Rational reasoning or adaptive behavior? Evidence from two-person beauty contest games

Many experiments have shown that human subjects do not necessarily behave in line with game theoretic assumptions and solution concepts. The reasons for this non-conformity are multiple. In this paper we study the argument whether a deviation from game theory is because subjects are rational, but doubt that others are rational as well, compared to the argument that subjects, in general, are boundedly rational themselves. To distinguish these two hypotheses, we study behavior in repeated 2-person and many-person Beauty-Contest-Games which are strategically different from one another. We analyze four different treatments and observe that convergence toward equilibrium is driven by learning through the information about the other player s choice and adaptation rather than self-initiated rational reasoning.

Human nature and institutional analysis

This essay reviews some findings in cognition sciences and examines their consequences for the analysis of institutions. It starts by exploring how humans specialization in producing knowledge ensures our success in dominating the environment but also changes fast our environment. So fast that it did not give time to natural selection to adapt our biology, causing it to be potentially maladapted in important dimensions. A main function of institutions is therefore to fill the gap between the demands of our relatively new environment and our biology, still adapted to our ancestral environment as hunter-gatherers. Moreover, institutions are built with the available elements, which include our instincts. A deeper understanding of both aspects, their adaptive function and this recruitment of ancestral instincts, will add greatly to our ability to manage institutions.

On the complexity of rationalizing behavior

We study the complexity of rationalizing choice behavior. We do so by analyzing two polar cases, and a number of intermediate ones. In our most structured case, that is where choice behavior is defined in universal choice domains and satisfies the "weak axiom of revealed preference," finding the complete preorder rationalizing choice behavior is a simple matter. In the polar case, where no restriction whatsoever is imposed, either on choice behavior or on choice domain, finding the complete preordersthat rationalize behavior turns out to be intractable. We show that the task of finding the rationalizing complete preorders is equivalent to a graph problem. This allows the search for existing algorithms in the graph theory literature, for the rationalization of choice.

Characterization of Human Late Outgrowth Endothelial Progenitor-Derived Cells under Various Flow Conditions.

Background: Endothelial progenitor-derived cells (EPC) are a cell therapy tool in peripheral arterial disease and for re-endothelialization of bypasses and stents. Objective: To assess EPC behavior under flow conditions normally found in vivo. Results: EPC were isolated from human cord blood, cultured on compliant tubes and exposed in an in vitro flow system mimicking hemodynamic environments normally found in medium and large arteries. EPC exposed for 24 h to unidirectional (0.3 ± 0.1 or 6 ± 3 dynes/cm(2)) shear stress oriented along flow direction, while those exposed to bidirectional shear stress (0.3 ± 3 dynes/cm(2)) or static conditions had random orientation. Under bidirectional flow, tissue factor (TF) activity and mRNA expression were significantly increased (2.5- and 7.0-fold) compared to static conditions. Under low shear unidirectional flow TF mRNA increased 4.9 ± 0.5-fold. Similar flow-induced increases were observed for TF in mature umbilical vein-derived endothelial cells. Expression of tissue-type plasminogen activator (t-PA), urokinase (u-PA) and monocyte chemotactic protein 1 (MCP1) were reduced by 40-60% in late outgrowth endothelial progenitor-derived cells (LO-EPC) exposed to any flow environment, while MCP1, but not t-PA or u-PA, was decreased in HUVEC. Conclusions: Flow, in particular bidirectional, modifies the hemostatic balance in LO-EPC with increased TF and decreased plasminogen activator expression.

Regulation of proliferation and differentiation of human fetal bone cells.

