The plasma metabolome of juvenile idiopathic arthritis varies according to subtype and underlying inflammatory status.

Background: Juvenile idiopathic arthritis (JIA) is challenging to classify and effectively monitor due to the lack of disease- and subtype-specific biomarkers. A robust molecular signature that tracks with specific JIA features over time is urgently required, and targeted plasma metabolomics may reveal such a signature. The primary aim of this study was to characterise the differences in the plasma metabolome between JIA patients and non-JIA controls and identify specific markers of JIA subtype.

Feed additives for methane mitigation: Modeling the impact of feed additives on enteric methane emission of ruminants-Approaches and recommendations.

Over the past decade, there has been considerable attention on mitigating enteric methane (CH) emissions from ruminants through the utilization of antimethanogenic feed additives (AMFA). Administered in small quantities, these additives demonstrate potential for substantial reductions of methanogenesis. Mathematical models play a crucial role in comprehending and predicting the quantitative impact of AMFA on enteric CH emissions across diverse diets and production systems.

Erratum: First Search for Dyons with the Full MoEDAL Trapping Detector in 13 TeV pp Collisions [Phys. Rev. Lett. 126, 071801 (2021)].

This corrects the article DOI: 10.1103/PhysRevLett.126.

Identifying climate refugia for vulnerable marine ecosystem indicator taxa under future climate change scenarios.

Vulnerable Marine Ecosystems (VMEs) are recognised as having high ecological significance and susceptibility to disturbances, including climate change. One approach to providing information on the location and biological composition of these ecosystems, especially in difficult-to-reach environments such as the deep sea, is to generate spatial predictions for VME indicator taxa. In this study, the Random Forest algorithm was used to model the spatial distribution of density for 14 deep-water VME indicator taxa under current environmental conditions and future climate change scenarios (SSP2-4.