Characterisation of seryl tRNA synthetase (srs-2) in Haemonchus contortus and Teladorsagia circumcincta.

The aim of the study was to purify and characterise recombinant proteins with the potential as an anti-parasite vaccine. Full-length cDNAs encoding seryl-tRNA synthetase (srs-2) were cloned from Haemonchus contortus (HcSRS-2) and Teladorsagia circumcincta (TcSRS-2). TcSRS-2 and HcSRS-2 cDNA (1458bp) encoded proteins of 486 amino acids, each of which was present as a single band of about 55 kDa on SDS-PAGE.

Navigation through high-dimensional chemical space: discovery of BaY[SiO]O and BaY[SiO].

Two compounds were discovered in the well-studied BaO-YO-SiO phase field. Two different experimental routines were used for the exploration of this system due to the differences of synthetic conditions and competition with a glass field. The first phase BaY[SiO]O was isolated through a combination of energy dispersive X-ray spectroscopy analysis and diffraction techniques which guided the exploration.

Integration of generative machine learning with the heuristic crystal structure prediction code FUSE.

The prediction of new compounds crystal structure prediction may transform how the materials chemistry community discovers new compounds. In the prediction of inorganic crystal structures there are three distinct classes of prediction: performing crystal structure prediction heuristic algorithms, using a range of established crystal structure prediction codes, an emerging community using generative machine learning models to predict crystal structures directly and the use of mathematical optimisation to solve crystal structures exactly. In this work, we demonstrate the combination of heuristic and generative machine learning, the use of a generative machine learning model to produce the starting population of crystal structures for a heuristic algorithm and discuss the benefits, demonstrating the method on eight known compounds with reported crystal structures and three hypothetical compounds.

Trauma advanced practice provider education: the current state of trauma advanced practice provider postgraduate education in the United States.

Background: Postgraduate education for advanced practice providers (APPs) is a rapidly evolving field and includes residencies and fellowships designed to help narrow the gap between physicians and APPs. The current state of trauma APP postgraduate programs in the U.S.