Project description:We used single-cell sequencing data and imaging to investigate Eukaryotic plankton from environmental marine samples collected from Coogee, NSW, Australia.
2024-08-18 | GSE274796 | GEO
Project description:Epidemiology of respiratory syncytial virus circulating in Lyon,
Project description:Diagnosis of acute respiratory viral infection is currently based on clinical symptoms and pathogen detection. Use of host peripheral blood gene expression data to classify individuals with viral respiratory infection represents a novel means of infection diagnosis. We used microarrays to capture peripheral blood gene expression at baseline and time of peak symptoms in healthy volunteers infected intranasally with influenza A H3N2, respiratory syncytial virus or rhinovirus. We determined groups of coexpressed genes that accurately classified symptomatic versus asymptomatic individuals. We experimentally inoculated healthy volunteers with intranasal influenza, respiratory syncytial virus or rhinovirus. Symptoms were documented and peripheral blood samples drawn into PAXgene tubes for RNA isolation.
Project description:This series includes a 32-array training dataset used to evaluate E-Predict normalization and similarity metric parameters as well as 13 microarrays used as examples in (Urisman, et. al 2005). Training data set includes 15 independent HeLa RNAhybridizations (microarrays 1-15), 10 independent nasal lavage samples positive for Respiratory Syncytial virus (microarrays 16-25), and 7 independent nasal lavage samples positive for Influenza A virus (microarrays 26-32). Examples iclude a serum sample positive for Hepatitis B virus (microarray 33), a nasal lavage sample positive for both Influenza A virus and Respiratory Syncytial virus (microarray 34), and culture samples of 11 distinct Human Rhinovirus serotypes (microarrays 35-45). Keywords = virus detection, E-Predict, species identification, metagenomics
Project description:Transcriptional responses in lungs of mice infected with Respiratory Syncytial Virus (RSV) were compared to a control and mock infections
Project description:Modelling combined virotherapy and immunotherapy:strengthening the antitumour immune response mediated byIL-12 and GM-CSF expression
Adrianne L. Jennera, Chae-Ok Yunb, Arum Yoonb, Adelle C. F. Costercand Peter S. Kimaa
School of Mathematics and Statistics, University of Sydney, Sydney, Australia;bDepartment ofBioengineering, Hanyang University, Seoul, Korea;cSchool of Mathematics and Statistics, University of NewSouth Wales, Sydney, Australia
ABSTRACT
Combined virotherapy and immunotherapy has been emergingas a promising and effective cancer treatment for some time.Intratumoural injections of an oncolytic virus instigate an immunereaction in the host, resulting in an influx of immune cells tothe tumour site. Through combining an oncolytic viral vector withimmunostimulatory cytokines an additional antitumour immuneresponse can be initiated, whereby immune cells induce apoptosisin both uninfected and virus infected tumour cells. We developa mathematical model to reproduce the experimental results fortumour growth under treatment with an oncolytic adenovirus co-expressing the immunostimulatory cytokines interleukin 12 (IL-12)and granulocyte-monocyte colony stimulating factor (GM-CSF). Byexploring heterogeneity in the immune cell stimulation by thetreatment, we find a subset of the parameter space for the immunecell induced apoptosis rate, in which the treatment will be lesseffective in a short time period. Therefore, we believe the bivariatenature of treatment outcome, whereby tumours are either completelyeradicated or grow unbounded, can be explained by heterogeneity inthis immune characteristic. Furthermore, the model highlights theapparent presence of negative feedback in the helper T cell and APCstimulation dynamics, when IL-12 and GM-CSF are co-expressed asopposed to individually expressed by the viral vector.