Can People Guess What Happened to Others from Their Reactions?

Are we able to infer what happened to a person from a brief sample of his/her behaviour? It has been proposed that mentalising skills can be used to retrodict as well as predict behaviour, that is, to determine what mental states of a target have already occurred. The current study aimed to develop a paradigm to explore these processes, which takes into account the intricacies of real-life situations in which reasoning about mental states, as embodied in behaviour, may be utilised. A novel task was devised which involved observing subtle and naturalistic reactions of others in order to determine the event that had previously taken place. Thirty-five participants viewed videos of real individuals reacting to the researcher behaving in one of four possible ways, and were asked to judge which of the four ‘scenarios’ they thought the individual was responding to. Their eye movements were recorded to establish the visual strategies used. Participants were able to deduce successfully from a small sample of behaviour which scenario had previously occurred. Surprisingly, looking at the eye region was associated with poorer identification of the scenarios, and eye movement strategy varied depending on the event experienced by the person in the video. This suggests people flexibly deploy their attention using a retrodictive mindreading process to infer events.     

A MONTE CARLO SIMULATION OF CLONE GROWTH

A Monte Carlo simulation of clone growth is discussed from the point of view of clonal volume. It is shown that clone volume is a good representation of the number of cells per clone for a wide range of single cell growth equations. However, the rate at which the coefficient of variation in clonal volume approaches that of cell number per clone is strongly dependent upon the particular growth equation.     

Evolution of green lacewings (Neuroptera: Chrysopidae): a molecular supermatrix approach

We present a time‐calibrated phylogeny of the charismatic green lacewings (Neuroptera: Chrysopidae). Previous phylogenetic studies on the family using DNA sequences have suffered from sparse taxon sampling and/or limited amounts of data. Here we combine all available previously published DNA sequence data and add to it new DNA sequences generated for this study. We analysed these data in a supermatrix using Bayesian and maximum likelihood methods and provide a phylogenetic hypothesis for the family that recovers strong support for the monophyly of all subfamilies and resolves relationships among a large proportion of chrysopine genera. Chrysopinae tribes Leucochrysini and Belonopterygini were recovered as monophyletic sister clades, while the species‐rich tribe Chrysopini was rendered paraphyletic by Ankylopterygini. Relationships among the subfamilies were resolved, although with relatively low statistical support, and the topology varied based on the method of analysis. Greatest support was found for Apochrysinae as sister to Nothochrysinae and Chrysopinae, which is in contrast to traditional concepts that place Nothochrysinae as sister to the rest of the family. Divergence estimates suggest that the stem groups to the various subfamilies diverged during the Triassic‐Jurassic, and that stem groups of the chrysopine tribes diverged during the Cretaceous.     

Genome-wide CRISPR Screens Reveal Host Factors Critical for SARS-CoV-2 Infection

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Emerging infectious diseases and animal social systems

Emerging infectious diseases threaten a wide diversity of animals, and important questions remain concerning disease emergence in socially structured populations. We developed a spatially explicit simulation model to investigate whether—and under what conditions—disease-related mortality can impact rates of pathogen spread in populations of polygynous groups. Specifically, we investigated whether pathogen-mediated dispersal (PMD) can occur when females disperse after the resident male dies from disease, thus carrying infections to new groups. We also examined the effects of incubation period and virulence, host mortality and rates of background dispersal, and we used the model to investigate the spread of the virus responsible for Ebola hemorrhagic fever, which currently is devastating African ape populations. Output was analyzed using regression trees, which enable exploration of hierarchical and non-linear relationships. Analyses revealed that the incidence of disease in single-male (polygynous) groups was significantly greater for those groups containing an average of more than six females, while the total number of infected hosts in the population was most sensitive to the number of females per group. Thus, as expected, PMD occurs in polygynous groups and its effects increase as harem size (the number of females) increases. Simulation output further indicated that population-level effects of Ebola are likely to differ among multi-male–multi-female chimpanzees and polygynous gorillas, with larger overall numbers of chimpanzees infected, but more gorilla groups becoming infected due to increased dispersal when the resident male dies. Collectively, our results highlight the importance of social system on the spread of disease in wild mammals.