RESUMO
The recent outbreak of a novel coronavirus SARS-CoV-2 (also known as 2019-nCoV) threatens global health, given serious cause for concern. SARS-CoV-2 is a human-to-human pathogen that caused fever, severe respiratory disease and pneumonia (known as COVID-19). By press time, more than 70,000 infected people had been confirmed worldwide. SARS-CoV-2 is very similar to the severe acute respiratory syndrome (SARS) coronavirus broke out 17 years ago. However, it has increased transmissibility as compared with the SARS-CoV, e.g. very often infected individuals without any symptoms could still transfer the virus to others. It is thus urgent to develop a rapid, accurate and onsite diagnosis methods in order to effectively identify these early infects, treat them on time and control the disease spreading. Here we developed an isothermal LAMP based method-iLACO (isothermal LAMP based method for COVID-19) to amplify a fragment of the ORF1ab gene using 6 primers. We assured the species-specificity of iLACO by comparing the sequences of 11 related viruses by BLAST (including 7 similar coronaviruses, 2 influenza viruses and 2 normal coronaviruses). The sensitivity is comparable to Taqman based qPCR detection method, detecting synthesized RNA equivalent to 10 copies of 2019-nCoV virus. Reaction time varied from 15-40 minutes, depending on the loading of virus in the collected samples. The accuracy, simplicity and versatility of the new developed method suggests that iLACO assays can be conveniently applied with for 2019-nCoV threat control, even in those cases where specialized molecular biology equipment is not available.
RESUMO
Autoimmune diseases (ADs) arise from an abnormal immune response of the body against substances and tissues normally present in the body. More than a hundred of ADs have been described in the literature so far. Although their etiology remains largely unclear, various types of ADs tend to share more associated genes with other types of ADs than with non-AD types. Here we present GAAD, a gene and AD association database. In GAAD, we collected 44,762 associations between 49 ADs and 4249 genes from public databases and MEDLINE documents. We manually verified the associations to ensure the quality and credibility. We reconstructed and recapitulated the relationships among ADs using their shared genes, which further validated the quality of our data. We also provided a list of significantly co-occurring gene pairs among ADs; with embedded tools, users can query gene co-occurrences and construct customized co-occurrence network with genes of interest. To make GAAD more straightforward to experimental biologists and medical scientists, we extracted additional information describing the associations through text mining, including the putative diagnostic value of the associations, type and position of gene polymorphisms, expression changes of implicated genes, as well as the phenotypical consequences, and grouped the associations accordingly. GAAD is freely available at http://gaad.medgenius.info.