Contrasting terrestrial and marine ecospace dynamics after the end-Triassic mass extinction event.

Mass extinctions have fundamentally altered the structure of the biosphere throughout Earth's history. The ecological severity of mass extinctions is well studied in marine ecosystems by categorizing marine taxa into functional groups based on 'ecospace' approaches, but the ecological response of terrestrial ecosystems to mass extinctions is less well understood due to the lack of a comparable methodology. Here, we present a new terrestrial ecospace framework that categorizes fauna into functional groups as defined by tiering, motility and feeding traits.

Challenges and directions in analytical paleobiology.

Over the last 50 years, access to new data and analytical tools has expanded the study of analytical paleobiology, contributing to innovative analyses of biodiversity dynamics over Earth's history. Despite-or even spurred by-this growing availability of resources, analytical paleobiology faces deep-rooted obstacles that stem from the need for more equitable access to data and best practices to guide analyses of the fossil record. Recent progress has been accelerated by a collective push toward more collaborative, interdisciplinary, and open science, especially by early-career researchers.

B Cell Profiling in Patients with Pemphigus Vulgaris.

Pemphigus vulgaris is a severe, socially significant autoimmune disease associated with autoantibodies to the desmoglein 3 antigen. The disease affects all age groups, beginning at 18 years of age; the mortality rate of pemphigus can reach as high as 50%, depending on a patient's age and a number of other factors. There is no highly selective or personalized therapy for pemphigus vulgaris at the moment.

How predictable are mass extinction events?

Many modern extinction drivers are shared with past mass extinction events, such as rapid climate warming, habitat loss, pollution and invasive species. This commonality presents a key question: can the extinction risk of species during past mass extinction events inform our predictions for a modern biodiversity crisis? To investigate if it is possible to establish which species were more likely to go extinct during mass extinctions, we applied a functional trait-based model of extinction risk using a machine learning algorithm to datasets of marine fossils for the end-Permian, end-Triassic and end-Cretaceous mass extinctions. Extinction selectivity was inferred across each individual mass extinction event, before testing whether the selectivity patterns obtained could be used to 'predict' the extinction selectivity exhibited during the other mass extinctions.