Cannonjohansson6474

COVENT-Tester (COVID-19 VENTilator Tester) is a low-cost and open source ventilator tester developed to calibrate the output of medical ventilators, including tidal volume, inspiratory pressure, and oxygen concentration. Currently, there are several open-source ventilator testers, however, existing open-source ventilator testers are unable to measure oxygen concentration. Conversely, commercial ventilator testers with the capacity to measure tidal volume, inspiratory pressure, and oxygen concentration, are very costly. The COVENT-Tester was therefore designed to be low-cost, by using Commercial Off-The-Shelf (COTS) components, to assist the open source community for rapidly manufactured pandemic ventilators. In addition, the COVENT-Tester measurement's validation results show the tester has good accuracy.The coronavirus disease 2019 (COVID-19) is an ongoing pandemic caused by an RNA virus termed as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). SARS-CoV-2 possesses an almost 30kbp long genome. The genome contains open-reading frame 1ab (ORF1ab) gene, the largest one of SARS-CoV-2, encoding polyprotein PP1ab and PP1a responsible for viral transcription and replication. Several vaccines have already been approved by the respective authorities over the world to develop herd immunity among the population. In consonance with this effort, RNA interference (RNAi) technology holds the possibility to strengthen the fight against this virus. Here, we have implemented a computational approach to predict potential short interfering RNAs including small interfering RNAs (siRNAs) and microRNAs (miRNAs), which are presumed to be intrinsically active against SARS-CoV-2. In doing so, we have screened miRNA library and siRNA library targeting the ORF1ab gene. We predicted the potential miRNA and siRNA candidate molecules utilizing an array of bioinformatic tools. CDK assay By extending the analysis, out of 24 potential pre-miRNA hairpins and 131 siRNAs, 12 human miRNA and 10 siRNA molecules were sorted as potential therapeutic agents against SARS-CoV-2 based on their GC content, melting temperature (Tm), heat capacity (Cp), hybridization and minimal free energy (MFE) of hybridization. This computational study is focused on lessening the extensive time and labor needed in conventional trial and error based wet lab methods and it has the potential to act as a decent base for future researchers to develop a successful RNAi therapeutic.The infectious bronchitis virus (IBV) is still one of the major respiratory viral pathogens of chickens. The IBV infection resulted in a wide range of clinical syndromes in the affected chickens, including respiratory, renal, gonads affections as well as generalized infections. Despite the intensive application of various commercial vaccines against the virus, many outbreaks are still reported in chickens worldwide. Several studies reported the circulation of several strains and genotypes of the IBV in eastern Saudi Arabia. The main goal of the current study was to isolate some of the circulating strains of IBV and assess its ability to reproduce the IBV infections in the challenge birds. Another objective was to monitor the immune status of the infected chickens during the course of this study. To achieve these goals, we used some filed IBV isolates retrieved from an outbreak in a broiler chicken farm in eastern Saudi Arabia in 2014. A total of 220-day-old chickens (110 Ross and 110 native Saudi breed chickens), twenty birds per each group, were used in this study. The chickens in some groups received some IBV vaccines on day one of the experiment, and some are boosted on day 19. All birds were challenged on day 28 of the experiment. Our results showed mild IBV signs in the non-vaccinated control group of chickens; however, the vaccinated chickens did not show any signs of IBV infections. Meanwhile, both the vaccinated and the none- vaccinated birds seroconverted to the IBV as shown by the ELISA results. In conclusion, the response of the IBV infected birds is mainly driven by the vaccination plans they received as a prime-boost regime. Further studies are required for a better understanding of the dynamics of IBV infection in native Saudi chickens.Purpose In sequential imaging studies, there exists rich information from past studies that can be used in prior-image-based reconstruction (PIBR) as a form of improved regularization to yield higher-quality images in subsequent studies. PIBR methods, such as reconstruction of difference (RoD), have demonstrated great improvements in the image quality of subsequent anatomy reconstruction even when CT data are acquired at very low-exposure settings. Approach However, to effectively use information from past studies, two major elements are required (1) registration, usually deformable, must be applied between the current and prior scans. Such registration is greatly complicated by potential ambiguity between patient motion and anatomical change-which is often the target of the followup study. (2) One must select regularization parameters for reliable and robust reconstruction of features. Results We address these two major issues and apply a modified RoD framework to the clinical problem of lung nodule surveillance. Specifically, we develop a modified deformable registration approach that enforces a locally smooth/rigid registration around the change region and extend previous analytic expressions relating reconstructed contrast to the regularization parameter and other system dependencies for reliable representation of image features. We demonstrate the efficacy of this approach using a combination of realistic digital phantoms and clinical projection data. Performance is characterized as a function of the size of the locally smooth registration region of interest as well as x-ray exposure. Conclusions This modified framework is effectively able to separate patient motion and anatomical change to directly highlight anatomical change in lung nodule surveillance.SARS- CoV-2 or novel coronavirus enters in human body through nose and mouth, stays there for a while. Then binds with ACE2 receptor, enters inside cell, multiply there and manifests. Again, Polyvinyl Pyrrolidone or Povidone Iodine (PVP-I) is a strong microbicidal agent having 99.99% virucidal efficacy in its only 0.23% concentration, irrespective of all known viruses, even in SARS- CoV-2 (in vitro). An oro-nasal spray is designed to apply the PVP-I in nose and oral cavity to gain a protective layer or coating over nasal and oral mucosa, so that SARS-CoV-2 can't bind with the ACE-2 receptor and prevent their entry inside. So, it will be effective for prevention of COVID-19. Moreover, as PVP-I has the ability for destruction of SARS-CoV-2, transmission of SARS- CoV-2 from patient will be reduced also. Thus PVP-I oro-nasal spray can act as an effective shield for COVID-19 protection for healthcare workers, for all.