During the last decade, extensive research has been performed in the field of orthopedic medicine to develop cell-based therapies for the restoration of injured bone tissue. We previously demonstrated that human primary fetal bone cells (HFBCs) associated with porous scaffolds induced a bone formation in critical calvaria defect; however, the environmental factors regulating their behavior in culture have not been identified. HFBCs (human fetal femur,12 week development) were compared to marrow-derived human mesenchymal stem cells (HMSCs) for their capacity to proliferate and differentiate into osteoblasts under various culture conditions. When cultured in standard alphaMEM medium, PDGF and FGF-2 increased cell proliferation of both cell types. Investigation of the differentiating capacity of HFBCs and HMSCs in a normal culture medium indicated that HFBCs expressed higher expression levels of RUNX2, OSX, and osteogenic markers compared with HMSCs, while SOX9 was expressed at very low levels in both cells types. However, HMSCs, but not HFBCs enhanced osteoblastic markers in response to osteogenic factors. Surprisingly, BMP-2 with osteogenic factors increased cell numbers and reduced osteoblastic differentiation in HFBCs with the opposite effect seen in HMSCs. Associated with a higher expression of osteoblastic markers, HFBCs produced a higher calcified extra cellular matrix compared with HMSCs. Taken together, data presented in this study suggest that HFBCs have characteristics of osteoprecursor cells that are more advanced in their osteogenesis development compared with mesenchymal stem cells, making fetal cells an interesting biological tool for treatment of skeletal defects and diseases.

Modeling the impact of lesions in the human brain.

Lesions of anatomical brain networks result in functional disturbances of brain systems and behavior which depend sensitively, often unpredictably, on the lesion site. The availability of whole-brain maps of structural connections within the human cerebrum and our increased understanding of the physiology and large-scale dynamics of cortical networks allow us to investigate the functional consequences of focal brain lesions in a computational model. We simulate the dynamic effects of lesions placed in different regions of the cerebral cortex by recording changes in the pattern of endogenous ("resting-state") neural activity. We find that lesions produce specific patterns of altered functional connectivity among distant regions of cortex, often affecting both cortical hemispheres. The magnitude of these dynamic effects depends on the lesion location and is partly predicted by structural network properties of the lesion site. In the model, lesions along the cortical midline and in the vicinity of the temporo-parietal junction result in large and widely distributed changes in functional connectivity, while lesions of primary sensory or motor regions remain more localized. The model suggests that dynamic lesion effects can be predicted on the basis of specific network measures of structural brain networks and that these effects may be related to known behavioral and cognitive consequences of brain lesions.

The overexpression of SOX2 affects the migration of human teratocarcinoma cell line NT2/D1.

The altered expression of the SOX2 transcription factor is associated with oncogenic or tumor suppressor functions in human cancers. This factor regulates the migration and invasion of different cancer cells. In this study we investigated the effect of constitutive SOX2 overexpression on the migration and adhesion capacity of embryonal teratocarcinoma NT2/D1 cells derived from a metastasis of a human testicular germ cell tumor. We detected that increased SOX2 expression changed the speed, mode and path of cell migration, but not the adhesion ability of NT2/D1 cells. Additionally, we demonstrated that SOX2 overexpression increased the expression of the tumor suppressor protein p53 and the HDM2 oncogene. Our results contribute to the better understanding of the effect of SOX2 on the behavior of tumor cells originating from a human testicular germ cell tumor. Considering that NT2/D1 cells resemble cancer stem cells in many features, our results could contribute to the elucidation of the role of SOX2 in cancer stem cells behavior and the process of metastasis.

Self-similar community structure in a network of human interactions

We propose a procedure for analyzing and characterizing complex networks. We apply this to the social network as constructed from email communications within a medium sized university with about 1700 employees. Email networks provide an accurate and nonintrusive description of the flow of information within human organizations. Our results reveal the self-organization of the network into a state where the distribution of community sizes is self-similar. This suggests that a universal mechanism, responsible for emergence of scaling in other self-organized complex systems, as, for instance, river networks, could also be the underlying driving force in the formation and evolution of social networks.

