Mesoscopic structure conditions the emergence of cooperation on social networks

We study the evolutionary Prisoner's Dilemma on two social networks obtained from actual relational data. We find very different cooperation levels on each of them that can not be easily understood in terms of global statistical properties of both networks. We claim that the result can be understood at the mesoscopic scale, by studying the community structure of the networks. We explain the dependence of the cooperation level on the temptation parameter in terms of the internal structure of the communities and their interconnections. We then test our results on community-structured, specifically designed artificial networks, finding perfect agreement with the observations in the real networks. Our results support the conclusion that studies of evolutionary games on model networks and their interpretation in terms of global properties may not be sufficient to study specific, real social systems. In addition, the community perspective may be helpful to interpret the origin and behavior of existing networks as well as to design structures that show resilient cooperative behavior.Comment: Largely improved version, includes an artificial network model that fully confirms the explanation of the results in terms of inter- and intra-community structur

Cooperation and Contagion in Web-Based, Networked Public Goods Experiments

A longstanding idea in the literature on human cooperation is that cooperation should be reinforced when conditional cooperators are more likely to interact. In the context of social networks, this idea implies that cooperation should fare better in highly clustered networks such as cliques than in networks with low clustering such as random networks. To test this hypothesis, we conducted a series of web-based experiments, in which 24 individuals played a local public goods game arranged on one of five network topologies that varied between disconnected cliques and a random regular graph. In contrast with previous theoretical work, we found that network topology had no significant effect on average contributions. This result implies either that individuals are not conditional cooperators, or else that cooperation does not benefit from positive reinforcement between connected neighbors. We then tested both of these possibilities in two subsequent series of experiments in which artificial seed players were introduced, making either full or zero contributions. First, we found that although players did generally behave like conditional cooperators, they were as likely to decrease their contributions in response to low contributing neighbors as they were to increase their contributions in response to high contributing neighbors. Second, we found that positive effects of cooperation were contagious only to direct neighbors in the network. In total we report on 113 human subjects experiments, highlighting the speed, flexibility, and cost-effectiveness of web-based experiments over those conducted in physical labs

Altruism can proliferate through group/kin selection despite high random gene flow

The ways in which natural selection can allow the proliferation of cooperative behavior have long been seen as a central problem in evolutionary biology. Most of the literature has focused on interactions between pairs of individuals and on linear public goods games. This emphasis led to the conclusion that even modest levels of migration would pose a serious problem to the spread of altruism in group structured populations. Here we challenge this conclusion, by analyzing evolution in a framework which allows for complex group interactions and random migration among groups. We conclude that contingent forms of strong altruism can spread when rare under realistic group sizes and levels of migration. Our analysis combines group-centric and gene-centric perspectives, allows for arbitrary strength of selection, and leads to extensions of Hamilton's rule for the spread of altruistic alleles, applicable under broad conditions.Comment: 5 pages, 2 figures. Supplementary material with 50 pages and 26 figure

Diagnostic yield of 18F-FDG PET/CT in suspected diagnosis of vascular graft infection: A prospective cohort study

Background. Prosthetic vascular graft infection (PVGI) is a severe complication associated with high morbidity and mortality. Clinical diagnosis is complex, requiring image testing such as CT angiography or leukocyte scintigraphy, which has considerable limitations. The aim of this study was to know the diagnostic yield of PET/CT with 18F-Fluorodeoxyglucose (18F-FDG) in patients with suspected PVGI. Methods. We performed a prospective cohort study including 49 patients with suspected PVGI, median age of 62 ± 14 years. Three uptake patterns were defined following published recommendations: (i) focal, (ii) patched (PVGI criteria), and (iii) diffuse (no PVGI criterion). Results. Sensitivity, specificity, and positive and negative predictive values for 18F-FDG-PET/ CT were 88%, 79%, 67%, and 93%, respectively. 18F-FDG-PET/CT identified 14/16 cases of PVGI showing a focal (n = 10) or patched pattern (n = 4), being true negative in 26/33 cases with either a diffuse pattern (n = 16) or without uptake (n = 10). Five of the seven false-positive cases (71%) showed a patched pattern and all coincided with the application of adhesives for PVG placement. Conclusions. 18F-FDG-PET/CT is a useful technique for the diagnosis of PVGI. A patched pattern on PET/CT in patients in whom adhesives were applied for prosthetic vascular graft placement does not indicate infection. (J Nucl Cardiol 2018) Key Words: Fluorodeoxyglucose (FDG) Æ diagnostic and prognostic application Æ PET/CT imagin

Group-level selection increases cooperation in the public goods game

When groups compete for resources, some groups will be more successful than others, forcing out less successful groups. Group-level selection is the most extreme form of group competition, where the weaker group ceases to exist, becoming extinct. We implement group-level selection in a controlled laboratory experiment in order to study its impact on human cooperation. The experiment uses variations on the standard linear public goods game. Group-level selection operates through competition for survival: the least successful, lowest-earning groups become extinct, in the sense that they no longer are able to play the game. Additional control treatments include group comparison without extinction, and extinction of the least successful individuals across groups. We find that group-level extinction produces very high contributions to the provision of the public good, while group comparison alone or individual extinction fail to cause higher contributions. Our results provide stark evidence that group-level selection enhances within-group cooperation

Interaction between NANOS2 and the CCR4-NOT Deadenylation Complex Is Essential for Male Germ Cell Development in Mouse

Nanos is one of the evolutionarily conserved proteins implicated in germ cell development and we have previously shown that it interacts with the CCR4-NOT deadenylation complex leading to the suppression of specific RNAs. However, the molecular mechanism and physiological significance of this interaction have remained elusive. In our present study, we identify CNOT1, a component of the CCR4-NOT deadenylation complex, as a direct factor mediating the interaction with NANOS2. We find that the first 10 amino acids (AAs) of NANOS2 are required for this binding. We further observe that a NANOS2 mutant lacking these first 10 AAs (NANOS2-ΔN10) fails to rescue defects in the Nanos2-null mouse. Our current data thus indicate that the interaction with the CCR4-NOT deadenylation complex is essential for NANOS2 function. In addition, we further demonstrate that NANOS2-ΔN10 can associate with specific mRNAs as well as wild-type NANOS2, suggesting the existence of other NANOS2-associated factor(s) that determine the specificity of RNA-binding independently of the CCR4-NOT deadenylation complex

The emergence of reciprocally beneficial cooperation

We offer a new and robust model of the emergence and persistence of cooperation when interactions are anonymous, the population is well-mixed, and evolution selects strategies according to material payoffs. The model has a Prisoner’s Dilemma structure, but with an outside option of non-participation. The payoff to mutual cooperation is stochastic; with positive probability, it exceeds that from cheating against a cooperator. Under mild conditions, mutually beneficial cooperation occurs in equilibrium. This is possible because the non-participation option holds down the equilibrium frequency of cheating. Dynamic properties of the model are investigated theoretically and through simulations based on replicator dynamics

Assessing historical realibility of the agent-based model of the global energy system

This study looks at the historical reliability of the agent-based model of the global energy system. We present a mathematical framework for the agent-based model calibration and sensitivity analysis based on historical observations. Simulation consistency with the historical record is measured as a distance between two vectors of data points and inference on parameter values is done from the probability distribution of this stochastic estimate. Proposed methodology is applied to the model of the global energy system. Some model properties and limitations followed from calibration results are discussed