Considering the role of social dynamics and positional behavior in gestural communication research.

While the hominin fossil record cannot inform us on either the presence or extent of social and cognitive abilities that may have paved the way for the emergence of language, studying non-vocal communication among our closest living relatives, the African apes, may provide valuable information about how language originated. Although much has been learned from gestural signaling in non-human primates, we have not yet established how and why gestural repertoires vary across species, what factors influence this variation, and how knowledge of these differences can contribute to an understanding of gestural signaling's contribution to language evolution. In this paper, we review arguments surrounding the theory that language evolved from gestural signaling and suggest some important factors to consider when conducting comparative studies of gestural communication among African apes. Specifically, we propose that social dynamics and positional behavior are critical components that shape the frequency and nature of gestural signaling across species and we argue that an understanding of these factors could shed light on how gestural communication may have been the basis of human language. We outline predictions for the influence of these factors on the frequencies and types of gestures used across the African apes and highlight the importance of including these factors in future gestural communication research with primates.

Response to Comment on "Whole-genome analyses resolve early branches in the tree of life of modern birds".

Mitchell et al. argue that divergence-time estimates for our avian phylogeny were too young because of an "inappropriate" maximum age constraint for the most recent common ancestor of modern birds and that, as a result, most modern bird orders diverged before the Cretaceous-Paleogene mass extinction event 66 million years ago instead of after. However, their interpretations of the fossil record and timetrees are incorrect.

North atlantic deepwater temperature change during late pliocene and late quaternary climatic cycles

Variations in the ratio of magnesium to calcium (Mg/Ca) in fossil ostracodes from Deep Sea Drilling Project Site 607 in the deep North Atlantic show that the change in bottom water temperature during late Pliocene 41,000-year obliquity cycles averaged 1.5°C between 3.2 and 2.8 million years ago (Ma) and increased to 2.3°C between 2.8 and 2.3 Ma, coincidentally with the intensification of Northern Hemisphere glaciation. During the last two 100,000-year glacial-to-interglacial climatic cycles of the Quaternary, bottom water temperatures changed by 4.5°C. These results show that glacial deepwater cooling has intensified since 3.2 Ma, most likely as the result of progressively diminished deep-water production in the North Atlantic and of the greater influence of Antarctic bottom water in the North Atlantic during glacial periods. The ostracode Mg/Ca data also allow the direct determination of the temperature component of the benthic foraminiferal oxygen isotope record from Site 607, as well as derivation of a hypothetical sea-level curve for the late Pliocene and late Quaternary. The effects of dissolution on the Mg/Ca ratios of ostracode shells appear to have been minimal.

Using electronic health record data for substance use Screening, Brief Intervention, and Referral to Treatment among adults with type 2 diabetes: Design of a National Drug Abuse Treatment Clinical Trials Network study.

BACKGROUND: The Affordable Care Act encourages healthcare systems to integrate behavioral and medical healthcare, as well as to employ electronic health records (EHRs) for health information exchange and quality improvement. Pragmatic research paradigms that employ EHRs in research are needed to produce clinical evidence in real-world medical settings for informing learning healthcare systems. Adults with comorbid diabetes and substance use disorders (SUDs) tend to use costly inpatient treatments; however, there is a lack of empirical data on implementing behavioral healthcare to reduce health risk in adults with high-risk diabetes. Given the complexity of high-risk patients' medical problems and the cost of conducting randomized trials, a feasibility project is warranted to guide practical study designs. METHODS: We describe the study design, which explores the feasibility of implementing substance use Screening, Brief Intervention, and Referral to Treatment (SBIRT) among adults with high-risk type 2 diabetes mellitus (T2DM) within a home-based primary care setting. Our study includes the development of an integrated EHR datamart to identify eligible patients and collect diabetes healthcare data, and the use of a geographic health information system to understand the social context in patients' communities. Analysis will examine recruitment, proportion of patients receiving brief intervention and/or referrals, substance use, SUD treatment use, diabetes outcomes, and retention. DISCUSSION: By capitalizing on an existing T2DM project that uses home-based primary care, our study results will provide timely clinical information to inform the designs and implementation of future SBIRT studies among adults with multiple medical conditions.

SMERED: A Bayesian Approach to Graphical Record Linkage and De-duplication

We propose a novel unsupervised approach for linking records across arbitrarily many files, while simultaneously detecting duplicate records within files. Our key innovation is to represent the pattern of links between records as a {\em bipartite} graph, in which records are directly linked to latent true individuals, and only indirectly linked to other records. This flexible new representation of the linkage structure naturally allows us to estimate the attributes of the unique observable people in the population, calculate $k$-way posterior probabilities of matches across records, and propagate the uncertainty of record linkage into later analyses. Our linkage structure lends itself to an efficient, linear-time, hybrid Markov chain Monte Carlo algorithm, which overcomes many obstacles encountered by previously proposed methods of record linkage, despite the high dimensional parameter space. We assess our results on real and simulated data.