Evolutionary game theory: Temporal and spatial effects beyond replicator dynamics

Evolutionary game dynamics is one of the most fruitful frameworks for studying evolution in different disciplines, from Biology to Economics. Within this context, the approach of choice for many researchers is the so-called replicator equation, that describes mathematically the idea that those individuals performing better have more offspring and thus their frequency in the population grows. While very many interesting results have been obtained with this equation in the three decades elapsed since it was first proposed, it is important to realize the limits of its applicability. One particularly relevant issue in this respect is that of non-mean-field effects, that may arise from temporal fluctuations or from spatial correlations, both neglected in the replicator equation. This review discusses these temporal and spatial effects focusing on the non-trivial modifications they induce when compared to the outcome of replicator dynamics. Alongside this question, the hypothesis of linearity and its relation to the choice of the rule for strategy update is also analyzed. The discussion is presented in terms of the emergence of cooperation, as one of the current key problems in Biology and in other disciplines.Comment: Review, 48 pages, 26 figure

Altruistic behavior pays, or the importance of fluctuations in evolutionary game theory

Human behavior is one of the main problems for evolution, as it is often the case that human actions are disadvantageous for the self and advantageous for other people. Behind this puzzle are our beliefs about rational behavior, based on game theory. Here we show that by going beyond the standard game-theoretical conventions, apparently altruistic behavior can be understood as self-interested. We discuss in detail an example related to the so called Ultimatum game and illustrate the appearance of altruistic behavior induced by fluctuations. In addition, we claim that in general settings, fluctuations play a very relevant role, and we support this claim by considering a completely different example, namely the Stag-Hunt game.Comment: For the proceedings of the 8th Granada Seminar on Computational Physics (AIP Proceedeings Series

Topological Traps Control Flow on Real Networks: The Case of Coordination Failures

We study evolutionary games in real social networks, with a focus on coordination games. We find that populations fail to coordinate in the same behavior for a wide range of parameters, a novel phenomenon not observed in most artificial model networks. We show that this result arises from the relevance of correlations beyond the first neighborhood, in particular from topological traps formed by links between nodes of different degrees in regions with few or no redundant paths. This specificity of real networks has not been modeled so far with synthetic networks. We thus conclude that model networks must be improved to include these mesoscopic structures, in order to successfully address issues such as the emergence of cooperation in real societies. We finally show that topological traps are a very generic phenomenon that may arise in very many different networks and fields, such as opinion models, spread of diseases or ecological networks

Severe glomerular disease in juvenile grey snapper Lutjanus griseus L. in the Gulf of Mexico caused by the myxozoan Sphaerospora motemarini n. sp.

AbstractIn the eastern Gulf of Mexico, off the coast of Florida, grey snapper, Lutjanus griseus was found to be infected with the myxozoan parasite Sphaerospora motemarini n. sp., with high prevalence (83%) and intensity of infection occuring in age-0 fish, and with parasite levels decreasing with age (age-1 snapper 40%; age-2 snapper 0%). The morphological, molecular and phylogenetic characterisation of the myxozoan showed that it is a member of the typically marine, polysporoplasmid Sphaerospora spp. which form a subclade within the Sphaerospora sensu stricto clade of myxozoans, which is characterised by large expansion segments in their SSU rDNA sequences. Presporogonic stages of S. motemarini n. sp. were detected in the blood, using PCR. Pseudoplasmodia and spores were found to develop in the renal corpuscles of the host, causing their massive expansion. Macroscopic and histopathological changes were observed in age-0 fish and show that S. motemarini n. sp. causes severe glomerulonephritis in L. griseus leading to a compromised host condition, which makes it more susceptible to stress (catch-and-release, predators, water quality) and can result in mortalities. These results are discussed in relation to the exploitation of grey snapper populations by commercial and recreational fisheries and with the observed increased mortalities with temperature along the coast of Florida. In the future, we would like to determine prevalence and intensity of infection with S. motemarini n. sp. in juvenile L. griseus in different areas of the Gulf of Mexico in order to be able to estimate the temperature dependence of S. motemarini n. sp. proliferation and to be able to predict its distribution and severity during climatic changes in the Gulf

AutoSpill is a principled framework that simplifies the analysis of multichromatic flow cytometry data.

