Stillingwynn1450

Uronychia clapsae sp. n. was discovered in an artificial channel that drains an endorheic area from the "sandy Pampa" into the upper basin of Salado River, Buenos Aires, Argentina. This euplotid measures 56-112 μm × 42-70 μm in vivo, is oval in shape and the buccal field is enormous, occupying ca. 80% of body length. It is characterized by having two macronuclear nodules and one micronucleus; usually 10 anterior and invariably three posterior membranelles; right end of paroral hook-like; buccal cirrus base about 3.5-6.0 μm long; invariably four frontal, two ventral, three left marginal, four transverse, and three caudal cirri; six dorsal kineties, kinety 1 with 15-22 dikinetids. Most Uronychia species were recorded in marine habitats, while this new isolate was found in a slightly saline, inland water body. Taxonomic and nomenclatorial concerns on some species assigned to Uronychia are also discussed.Background and objective The novel Coronavirus also called COVID-19 originated in Wuhan, China in December 2019 and has now spread across the world. It has so far infected around 1.8 million people and claimed approximately 114,698 lives overall. As the number of cases are rapidly increasing, most of the countries are facing shortage of testing kits and resources. The limited quantity of testing kits and increasing number of daily cases encouraged us to come up with a Deep Learning model that can aid radiologists and clinicians in detecting COVID-19 cases using chest X-rays. Methods In this study, we propose CoroNet, a Deep Convolutional Neural Network model to automatically detect COVID-19 infection from chest X-ray images. The proposed model is based on Xception architecture pre-trained on ImageNet dataset and trained end-to-end on a dataset prepared by collecting COVID-19 and other chest pneumonia X-ray images from two different publically available databases. Results CoroNet has been trained and tested on the prepared dataset and the experimental results show that our proposed model achieved an overall accuracy of 89.6%, and more importantly the precision and recall rate for COVID-19 cases are 93% and 98.2% for 4-class cases (COVID vs Pneumonia bacterial vs pneumonia viral vs normal). For 3-class classification (COVID vs Pneumonia vs normal), the proposed model produced a classification accuracy of 95%. The preliminary results of this study look promising which can be further improved as more training data becomes available. Conclusion CoroNet achieved promising results on a small prepared dataset which indicates that given more data, the proposed model can achieve better results with minimum pre-processing of data. Overall, the proposed model substantially advances the current radiology based methodology and during COVID-19 pandemic, it can be very helpful tool for clinical practitioners and radiologists to aid them in diagnosis, quantification and follow-up of COVID-19 cases.The C-X-C chemokine receptor type 4 (CXCR4) is a potential therapeutic target for HIV infection, metastatic cancer, and inflammatory autoimmune diseases. In this study, we screened the ZINC chemical database for novel CXCR4 modulators through a series of in silico guided processes. After evaluating the screened compounds for their binding affinities to CXCR4 and inhibitory activities against the chemoattractant CXCL12, we identified a hit compound (ZINC 72372983) showing 100 nM affinity and 69% chemotaxis inhibition at the same concentration (100 nM). To increase the potency of our hit compound, we explored the protein-ligand interactions at an atomic level using molecular dynamics simulation which enabled us to design and synthesize a novel compound (Z7R) with nanomolar affinity (IC50 = 1.25 nM) and improved chemotaxis inhibition (78.5%). Z7R displays promising anti-inflammatory activity (50%) in a mouse edema model by blocking CXCR4-expressed leukocytes, being supported by our immunohistochemistry study.NETosis, being an alternative form of cell death is the creation of web-like chromatin decondensates by suitably primed neutrophils as a response to stimulus aimed at containing and eliminating the same. In certain situations, it causes more harm than benefit in the form of bystander damage directly or via activation of autoimmune mechanisms. Such pathophysiology finds evidence in both Periodontal disease and COVID-19. Ruboxistaurin Coupled with impaired removal, NETs have been implicated in both these disease forms to promote a state of inflammation and be a source of constant harm to the tissues involved. This potentially forms groundwork to implicate Periodontal disease as predisposing towards adverse COVID-19 related outcomes.Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 19 (COVID-19), was declared pandemic by the World Health Organization in March 2020. SARS-CoV-2 binds its host cell receptor, angiotensin-converting enzyme 2 (ACE2), through the viral spike (S) protein. The mortality related to severe acute respiratory distress syndrome (ARDS) and multi-organ failure in COVID-19 patients has been suggested to be connected with cytokine storm syndrome (CSS), an excessive immune response that severely damages healthy lung tissue. In addition, cardiac symptoms, including fulminant myocarditis, are frequent in patients in a severe state of illness. Diacerein (DAR) is an anthraquinone derivative drug whose active metabolite is rhein. Different studies have shown that this compound inhibits the IL-1, IL-2, IL-6, IL-8, IL-12, IL-18, TNF-α, NF-κB and NALP3 inflammasome pathways. The antiviral activity of rhein has also been documented. This metabolite prevents hepatitis B virus (HBV) replication and influenza A virus (IAV) adsorption and replication through mechanisms involving regulation of oxidative stress and alterations of the TLR4, Akt, MAPK, and NF-κB signalling pathways. Importantly, rhein inhibits the interaction between the SARS-CoV S protein and ACE2 in a dose-dependent manner, suggesting rhein as a potential therapeutic agent for the treatment of SARS-CoV infection. Based on these findings, we hypothesize that DAR is a multi-target drug useful for COVID-19 treatment. This anthraquinone may control hyperinflammatory conditions by multi-faceted cytokine inhibition and by reducing viral infection.