Attentional Prioritization of Infant Faces Is Limited to Own-Race Infants

Background: Recent evidence indicates that infant faces capture attention automatically, presumably to elicit caregiving behavior from adults and leading to greater probability of progeny survival. Elsewhere, evidence demonstrates that people show deficiencies in the processing of other-race relative to own-race faces. We ask whether this other-race effect impacts on attentional attraction to infant faces. Using a dot-probe task to reveal the spatial allocation of attention, we investigate whether other-race infants capture attention. Principal Findings: South Asian and White participants (young adults aged 18–23 years) responded to a probe shape appearing in a location previously occupied by either an infant face or an adult face; across trials, the race (South Asian/ White) of the faces was manipulated. Results indicated that participants were faster to respond to probes that appeared in the same location as infant faces than adult faces, but only on own-race trials. Conclusions/Significance: Own-race infant faces attract attention, but other-race infant faces do not. Sensitivity to facespecific care-seeking cues in other-race kindenschema may be constrained by interracial contact and experience

Animal movement in dynamic landscapes : interaction between behavioural strategies and resource distributions

Most ecological and evolutionary processes are thought to critically depend on dispersal and individual movement but there is little empirical information on the movement strategies used by animals to find resources. In particular, it is unclear whether behavioural variation exists at all scales, or whether behavioural decisions are primarily made at small spatial scales and thus broad-scale patterns of movement simply reflect underlying resource distributions. We evaluated animal movement responses to variable resource distributions using the grey teal (Anas gracilis) in agricultural and desert landscapes in Australia as a model system. Birds in the two landscapes differed in the fractal dimension of their movement paths, with teal in the desert landscape moving less tortuously overall than their counterparts in the agricultural landscape. However, the most striking result was the high levels of individual variability in movement strategies, with different animals exhibiting different responses to the same resources. Teal in the agricultural basin moved with both high and low tortuosity, while teal in the desert basin primarily moved using low levels of tortuosity. These results call into question the idea that broad-scale movement patterns simply reflect underlying resource distributions, and suggest that movement responses in some animals may be behaviourally complex regardless of the spatial scale over which movement occurs

The Immune Landscape of Cancer

We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes\u2014wound healing, IFN-\u3b3 dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-\u3b2 dominant\u2014characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell proliferation, expression of immunomodulatory genes, and prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF, TP53, or CASP8) leukocyte levels across all cancers. Multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number, and epigenetic processes) were involved in tumor-immune cell interactions, both across and within immune subtypes. Our immunogenomics pipeline to characterize these heterogeneous tumors and the resulting data are intended to serve as a resource for future targeted studies to further advance the field. Thorsson et al. present immunogenomics analyses of more than 10,000 tumors, identifying six immune subtypes that encompass multiple cancer types and are hypothesized to define immune response patterns impacting prognosis. This work provides a resource for understanding tumor-immune interactions, with implications for identifying ways to advance research on immunotherapy

Erratum: The Immune Landscape of Cancer (Immunity (2018) 48(4) (812–830.e14), (S1074761318301213), (10.1016/j.immuni.2018.03.023))

(Immunity 48, 812–830.e1–e14; April 17, 2018) In the originally published version of this article, the authors neglected to include Younes Mokrab and Aaron M. Newman as co-authors and misspelled the names of authors Charles S. Rabkin and Ilya Shmulevich. The author names have been corrected here and online. In addition, the concluding sentence of the subsection “Immune Signature Compilation” in the Method Details in the original published article was deemed unclear because it did not specify differences among the gene set scoring methods. The concluding sentences now reads “Gene sets from Bindea et al., Senbabaoglu et al., and the MSigDB C7 collection were scored using single-sample gene set enrichment (ssGSEA) analysis (Barbie et al., 2009), as implemented in the GSVA R package (Hänzelmann et al., 2013). All other signatures were scored using methods found in the associated citations.