Using synthetic biology to screen for functional diversity of GH1 enzymes

Advances in next-generation sequencing technologies have enabled single genomes as well as complex environmental samples (metagenomes) to be comprehensively sequenced on a routine basis. Bioinformatics analysis of the resulting sequencing data reveals a continually expanding catalogue of predicted proteins ( 14 million as of April 2011), 75 percent of which are associated with functional annotation (COG, Pfam, Enzyme, Kegg, etc). These predicted proteins cover the full spectrum of known pathways and functional activities, including many novel biocatalysts that are expected to significantly contribute to the development of clean technologies including biomass degradation, lipid transformation for biodiesel generation, intermediates for polymer production, carbon capture, and bioremediation

The Nairobi Declaration—Reducing the burden of dementia in low‐ and middle‐income countries (LMICs): Declaration of the 2022 Symposium on Dementia and Brain Aging in LMICs

[No abstract available

Event generators for high-energy physics experiments

We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements. Particular emphasis is given to physics models and algorithms that are employed across a variety of experiments. These common themes in event generator development lead to a more comprehensive understanding of physics at the highest energies and intensities, and allow models to be tested against a wealth of data that have been accumulated over the past decades. A cohesive approach to event generator development will allow these models to be further improved and systematic uncertainties to be reduced, directly contributing to future experimental success. Event generators are part of a much larger ecosystem of computational tools. They typically involve a number of unknown model parameters that must be tuned to experimental data, while maintaining the integrity of the underlying physics models. Making both these data, and the analyses with which they have been obtained accessible to future users is an essential aspect of open science and data preservation. It ensures the consistency of physics models across a variety of experiments.peerReviewe