Transcriptional profile and serological studies of the European sea bass immune response against betanodavirus infections

European sea bass is highly affected by outbreaks of viral nervous necrosis disease, provoked by the nervous necrosis virus (NNV). This virus displays a positive-sense RNA genome composed of two segments, RNA1, encoding the viral polymerase; and RNA2, encoding the capsid protein. Two genotypes of NNV have been detected in sea bass, although showing different virulence: RGNNV is highly virulent, whereas SJNNV replicates in sea bass brain without causing clinical signs. In the present work, the comparative analysis of the European sea bass immune response against both genotypes has been performed. The immune response has been evaluated in brain and head kidney of infected sea bass by relative real-time PCR of genes involved in the type I interferon system, and genes related to inflammatory and adaptive responses. In addition, a serological study, consisting of the ELISA quantification of IgM in sera, was also performed. The transcription analyses point out the importance of IFN system to control betanodavirus infections. The results obtained showed a strong induction of ifn-I, mxA, isg15 and isg12 in both organs analysed, especially in response to RGNNV. However, the response was quicker in head kidney of SJNNV inoculated sea bass, suggesting that this genotype induces a more rapid systemic response. Regarding the inflammatory response, RGNNV triggered a strong transcription of proinflammatory genes in brain, which provides evidences about the importance of the inflammatory process in NNV infection. Thus, the massive inflammatory process may be responsible for the eventual damage in nervous tissues, which would lead to fish dead. Finally, the high values of tr-g and mhc-b mRNA recorded in brain and the high IgM titer in sera, which was higher in SJNNV-inoculated fish, suggest that the adaptive response constitutes another important factor in the sea bass immune response against betanodaviruses, both at systemic and at local level.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. This study has been supported by the project AGL2017-84644-R (MINECO/ AEI/FEDER, UE). P. Moreno was supported by a fellowship from Ministerio de Educacio n, Cultura y Deporte (FPU12/00265, Spanish Government)

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Outsourcing

Seminario: Estudio y aplicación de los impuestos en Méxic