Behavior of Eucalyptus urophylla and Eucalyptus citriodora Seedlings Grown in Soil Contaminated by Arsenate

ABSTRACT Persistent areas of tailings and deposits from coal and gold mining may present high levels of arsenic (As), mainly in the arsenate form, endangering the environment and human health. The establishment of vegetation cover is a key step to reclaiming these environments. Thus, this study aimed to evaluate the potential of Eucalyptus urophylla and E. citriodora seedlings for use in phytoremediation programs of arsenate-contaminated areas. Soil samples were incubated at increasing rates (0, 50, 100, 200 and 400 mg dm-3) of arsenic (arsenate form, using Na2HAsO4) for 15 days. The seedlings were produced in a substrate (vermiculite + sawdust) and were transplanted to the pots with soil three months after seed germination. The values of plant height and diameter were taken during transplanting and 30, 60 and 90 days after transplanting. In the last evaluation, the total leaf area and biomass of shoots and roots were also determined. The values of available As in soil which caused a 50 % dry matter reduction (TS50%), the As translocation index (TI) from the roots to the shoot of the plants, and its bioconcentration factor (BF) were also calculated. Higher levels of arsenate in the soil significantly reduced the dry matter production of roots and shoots and the height of both species, most notably in E. urophylla plants. The highest levels of As were found in the root, with higher values for E. citriodora (ranging from 253.86 to 400 mg dm-3). The TI and BF were also reduced with As doses, but the values found in E. citriodora were significantly higher than in E. urophylla. E. citriodora plants presented a higher capacity to tolerate As and translocate it to the shoot than E. urophylla. Although these species cannot be considered as hyperaccumulators of As, E. citriodora presented the potential to be used in phytoremediation programs in arsenate-contaminated areas due to the long-term growth period of this species.

Affective state and voice : cross-cultural assessment of speaking behavior and voice sound characteristics : a normative multicenter study of 577 + 36 healthy subjects

BACKGROUND: Human speech is greatly influenced by the speakers' affective state, such as sadness, happiness, grief, guilt, fear, anger, aggression, faintheartedness, shame, sexual arousal, love, amongst others. Attentive listeners discover a lot about the affective state of their dialog partners with no great effort, and without having to talk about it explicitly during a conversation or on the phone. On the other hand, speech dysfunctions, such as slow, delayed or monotonous speech, are prominent features of affective disorders. METHODS: This project was comprised of four studies with healthy volunteers from Bristol (English: n = 117), Lausanne (French: n = 128), Zurich (German: n = 208), and Valencia (Spanish: n = 124). All samples were stratified according to gender, age, and education. The specific study design with different types of spoken text along with repeated assessments at 14-day intervals allowed us to estimate the 'natural' variation of speech parameters over time, and to analyze the sensitivity of speech parameters with respect to form and content of spoken text. Additionally, our project included a longitudinal self-assessment study with university students from Zurich (n = 18) and unemployed adults from Valencia (n = 18) in order to test the feasibility of the speech analysis method in home environments. RESULTS: The normative data showed that speaking behavior and voice sound characteristics can be quantified in a reproducible and language-independent way. The high resolution of the method was verified by a computerized assignment of speech parameter patterns to languages at a success rate of 90%, while the correct assignment to texts was 70%. In the longitudinal self-assessment study we calculated individual 'baselines' for each test person along with deviations thereof. The significance of such deviations was assessed through the normative reference data. CONCLUSIONS: Our data provided gender-, age-, and language-specific thresholds that allow one to reliably distinguish between 'natural fluctuations' and 'significant changes'. The longitudinal self-assessment study with repeated assessments at 1-day intervals over 14 days demonstrated the feasibility and efficiency of the speech analysis method in home environments, thus clearing the way to a broader range of applications in psychiatry. © 2014 S. Karger AG, Basel.

