Identifying individuals at risk for weight gain using machine learning in electronic medical records from the United States.

Aims: Numerous risk factors for the development of obesity have been identified, yet the aetiology is not well understood. Traditional statistical methods for analysing observational data are limited by the volume and characteristics of large datasets. Machine learning (ML) methods can analyse large datasets to extract novel insights on risk factors for obesity.

Anti-icing properties of polar bear fur.

The polar bear () is the only Arctic land mammal that dives into water to hunt. Despite thermal insulation provided by blubber and fur layers and low Arctic temperatures, their fur is typically observed to be free of ice. This study investigates the anti-icing properties of polar bear fur.

The Unusual Mesophases and Properties Exhibited by a Family of Glycosteroids.

In this article we describe research on the synthesis and characterization of a family of "Janus" amphiphiles composed of disaccharide head groups and alkaloid units joined together via a methylene linker, and bearing a lateral aliphatic chain of varying length. The condensed phases formed by self-organization of the products as a function of temperature were characterized by differential scanning calorimetry, thermal polarized light microscopy, and small angle X-ray scattering, allied with computational modelling and simulations. Structural studies on heating specimens from the solid showed that some homologues exhibited lamellar, columnar and bicontinuous mesophases, whereas the same homologues revealed different phase sequences on cooling from the amorphous liquid.

Human outbreaks of a novel reassortant Oropouche virus in the Brazilian Amazon region.

The Brazilian western Amazon is experiencing its largest laboratory-confirmed Oropouche virus (OROV) outbreak, with more than 6,300 reported cases between 2022 and 2024. In this study, we sequenced and analyzed 382 OROV genomes from human samples collected in Amazonas, Acre, Rondônia and Roraima states, between August 2022 and February 2024, to uncover the origin and genetic evolution of OROV in the current outbreak. Genomic analyses revealed that the upsurge of OROV cases in the Brazilian Amazon coincides with spread of a novel reassortant lineage containing the M segment of viruses detected in the eastern Amazon region (2009-2018) and the L and S segments of viruses detected in Peru, Colombia and Ecuador (2008-2021).