Compensating in flow cytometry is an unavoidable challenge in the data analysis of fluorescence-based flow cytometry. Even the advent of spectral cytometry cannot circumvent the spillover problem, with spectral unmixing an intrinsic part of such systems. The calculation of spillover coefficients from single-color controls has remained essentially unchanged since its inception, and is increasingly limited in its ability to deal with high-parameter flow cytometry. Here, we present AutoSpill, an alternative method for calculating spillover coefficients. The approach combines automated gating of cells, calculation of an initial spillover matrix based on robust linear regression, and iterative refinement to reduce error. Moreover, autofluorescence can be compensated out, by processing it as an endogenous dye in an unstained control. AutoSpill uses single-color controls and is compatible with common flow cytometry software. AutoSpill allows simpler and more robust workflows, while reducing the magnitude of compensation errors in high-parameter flow cytometry

Increased IL-10-producing regulatory T cells are characteristic of severe cases of COVID-19.

OBJECTIVES: The pandemic spread of the coronavirus SARS-CoV-2 is due, in part, to the immunological properties of the host-virus interaction. The clinical presentation varies from individual to individual, with asymptomatic carriers, mild-to-moderate-presenting patients and severely affected patients. Variation in immune response to SARS-CoV-2 may underlie this clinical variation. METHODS: Using a high-dimensional systems immunology platform, we have analysed the peripheral blood compartment of 6 healthy individuals, 23 mild-to-moderate and 20 severe COVID-19 patients. RESULTS: We identify distinct immunological signatures in the peripheral blood of the mild-to-moderate and severe COVID-19 patients, including T-cell lymphopenia, more consistent with peripheral hypo- than hyper-immune activation. Unique to the severe COVID-19 cases was a large increase in the proportion of IL-10-secreting regulatory T cells, a lineage known to possess anti-inflammatory properties in the lung. CONCLUSION: As IL-10-secreting regulatory T cells are known to possess anti-inflammatory properties in the lung, their proportional increase could contribute to a more severe COVID-19 phenotype. We openly provide annotated data (https://flowrepository.org/experiments/2713) with clinical correlates as a systems immunology resource for the COVID-19 research community

NG2 antigen is involved in leukemia invasiveness and central nervous system infiltration in MLL-rearranged infant B-ALL

Mixed-lineage leukemia (MLL)-rearranged (MLLr) infant B-cell acute lymphoblastic leukemia (iMLLr-B-ALL) has a dismal prognosis and is associated with a pro-B/mixed phenotype, therapy refractoriness and frequent central nervous system (CNS) disease/relapse. Neuron-glial antigen 2 (NG2) is specifically expressed in MLLr leukemias and is used in leukemia immunophenotyping because of its predictive value for MLLr acute leukemias. NG2 is involved in melanoma metastasis and brain development; however, its role in MLL-mediated leukemogenesis remains elusive. Here we evaluated whether NG2 distinguishes leukemia-initiating/propagating cells (L-ICs) and/or CNS-infiltrating cells (CNS-ICs) in iMLLr-B-ALL. Clinical data from the Interfant cohort of iMLLr-B-ALL demonstrated that high NG2 expression associates with lower event-free survival, higher number of circulating blasts and more frequent CNS disease/relapse. Serial xenotransplantation of primary MLL-AF4 + leukemias indicated that NG2 is a malleable marker that does not enrich for L-IC or CNS-IC in iMLLr-B-All. However, NG2 expression was highly upregulated in blasts infiltrating extramedullar hematopoietic sites and CNS, and specific blockage of NG2 resulted in almost complete loss of engraftment. Indeed, gene expression profiling of primary blasts and primografts revealed a migratory signature of NG2 + blasts. This study provides new insights on the biology of NG2 in iMLLr-B-ALL and suggests NG2 as a potential therapeutic target to reduce the risk of CNS disease/relapse and to provide safer CNS-directed therapies for iMLLr-B-ALL