine storm, and metabolome. Additionally, cells isolated from the lungs were used to perform single-cell RNA sequencing and transcriptome analysis. A database analysis of human COVID-19 patients was also performed to compare the signaling pathways with SEB-mediated ARDS. The treatment of SEB-mediated ARDS mice with THC led to a 100% survival, decreased lung inflammation, and the suppression of cytokine storm. This was associated with immune cell apoptosis involving the mitochondrial pathway, as suggested by single-cell RNA sequencing. A transcriptomic analysis of immune cells from the lungs revealed an increase in mitochondrial respiratory chain enzymes following THC treatment. In addition, metabolomic analysis revealed elevated serum concentrations of amino acids, lysine, n-acetyl methionine, carnitine, and propionyl L-carnitine in THC-treated mice. THC caused the downregulation of miR-185, which correlated with an increase in the pro-apoptotic gene targets. Interestingly, the gene expression datasets from the bronchoalveolar lavage fluid (BALF) of human COVID-19 patients showed some similarities between cytokine and apoptotic genes with SEB-induced ARDS. Collectively, this study suggests that the activation of cannabinoid receptors may serve as a therapeutic modality to treat ARDS associated with COVID-19.
The research deals with solar energy as one of the sources of renewable energies available in Iraq, which can be utilized. The research aims to identify the design pillars of the use of solar energy in street furniture and its relationship to formal variables. The research limits included street furniture manufactured by JCDecaux in Boston during the period 2015-2016, and included the theoretical framework which consists of two sections: solar energy (its beginnings and uses), and solar energy and its uses in Street furniture design.
As far as the research procedures and methodology are concerned, it adopted the descriptive approach in describing and analyzing the sample models in addition to describing and analyzing the sample i
... Show MoreThe study aimed to prepare psychological measures of intellectual emptiness and mental distraction on university students. The two researchers used the descriptive approach in the two methods of surveying and correlational relations to suit the nature of the research, where the study sample consisted of (101) students of physical education and sports sciences. The phrase- Intellectual emptiness(35) and (34) is a phrase for mental distraction and presented it to experts in psychology, testing and measurement, and the statistical bag for social sciences (spss) was used, and the results of the research showed that intellectual emptiness has a moral relationship with straying among some students of the College of Physical Education
... Show MoreThe study aims to identify the metamemory and perceptual speed among College students, the correlation between metamemory and perceptual speed among College students, and to which extend does metamemory contribute to perceptual speed among College students. The sample consisted of group of students were selected randomly by the researcher from five-different disciplines at the college of education for pure sciences. To collect study data, the researcher utilized two scales: perceptual speed scale that has translated to Arabic language by (Al-Shraqawi, Al- Shaikh, and Nadia Abed Al-Salam (1993). The second scale is metamemory scale (2002) which has translated to Arabic by Abu Ghazal (2007). The results revealed that college students have
... Show MoreSevere periodontitis is ranked as the sixth most prevalent disease affecting humankind, with an estimated 740 million people affected worldwide. The diagnosis of periodontal diseases mainly relies upon assessment of conventional clinical parameters. However, these parameters reflect past, rather than current, clinical status or future disease progression and, likely, outcome of periodontal treatment. Specific and sensitive biomarkers for periodontal diseases have been examined widely to address these issues and some biomarkers have been translated as point-of-care (PoC) tests. The aim of this review was to provide an update on PoC tests for use in the diagnosis and management of periodontal diseases. Among the PoC tests developed so
... Show MoreIsolation of fungi was performed from February to July, 2019. One hundred clinical specimens were collected from King Abdullah Hospital (KAH) Bisha, Saudi Arabia. Samples were collected from twenty patients of different ages (30 - 70 years old) ten males and ten females. The samples were collected from patients with the two types of diabetics. Specimens included blood, hair, nail, oral swabs and skin. Specimens were inoculated on Sabourauds Dextrose agar containing chloramphenicol. Thirteen fungal species were isolated and identified. The isolated species were: Aspergillus flavus, A. niger, A. terrus, A. nidulans, A. fumigatus, Candida albicans, C. krusei, C. parapsilosis, C. Tropicalis, Curvularia lunata, Fusarium solani, Penicill
... Show MoreIn this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For
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