Integrated methodologies to study human transcriptional regulation from functional genomics data

Abstract : The human body is composed of a huge number of cells acting together in a concerted manner. The current understanding is that proteins perform most of the necessary activities in keeping a cell alive. The DNA, on the other hand, stores the information on how to produce the different proteins in the genome. Regulating gene transcription is the first important step that can thus affect the life of a cell, modify its functions and its responses to the environment. Regulation is a complex operation that involves specialized proteins, the transcription factors. Transcription factors (TFs) can bind to DNA and activate the processes leading to the expression of genes into new proteins. Errors in this process may lead to diseases. In particular, some transcription factors have been associated with a lethal pathological state, commonly known as cancer, associated with uncontrolled cellular proliferation, invasiveness of healthy tissues and abnormal responses to stimuli. Understanding cancer-related regulatory programs is a difficult task, often involving several TFs interacting together and influencing each other's activity. This Thesis presents new computational methodologies to study gene regulation. In addition we present applications of our methods to the understanding of cancer-related regulatory programs. The understanding of transcriptional regulation is a major challenge. We address this difficult question combining computational approaches with large collections of heterogeneous experimental data. In detail, we design signal processing tools to recover transcription factors binding sites on the DNA from genome-wide surveys like chromatin immunoprecipitation assays on tiling arrays (ChIP-chip). We then use the localization about the binding of TFs to explain expression levels of regulated genes. In this way we identify a regulatory synergy between two TFs, the oncogene C-MYC and SP1. C-MYC and SP1 bind preferentially at promoters and when SP1 binds next to C-NIYC on the DNA, the nearby gene is strongly expressed. The association between the two TFs at promoters is reflected by the binding sites conservation across mammals, by the permissive underlying chromatin states 'it represents an important control mechanism involved in cellular proliferation, thereby involved in cancer. Secondly, we identify the characteristics of TF estrogen receptor alpha (hERa) target genes and we study the influence of hERa in regulating transcription. hERa, upon hormone estrogen signaling, binds to DNA to regulate transcription of its targets in concert with its co-factors. To overcome the scarce experimental data about the binding sites of other TFs that may interact with hERa, we conduct in silico analysis of the sequences underlying the ChIP sites using the collection of position weight matrices (PWMs) of hERa partners, TFs FOXA1 and SP1. We combine ChIP-chip and ChIP-paired-end-diTags (ChIP-pet) data about hERa binding on DNA with the sequence information to explain gene expression levels in a large collection of cancer tissue samples and also on studies about the response of cells to estrogen. We confirm that hERa binding sites are distributed anywhere on the genome. However, we distinguish between binding sites near promoters and binding sites along the transcripts. The first group shows weak binding of hERa and high occurrence of SP1 motifs, in particular near estrogen responsive genes. The second group shows strong binding of hERa and significant correlation between the number of binding sites along a gene and the strength of gene induction in presence of estrogen. Some binding sites of the second group also show presence of FOXA1, but the role of this TF still needs to be investigated. Different mechanisms have been proposed to explain hERa-mediated induction of gene expression. Our work supports the model of hERa activating gene expression from distal binding sites by interacting with promoter bound TFs, like SP1. hERa has been associated with survival rates of breast cancer patients, though explanatory models are still incomplete: this result is important to better understand how hERa can control gene expression. Thirdly, we address the difficult question of regulatory network inference. We tackle this problem analyzing time-series of biological measurements such as quantification of mRNA levels or protein concentrations. Our approach uses the well-established penalized linear regression models where we impose sparseness on the connectivity of the regulatory network. We extend this method enforcing the coherence of the regulatory dependencies: a TF must coherently behave as an activator, or a repressor on all its targets. This requirement is implemented as constraints on the signs of the regressed coefficients in the penalized linear regression model. Our approach is better at reconstructing meaningful biological networks than previous methods based on penalized regression. The method is tested on the DREAM2 challenge of reconstructing a five-genes/TFs regulatory network obtaining the best performance in the "undirected signed excitatory" category. Thus, these bioinformatics methods, which are reliable, interpretable and fast enough to cover large biological dataset, have enabled us to better understand gene regulation in humans.

Unraveling dynamics of human physical activity patterns in chronic pain conditions.