Multisystem inflammatory syndrome in children (MIS-C) is a potentially life-threatening condition occurring 2-6 weeks after Coronavirus disease 2019 (COVID-19) in previously healthy children and adolescents, characterized by clinical and laboratory evidence of multiorgan inflammation. We reported the case of a 6-year-old child presented with acute abdomen and then diagnosed with MIS-C. In addition, to better portray this new entity, we performed a systematic review of MIS-C gastrointestinal features and particularly on those mimicking surgical emergencies.

We described the clinical presentation, the diagnostic approach and the therapeutic outcomes of our MIS-C patient. Parallel to this, we conducted a systematic literature search using Google Scholar, PubMed, EMBASE, Scopus, focusing on gastrointestinal MIS-C.

Our patient was initially assessed by the surgical team due to his query acute abdomen. Following the diagnosis of MIS-C with myocarditis, intravenous methylprednisolone (2 mg/Kg/day) and intravenchildren with query acute abdomen, MIS-C should be promptly ruled out in order to avoid unnecessary surgeries that could worsen the already frail outcome of this new syndrome. Nevertheless, it should be considered that MIS-C might well encompass complications (e.g. appendicitis, segmental intestinal ischemia) which need swift surgical treatment.A 30-year-old woman presented with remitting upper airway infections. Over time she developed mastoiditis resistant to antibiotics, arthritis of her ankle as well as multilocular arthralgias and a livid discoloration of her fingertips. A computed tomography (CT) scan of her chest revealed a cavernous process and c‑ANCA (Anti Neutrophilen Cytoplasmatic Antibody) positivity led to the diagnosis granulomatosis with polyangiitis (formerly called Wegener's). In line with literature reports, rituximab and cortisosteroid therapy quickly induced remission.In response to the coronavirus disease-19 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), global efforts are focused on the development of new therapeutic interventions. For the treatment of COVID-19, selective lung-localizing strategies hold tremendous potential, as SARS-CoV-2 invades the lung via ACE2 receptors and causes severe pneumonia. Similarly, recent reports have shown the association of COVID-19 with decreased 25-hydroxycholesterol (25-HC) and increased cytokine levels. This mechanism, which involves the activation of inflammatory NF-κB- and SREBP2-mediated inflammasome signaling pathways, is believed to play a crucial role in COVID-19 pathogenesis, inducing acute respiratory distress syndrome (ARDS) and sepsis. To resolve those clinical conditions observed in severe SARS-CoV-2 patients, we report 25-HC and didodecyldimethylammonium bromide (DDAB) nanovesicles (25-HC@DDAB) as a COVID-19 drug candidate for the restoration of intracellular cholesterol level and suppression of cytokine storm. Our data demonstrate that 25-HC@DDAB can selectively accumulate the lung tissues and effectively downregulate NF-κB and SREBP2 signaling pathways in COVID-19 patient-derived PBMCs, reducing inflammatory cytokine levels. Altogether, our findings suggest that 25-HC@DDAB is a promising candidate for the treatment of symptoms associated with severe COVID-19 patients, such as decreased cholesterol level and cytokine storm.The coronavirus (COVID-19) is currently the most common contagious disease which is prevalent all over the world. The main challenge of this disease is the primary diagnosis to prevent secondary infections and its spread from one person to another. Therefore, it is essential to use an automatic diagnosis system along with clinical procedures for the rapid diagnosis of COVID-19 to prevent its spread. Artificial intelligence techniques using computed tomography (CT) images of the lungs and chest radiography have the potential to obtain high diagnostic performance for Covid-19 diagnosis. In this study, a fusion of convolutional neural network (CNN), support vector machine (SVM), and Sobel filter is proposed to detect COVID-19 using X-ray images. A new X-ray image dataset was collected and subjected to high pass filter using a Sobel filter to obtain the edges of the images. Then these images are fed to CNN deep learning model followed by SVM classifier with ten-fold cross validation strategy. This method is designed so that it can learn with not many data.