Mammal responses to global changes in human activity vary by trophic group and landscape.

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely.

Inositol phosphatase INPP4B sustains ILC1s and intratumoral NK cells through an AKT-driven pathway.

Innate lymphoid cells (ILCs) are a heterogeneous population of lymphocytes that coordinate early immune responses and maintain tissue homeostasis. Type 1 innate immune responses are mediated by natural killer (NK) cells and group 1 ILCs (ILC1s). Despite their shared features, NK cells and ILC1s display profound differences among various tissue microenvironments.

Diversification of the terrestrial frog genus Anomaloglossus (Anura, Aromobatidae) in the Guiana Shield proceeded from highlands to lowlands, with successive loss and reacquisition of endotrophy.

Two main landscapes emerge from the Guiana Shield: the highlands to the west called the Pantepui region and the Amazonian lowlands to the east, both harbouring numerous endemic species. With 32 currently recognized species, the genus Anomaloglossus stands out among Neotropical frogs as one that diversified only within the Guiana Shield both in the highlands and the lowlands. We present a time-calibrated phylogeny obtained by using combined mitogenomic and nuclear DNA, which suggests that the genus originates from Pantepui where extant lineages started diversifying around 21 Ma, and subsequently (ca.

Measuring uncertainty in human visual segmentation.

Segmenting visual stimuli into distinct groups of features and visual objects is central to visual function. Classical psychophysical methods have helped uncover many rules of human perceptual segmentation, and recent progress in machine learning has produced successful algorithms. Yet, the computational logic of human segmentation remains unclear, partially because we lack well-controlled paradigms to measure perceptual segmentation maps and compare models quantitatively.