Quantitative historical analysis uncovers a single dimension of complexity that structures global variation in human social organization.

Do human societies from around the world exhibit similarities in the way that they are structured, and show commonalities in the ways that they have evolved? These are long-standing questions that have proven difficult to answer. To test between competing hypotheses, we constructed a massive repository of historical and archaeological information known as "Seshat: Global History Databank." We systematically coded data on 414 societies from 30 regions around the world spanning the last 10,000 years. We were able to capture information on 51 variables reflecting nine characteristics of human societies, such as social scale, economy, features of governance, and information systems. Our analyses revealed that these different characteristics show strong relationships with each other and that a single principal component captures around three-quarters of the observed variation. Furthermore, we found that different characteristics of social complexity are highly predictable across different world regions. These results suggest that key aspects of social organization are functionally related and do indeed coevolve in predictable ways. Our findings highlight the power of the sciences and humanities working together to rigorously test hypotheses about general rules that may have shaped human history.

Open Targets: a platform for therapeutic target identification and validation.

We have designed and developed a data integration and visualization platform that provides evidence about the association of known and potential drug targets with diseases. The platform is designed to support identification and prioritization of biological targets for follow-up. Each drug target is linked to a disease using integrated genome-wide data from a broad range of data sources. The platform provides either a target-centric workflow to identify diseases that may be associated with a specific target, or a disease-centric workflow to identify targets that may be associated with a specific disease. Users can easily transition between these target- and disease-centric workflows. The Open Targets Validation Platform is accessible at https://www.targetvalidation.org.

War, space, and the evolution of Old World complex societies.

How did human societies evolve from small groups, integrated by face-to-face cooperation, to huge anonymous societies of today, typically organized as states? Why is there so much variation in the ability of different human populations to construct viable states? Existing theories are usually formulated as verbal models and, as a result, do not yield sharply defined, quantitative predictions that could be unambiguously tested with data. Here we develop a cultural evolutionary model that predicts where and when the largest-scale complex societies arose in human history. The central premise of the model, which we test, is that costly institutions that enabled large human groups to function without splitting up evolved as a result of intense competition between societies-primarily warfare. Warfare intensity, in turn, depended on the spread of historically attested military technologies (e.g., chariots and cavalry) and on geographic factors (e.g., rugged landscape). The model was simulated within a realistic landscape of the Afroeurasian landmass and its predictions were tested against a large dataset documenting the spatiotemporal distribution of historical large-scale societies in Afroeurasia between 1,500 BCE and 1,500 CE. The model-predicted pattern of spread of large-scale societies was very similar to the observed one. Overall, the model explained 65% of variance in the data. An alternative model, omitting the effect of diffusing military technologies, explained only 16% of variance. Our results support theories that emphasize the role of institutions in state-building and suggest a possible explanation why a long history of statehood is positively correlated with political stability, institutional quality, and income per capita.

Antegrade rapid prime displacement in elective coronary artery surgery is associated with lower perioperative blood transfusions and a shorter hospital stay.

OBJECTIVES: Haemodilution during cardiopulmonary bypass is associated with increased perioperative blood transfusions and is thought to reduce intraoperative oxygen delivery to the brain. We sought to evaluate our method of rapid antegrade prime displacement in the context of the perioperative blood transfusion rate, intraoperative cerebral saturations and postoperative hospital stay. METHODS: Retrospective analysis of 160 propensity-matched patients undergoing elective coronary artery bypass grafting was performed comparing different perfusion strategies on perioperative blood transfusion and length of postoperative stay. Eighty patients who had rapid antegrade prime displacement and vacuum-assisted venous drainage (RAD-VAD) were compared with 80 patients who had conventional cardiopulmonary bypass with gravity drainage (CB). RAD-VAD involved displacing all or most of the prime in the circuit with the patient's own blood prior to the initiation of cardiopulmonary bypass within a 15-20 s window. Within each group, 10 patients had intraoperative cerebral saturation measurements. RESULTS: There were no differences in the baseline characteristics between the groups. Both groups had a significant fall (P < 0.05) in haematocrit during cardiopulmonary bypass from preoperative values, however, the fall in haematocrit was significantly less in the RAD-VAD group (P < 0.05). There was significantly (P < 0.05) less intraoperative and postoperative homologous blood transfusions in the RAD-VAD group (47.892 ml ± 8.14 and 76.58 ml ± 21.58) compared with the CB group (229.06 ml ± 105.03 and 199.91 ml ± 47.13). There was a significant fall in cerebral saturations within both groups (P < 0.05) but it was not significant between the groups. The postoperative stay was significantly (P < 0.05) shorter in the RAD-VAD group compared with the conventional group (7.74 days ± 0.51 vs 10.13 days ± 0.95). CONCLUSIONS: RAD-VAD is associated with a significantly lower blood transfusion rate perioperatively and shorter hospital stays compared with CB.