Cornell researchers document one of the largest known ground-nesting bee populations
Peer-Reviewed Publication
Updates every hour. Last Updated: 30-May-2026 06:16 ET (30-May-2026 10:16 GMT/UTC)
New Cornell University research finds an Ithaca cemetery is home to one of the largest and oldest recorded aggregations of ground nesting bees in the world, with an estimated 5.5 million individual bees. That’s the equivalent of more than 200 honeybee hives in a 1.5 acre plot of land.
In the deserts of southeastern Arizona, harvester ants congregate with serrated jaws agape outside the nests of much smaller cone ants. However, the nests’ inhabitants are not threatened. Instead, they crawl all over the harvester ants and lick and nibble their body surfaces—the first known example of an ant that cleans a much larger ant species. The unusual behavior, described for the first time this week in the journal Ecology and Evolution, was observed by entomologist Mark Moffett, a research associate at the Smithsonian's National Museum of Natural History.
A team of Weill Cornell Medicine investigators is working to cross-train the next generation of cancer researchers in cancer biology and the use of artificial intelligence tools for research.
Vaccines rely on adjuvants to enhance immune protection, but these often cause reactogenicity, such as swelling or fever. Challenging the long-held assumption that these effects are inseparable, researchers from Japan have shown that vaccine efficacy and reactogenicity are driven by distinct immune pathways. Their findings reveal specific roles for IL-1α and IL-1β in controlling these responses, opening new possibilities for designing vaccines that maintain strong immunity while minimizing adverse effects.
With the rapid development of single-cell RNA sequencing (scRNA-seq), researchers can now examine gene activity in individual plant cells at unprecedented resolution, opening new opportunities to study cell differentiation, tissue development, and stress responses. However, scRNA-seq datasets compile data from thousands of cells and are characterized by high dimensionality, extreme sparsity, and substantial technical noise. Notably, most of the genes expressed in a given cell are expressed in every type of cell; only a relatively small number of genes, so-called marker genes, are specific to each cell type. Consequently, the task of assigning roles to individual cells relies heavily on prior knowledge of the biological context and which genes are highly expressed in each cell type — making it difficult to identify marker genes and assign cell types accurately.