Three new species of the family Idyanthidae (Copepoda, Harpacticoida) from sublittoral zones around the Korean Peninsula.

There are few taxonomic studies of the harpacticoid family Idyanthidae Lang, 1944 in the Pacific Ocean. As a first report of the family in this region, one species of the monotypic genus Lang, 1948 and two species of the genus Sars, 1905 are described from sublittoral habitats around the Korean Peninsula. sp.

Foxi2 and Sox3 are master regulators controlling ectoderm germ layer specification.

Unlabelled: In vertebrates, germ layer specification represents a critical transition where pluripotent cells acquire lineage-specific identities. We identify the maternal transcription factors Foxi2 and Sox3 to be pivotal master regulators of ectodermal germ layer specification in . Ectopic co-expression of Foxi2 and Sox3 in prospective endodermal tissue induces the expression of ectodermal markers while suppressing mesendodermal markers.

Proteomic analysis reveals the roles of silicon in mitigating glyphosate-induced toxicity in Brassica napus L.

Glyphosate (Gly) is a widely used herbicide for weed control in agriculture, but it can also adversely affect crops by impairing growth, reducing yield, and disrupting nutrient uptake, while inducing toxicity. Therefore, adopting integrated eco-friendly approaches and understanding the mechanisms of glyphosate tolerance in plants is crucial, as these areas remain underexplored. This study provides proteome insights into Si-mediated improvement of Gly-toxicity tolerance in Brassica napus.

Graph-based deep learning for predictions on changes in microbiomes and biogas production in anaerobic digestion systems.

Anaerobic digestion (AD), which relies on a complex microbial consortium for efficient biogas generation, is a promising avenue for renewable energy production and organic waste treatment. However, understanding and optimising AD processes are challenging because of the intricate interactions within microbial communities and the impact of volatile fatty acids (VFAs) on biogas production. To address these challenges, this study proposes the application of graph convolutional networks (GCNs) to comprehensively model AD processes.