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AbstractObjectivesThis study characterizes patterns of cranial trauma prevalence in a large sample of Upper Paleolithic (UP) fossil specimens (40,000–10,000 BP).Materials and MethodsOur sample comprised 234 individual crania (specimens), representing 1,285 cranial bones (skeletal elements), from 101 Eurasian UP sites. We used generalized linear mixed models (GLMMs) to assess trauma prevalence in relation to age‐at‐death, sex, anatomical distribution, and between pre‐ and post‐Last Glacial Maximum (LGM) samples, while accounting for skeletal preservation.ResultsModels predicted a mean cranial trauma prevalence of 0.07 (95% CI 0.003–0.19) at the level of skeletal elements, and of 0.26 (95% CI 0.08–0.48) at the level of specimens, each when 76–100% complete. Trauma prevalence increased with skeletal preservation. Across specimen and skeletal element datasets, trauma prevalence tended to be higher for males, and was consistently higher in the old age group. We found no time‐specific trauma prevalence patterns for the two sexes or age cohorts when comparing samples from before and after the LGM. Samples showed higher trauma prevalence in the vault than in the face, with vault remains being affected predominantly in males.DiscussionCranial trauma prevalence in UP humans falls within the variation described for Mesolithic and Neolithic samples. According to our current dataset, UP males and females were exposed to slightly different injury risks and trauma distributions, potentially due to different activities or behaviors, yet both sexes exhibit more trauma among the old. Environmental stressors associated with climatic changes of the LGM are not reflected in cranial trauma prevalence. To analyze trauma in incomplete skeletal remains we propose GLMMs as an informative alternative to crude frequency calculations.

The first issue of Nature Reviews Neuroscience was published 20 years ago, in 2000. To mark this anniversary, in this Viewpoint article we asked a selection of researchers from across the field who have authored pieces published in the journal in recent years for their thoughts on notable and interesting developments in neuroscience, and particularly in their areas of the field, over the past two decades. They also provide some thoughts on current lines of research and questions that excite them.

Eocene transient global warming events (hyperthermals) can provide insight into a future warmer world. While much research has focused on the Paleocene–Eocene Thermal Maximum (PETM), hyperthermals of a smaller magnitude can be used to characterize climatic responses over different magnitudes of forcing. This study identifies two events, namely the Eocene Thermal Maximum 2 (ETM2 and H2), in shallow marine sediments of the Eocene-aged Salisbury Embayment of Maryland, based on magnetostratigraphy, calcareous nannofossil, and dinocyst biostratigraphy, as well as the recognition of negative stable carbon isotope excursions (CIEs) in biogenic calcite. We assess local environmental change in the Salisbury Embayment, utilizing clay mineralogy, marine palynology, δ18O of biogenic calcite, and biomarker paleothermometry (TEX86). Paleotemperature proxies show broad agreement between surface water and bottom water temperature changes. However, the timing of the warming does not correspond to the CIE of the ETM2 as expected from other records, and the highest values are observed during H2, suggesting factors in addition to pCO2 forcing have influenced temperature changes in the region. The ETM2 interval exhibits a shift in clay mineralogy from smectite-dominated facies to illite-rich facies, suggesting hydroclimatic changes but with a rather dampened weathering response relative to that of the PETM in the same region. Organic walled dinoflagellate cyst assemblages show large fluctuations throughout the studied section, none of which seem systematically related to CIE warming. These observations are contrary to the typical tight correspondence between climate change and assemblages across the PETM, regionally and globally, and ETM2 in the Arctic Ocean. The data do indicate very warm and (seasonally) stratified conditions, likely salinity-driven, across H2. The absence of evidence for strong perturbations in local hydrology and nutrient supply during ETM2 and H2, compared to the PETM, is consistent with the less extreme forcing and the warmer pre-event baseline, as well as the non-linear response in hydroclimates to greenhouse forcing.

Its focus on dependencies and patterns in relational data makes network science a promising addition to the analytic toolbox in archaeology. Despite its tradition in a number of other fields, however, the methodology of network science is only in development and its scope and proper usage are subject to debate. We argue that the historical linkage with graph theory and limitations in commonly available software form an obstacle to leveraging the full potential of network methods. This is illustrated via replication of a study of Maya obsidian (Golitko et al. Antiquity, 2012), in which it seemed necessary to discard detailed information in order to represent data in networks suitable for further processing. We propose means to avoid such information loss by using methods capable of handling valued rather than binarized data. The resulting representations corroborate previous conclusions but are more reliable and thus justify a more detailed interpretation of shifting supply routes as an underlying process contributing to the collapse of Maya urban centers. Some general conclusions for the use of network science in archaeology are offered. published

Recent work on Model Informed Drug Discovery and Development (MID3) has noted the need for clarity in model description used in quantitative disciplines such as pharmacology and statistics. 1-3 Currently, models are encoded in a variety of computer languages and are shared through publications that rarely include original code and generally lack reproducibility. The DDMoRe Model Description Language (MDL) has been developed primarily as a language standard to facilitate sharing knowledge and understanding of models.

The expansion of Bantu languages represents one of the most momentous events in the history of Africa. While it is well accepted that Bantu languages spread from their homeland (Cameroon/Nigeria) approximately 5000 years ago (ya), there is no consensus about the timing and geographical routes underlying this expansion. Two main models of Bantu expansion have been suggested: The 'early-split' model claims that the most recent ancestor of Eastern languages expanded north of the rainforest towards the Great Lakes region approximately 4000 ya, while the 'late-split' model proposes that Eastern languages diversified from Western languages south of the rainforest approximately 2000 ya. Furthermore, it is unclear whether the language dispersal was coupled with the movement of people, raising the question of language shift versus demic diffusion. We use a novel approach taking into account both the spatial and temporal predictions of the two models and formally test these predictions with linguistic and genetic data. Our results show evidence for a demic diffusion in the genetic data, which is confirmed by the correlations between genetic and linguistic distances. While there is little support for the early-split model, the late-split model shows a relatively good fit to the data. Our analyses demonstrate that subsequent contact among languages/populations strongly affected the signal of the initial migration via isolation by distance. International audience