SARS-CoV-2 mRNA-based vaccines in the Aicardi Goutières Syndrome.

Aicardi Goutières Syndrome (AGS) is an autoinflammatory disorder resulting in sustained interferon activation through defects in nucleic acid modification and sensing pathways. Thus, mRNA-based vaccination used against SARS-CoV-2, raise disease-specific safety concerns. To assess interferon signaling, we tested mRNA SARS-CoV-2 vaccines in AGS whole blood samples. Interferon activation is measured through quantitation of interferon signaling gene (ISG) expression and is increased in AGS patients. There was no increase in ISG scores from baseline following treatment with the nucleoside modified mRNA formulation compared to an increase with unmodified. A patient-family survey reported that the vaccines were well tolerated. These findings suggest that COVID vaccination using nucleoside-modified forms of mRNA vaccines are unlikely to directly stimulate ISG expression in response to mRNA internalization in AGS tissues. With continued community spread, we recommend vaccination using nucleoside-modified mRNA vaccines in this rare disease group in individuals for whom vaccines were previously well tolerated.

The Proteome Folding Project: proteome-scale prediction of structure and function.

The incompleteness of proteome structure and function annotation is a critical problem for biologists and, in particular, severely limits interpretation of high-throughput and next-generation experiments. We have developed a proteome annotation pipeline based on structure prediction, where function and structure annotations are generated using an integration of sequence comparison, fold recognition, and grid-computing-enabled de novo structure prediction. We predict protein domain boundaries and three-dimensional (3D) structures for protein domains from 94 genomes (including human, Arabidopsis, rice, mouse, fly, yeast, Escherichia coli, and worm). De novo structure predictions were distributed on a grid of more than 1.5 million CPUs worldwide (World Community Grid). We generated significant numbers of new confident fold annotations (9% of domains that are otherwise unannotated in these genomes). We demonstrate that predicted structures can be combined with annotations from the Gene Ontology database to predict new and more specific molecular functions.

Self-indicating radiation alert dosemeter (SIRAD).

In an event of a nuclear or dirty bomb explosion and a radiological accident, there is a need for self-indicating instant radiation dosemeter for monitoring radiation exposure. The self-indicating instant radiation alert dosemeter (SIRAD) is a credit card size radiation dosemeter for monitoring ionising radiation from a few hundredths of a Gray to a few Gray. It is always active and is ready to use. It needs no battery. The dosemeter develops colour instantly upon exposure, and the colour intensifies with dose. It has a colour chart so that the dose on the active element may be read by matching its colour with the chart that is printed next to it on the card. However, in this work, the dose is measured by the optical density of the element. The dosemeter cannot be reset. The response changes by <1% per degrees C from -20 to +60 degrees C. The shelf-life is >3 y at room temperature. It contains no hazardous materials. The dosemeter would meet the requirements of instantly monitoring high dose in an event of a nuclear or dirty bomb explosion or a radiation accident.