Chronic pain is a complex disabling experience that negatively affects the cognitive, affective and physical functions as well as behavior. Although the interaction between chronic pain and physical functioning is a well-accepted paradigm in clinical research, the understanding of how pain affects individuals' daily life behavior remains a challenging task. Here we develop a methodological framework allowing to objectively document disruptive pain related interferences on real-life physical activity. The results reveal that meaningful information is contained in the temporal dynamics of activity patterns and an analytical model based on the theory of bivariate point processes can be used to describe physical activity behavior. The model parameters capture the dynamic interdependence between periods and events and determine a 'signature' of activity pattern. The study is likely to contribute to the clinical understanding of complex pain/disease-related behaviors and establish a unified mathematical framework to quantify the complex dynamics of various human activities.

Linear random knots and their scaling behavior

We present here a nonbiased probabilistic method that allows us to consistently analyze knottedness of linear random walks with up to several hundred noncorrelated steps. The method consists of analyzing the spectrum of knots formed by multiple closures of the same open walk through random points on a sphere enclosing the walk. Knottedness of individual "frozen" configurations of linear chains is therefore defined by a characteristic spectrum of realizable knots. We show that in the great majority of cases this method clearly defines the dominant knot type of a walk, i.e., the strongest component of the spectrum. In such cases, direct end-to-end closure creates a knot that usually coincides with the knot type that dominates the random closure spectrum. Interestingly, in a very small proportion of linear random walks, the knot type is not clearly defined. Such walks can be considered as residing in a border zone of the configuration space of two or more knot types. We also characterize the scaling behavior of linear random knots.

Resistance to extreme strategies, rather than prosocial preferences, can explain human cooperation in public goods games.

The results of numerous economic games suggest that humans behave more cooperatively than would be expected if they were maximizing selfish interests. It has been argued that this is because individuals gain satisfaction from the success of others, and that such prosocial preferences require a novel evolutionary explanation. However, in previous games, imperfect behavior would automatically lead to an increase in cooperation, making it impossible to decouple any form of mistake or error from prosocial cooperative decisions. Here we empirically test between these alternatives by decoupling imperfect behavior from prosocial preferences in modified versions of the public goods game, in which individuals would maximize their selfish gain by completely (100%) cooperating. We found that, although this led to higher levels of cooperation, it did not lead to full cooperation, and individuals still perceived their group mates as competitors. This is inconsistent with either selfish or prosocial preferences, suggesting that the most parsimonious explanation is imperfect behavior triggered by psychological drives that can prevent both complete defection and complete cooperation. More generally, our results illustrate the caution that must be exercised when interpreting the evolutionary implications of economic experiments, especially the absolute level of cooperation in a particular treatment.

A novel population of human melanoma-specific CD8 T cells recognizes Melan-AMART-1 immunodominant nonapeptide but not the corresponding decapeptide.

HLA-A2-restricted cytolytic T cells specific for the immunodominant human tumor Ag Melan-A(MART-1) can kill most HLA-matched melanoma cells, through recognition of two naturally occurring antigenic variants, i.e., Melan-A nonamer AAGIGILTV and decamer EAAGIGILTV peptides. Several previous studies have suggested a high degree of TCR cross-reactivity to the two peptides. In this study, we describe for the first time that some T cell clones are exclusively nonamer specific, because they are not labeled by A2/decamer-tetramers and do not recognize the decamer when presented endogenously. Functional assays with peptides gave misleading results, possibly because decamers were cleaved by exopeptidases. Interestingly, nonapeptide-specific T cell clones were rarely Valpha2.1 positive (only 1 of 19 clones), in contrast to the known strong bias for Valpha2.1-positive TCRs found in decamer-specific clones (59 of 69 clones). Molecular modeling revealed that nonapeptide-specific TCRs formed unfavorable interactions with the decapeptide, whereas decapeptide-specific TCRs productively created a hydrogen bond between CDR1alpha and glutamic acid (E) of the decapeptide. Ex vivo analysis of T cells from melanoma metastases demonstrated that both nonamer and decamer-specific T cells were enriched to substantial frequencies in vivo, and representative clones showed efficient tumor cell recognition and killing. We conclude that the two peptides should be regarded as distinct epitopes when analyzing tumor immunity and developing immunotherapy against melanoma.