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Unfortunately, the speed at which the COVID-19 pandemic has emerged in Canada may prevent healthcare sectors in both urban and rural settings to have an opportunity for healthcare teams to participate in just-in-time in situ simulation-based learning prior to a potential surge of COVID-19 patients. Our coordinated approach and infrastructure have enabled organizational learnings and the ability to theme and categorize a mass volume of simulation outcome data, primarily from acute care settings to help all sectors further anticipate and plan. The goal of this paper is to share the unique features and advantages of using a centralized provincial simulation response team, preparedness using learning and systems integration methods, and to share the highest risk and highest frequency outcomes from analyzing a mass volume of COVID-19 simulation data across the largest health authority in Canada.Leishmaniases are neglected diseases caused by infection with Leishmania parasites and there are currently no prophylactic vaccines. In this study, we designed in silico a synthetic recombinant vaccine against visceral leishmaniasis (VL) called ChimeraT, which contains specific T-cell epitopes from Leishmania Prohibitin, Eukaryotic Initiation Factor 5a and the hypothetical LiHyp1 and LiHyp2 proteins. Subcutaneous delivery of ChimeraT plus saponin stimulated a Th1 cell-mediated immune response and protected mice against L. infantum infection, significantly reducing the parasite load in distinct organs. ChimeraT/saponin vaccine stimulated significantly higher levels of IFN-γ, IL-12, and GM-CSF cytokines by both murine CD4+ and CD8+ T cells, with correspondingly low levels of IL-4 and IL-10. Induced antibodies were predominantly IgG2a isotype and homologous antigen-stimulated spleen cells produced significant nitrite as a proxy for nitric oxide. ChimeraT also induced lymphoproliferative responses in peripheral blood mononuclear cells from VL patients after treatment and healthy subjects, as well as higher IFN-γ and lower IL-10 secretion into cell supernatants. Thus, ChimeraT associated with a Th1 adjuvant could be considered as a potential vaccine candidate to protect against human disease.The significance of the microbiota-gut-brain axis has been increasingly recognized as a major modulator of autoimmunity. Here, we aim to characterize the gut microbiota of a large cohort of treatment-naïve anti-N-methyl-d-aspartate receptor (anti-NMDAR) encephalitis patients relative to that of healthy controls (HCs). Relative to HCs, anti-NMDAR encephalitis patients had a decreased microbiome alpha-diversity index, marked disturbances of gut microbial composition and intestinal permeability damage. Disturbed microbiota in anti-NMDAR encephalitis patients might be linked with different clinical characteristics. Imputed KEGG analysis revealed perturbations of functional modules in the gut microbiomes of anti-NMDAR encephalitis. Compared to HCs, microbiota-depleted mice receiving fecal microbiota transplantation (FMT) from anti-NMDAR encephalitis patients had hypersensitivity and cognitive impairment. Furthermore, anti-NMDAR encephalitis FMT mice showed altered T cells in the spleen and small intestine lamina propria with an increased Th17 cells. Overall, this study first suggests that the anti-NMDAR encephalitis microbiome itself can influence neurologic, Th17 response and behavioral function. The gut microbiota is a potential therapeutic target for anti-NMDAR encephalitis.Mechanisms of tissue damage in Huntington's disease involve excitotoxicity, mitochondrial damage, and neuroinflammation, including microglia activation. In the present study, we investigate the role of pyroptosis process in the striatal neurons of the R6/2 mouse model of Huntington's disease. Transgenic mice were sacrificed at 4 and 13 weeks of age. PF-07104091 manufacturer After sacrifice, histological and immunohistochemical studies were performed. We found that NLRP3 and Caspase-1 were intensely expressed in 13-week-old R6/2 mice. Moreover, NLRP3 expression levels were higher in striatal spiny projection neurons and in parvalbumin interneurons, which are prone to degenerate in HD.Due to the continued high incidence and mortality rate worldwide, there is still a need to develop new strategies for the prevention, diagnosis and treatment of cardiovascular diseases (CVDs). Proper cardiovascular function depends on the coordinated interplay and communication between cardiomyocytes and noncardiomyocytes. Extracellular vesicles (EVs) are enclosed in a lipid bilayer and represent a significant mechanism for intracellular communication. By containing and transporting various bioactive molecules, such as micro-ribonucleic acids (miRs) and proteins, to target cells, EVs impart favourable, neutral or detrimental effects on recipient cells, such as modulating gene expression, influencing cell phenotype, affecting molecular pathways and mediating biological behaviours. EVs can be released by cardiovascular system-related cells, such as cardiomyocytes, endotheliocytes, fibroblasts, platelets, smooth muscle cells, leucocytes, monocytes and macrophages. EVs containing miRs and proteins regulate a multitude of diverse functions in target cells, maintaining cardiovascular balance and health or inducing pathological changes in CVDs. On the one hand, miRs and proteins transferred by EVs play biological roles in maintaining normal cardiac structure and function under physiological conditions. On the other hand, EVs change the composition of their miR and protein cargoes under pathological conditions, which gives rise to the development of CVDs. Therefore, EVs hold tremendous potential to prevent, diagnose and treat CVDs. The current article reviews the specific functions of EVs in different CVDs.

Advanced developments in diagnostic radiology have provided a rapid increase in the number of radiological investigations worldwide. Recently, Artificial Intelligence (AI) has been applied in diagnostic radiology. The purpose of developing such applications is to clinically validate and make them feasible for the current practice of diagnostic radiology, in which there is less time for diagnosis.

To assess radiologists' knowledge about AI's role and establish a baseline to help in providing educational activities on AI in diagnostic radiology in Saudi Arabia.

An online questionnaire was designed using QuestionPro software. The study was conducted in large hospitals located in different regions in Saudi Arabia. A total of 93 participants completed the questionnaire, of which 32 (34%) were trainee radiologists from year 1 to year 4 (R1-R4) of the residency programme, 33 (36%) were radiologists and fellows, and 28 (30%) were consultants.

The responses to the question related to the use of AI on a daily basis illustrated that 76 (82%) of the participants were not using any AI software at all during daily interpretation of diagnostic images.