Using robots to understand social behaviour.

A major challenge in studying social behaviour stems from the need to disentangle the behaviour of each individual from the resulting collective. One way to overcome this problem is to construct a model of the behaviour of an individual, and observe whether combining many such individuals leads to the predicted outcome. This can be achieved by using robots. In this review we discuss the strengths and weaknesses of such an approach for studies of social behaviour. We find that robots-whether studied in groups of simulated or physical robots, or used to infiltrate and manipulate groups of living organisms-have important advantages over conventional individual-based models and have contributed greatly to the study of social behaviour. In particular, robots have increased our understanding of self-organization and the evolution of cooperative behaviour and communication. However, the resulting findings have not had the desired impact on the biological community. We suggest reasons for why this may be the case, and how the benefits of using robots can be maximized in future research on social behaviour.

Co-evolution between sociality and dispersal: The role of synergistic cooperative benefits.

Explaining the evolution of sociality is challenging because social individuals face disadvantages that must be balanced by intrinsic benefits of living in a group. One potential route towards the evolution of sociality may emerge from the avoidance of dispersal, which can be risky in some environments. Although early studies found that local competition may cancel the benefits of cooperation in viscous populations, subsequent studies have identified conditions, such as the presence of kin recognition or specific demographic conditions, under which altruism will still spread. Most of these studies assume that the costs of cooperating outweigh the direct benefits (strong altruism). In nature, however, many organisms gain synergistic benefits from group living, which may counterbalance even costly altruistic behaviours. Here, we use an individual based model to investigate how dispersal and social behaviour co-evolve when social behaviours result in synergistic benefits that counterbalance the relative cost of altruism to a greater extent than assumed in previous models. When the cost of cooperation is high, selection for sociality responds strongly to the cost of dispersal. In particular, cooperation can begin to spread in a population when higher cooperation levels become correlated with lower dispersal tendencies within individuals. In contrast, less costly social behaviours are less sensitive to the cost of dispersal. In line with previous studies, we find that mechanisms of global population control also affect this relationship: when whole patches (groups) go extinct each generation, selection favours a relatively high dispersal propensity, and social behaviours evolve only when they are not very costly. If random individuals within groups experience mortality each generation to maintain a global carrying capacity, on the other hand, social behaviours spread and dispersal is reduced, even when the latter is not costly.

C3-symmetric peptide scaffolds are functional mimetics of trimeric CD40L.

Interaction between CD40, a member of the tumor necrosis factor receptor (TNFR) superfamily, and its ligand CD40L, a 39-kDa glycoprotein, is essential for the development of humoral and cellular immune responses. Selective blockade or activation of this pathway provides the ground for the development of new treatments against immunologically based diseases and malignancies. Like other members of the TNF superfamily, CD40L monomers self-assemble around a threefold symmetry axis to form noncovalent homotrimers that can each bind three receptor molecules. Here, we report on the structure-based design of small synthetic molecules with C3 symmetry that can mimic CD40L homotrimers. These molecules interact with CD40, compete with the binding of CD40L to CD40, and reproduce, to a certain extent, the functional properties of the much larger homotrimeric soluble CD40L. Architectures based on rigid C3-symmetric cores may thus represent a general approach to mimicking homotrimers of the TNF superfamily.

The international development of the RGHQoL: a quality of life measure for recurrent genital herpes.

This paper describes the international development and psychometric testing of the Recurrent Genital Herpes Quality of Life Questionnaire (RGHQoL), a condition-specific quality of life (QoL) instrument. The theoretical foundation for the measure is the needs-based model of QoL and the content of the instrument was derived from in-depth qualitative interviews with relevant patients in the UK. Versions of the RGHQoL were required for the UK, USA, Italy, Germany, France and Denmark for use in international clinical trials. The results indicate that the final 20 item measure has good reliability, internal consistency and validity for all language versions. A small responsiveness study in Denmark suggested that the measure is sensitive to changes in QoL associated with the initiation of suppression treatment for recurrent genital herpes (RGH). It is concluded that the RGHQoL is a valuable instrument for inclusion in clinical trials. The psychometric properties of the instrument are such that it may also be used to monitor the progress of individual patients.

SwissParam: a fast force field generation tool for small organic molecules.

The drug discovery process has been deeply transformed recently by the use of computational ligand-based or structure-based methods, helping the lead compounds identification and optimization, and finally the delivery of new drug candidates more quickly and at lower cost. Structure-based computational methods for drug discovery mainly involve ligand-protein docking and rapid binding free energy estimation, both of which require force field parameterization for many drug candidates. Here, we present a fast force field generation tool, called SwissParam, able to generate, for arbitrary small organic molecule, topologies, and parameters based on the Merck molecular force field, but in a functional form that is compatible with the CHARMM force field. Output files can be used with CHARMM or GROMACS. The topologies and parameters generated by SwissParam are used by the docking software EADock2 and EADock DSS to describe the small molecules to be docked, whereas the protein is described by the CHARMM force field, and allow them to reach success rates ranging from 56 to 78%. We have also developed a rapid binding free energy estimation approach, using SwissParam for ligands and CHARMM22/27 for proteins, which requires only a short minimization to reproduce the experimental binding free energy of 214 ligand-protein complexes involving 62 different proteins, with a standard error of 2.0 kcal mol(-1), and a correlation coefficient of 0.74. Together, these results demonstrate the relevance of using SwissParam topologies and parameters to describe small organic molecules in computer-aided drug design applications, together with a CHARMM22/27 description of the target protein. SwissParam is available free of charge for academic users at www.swissparam.ch.

Influence of learning on range expansion and adaptation to novel habitats.

Learning has been postulated to 'drive' evolution, but its influence on adaptive evolution in heterogeneous environments has not been formally examined. We used a spatially explicit individual-based model to study the effect of learning on the expansion and adaptation of a species to a novel habitat. Fitness was mediated by a behavioural trait (resource preference), which in turn was determined by both the genotype and learning. Our findings indicate that learning substantially increases the range of parameters under which the species expands and adapts to the novel habitat, particularly if the two habitats are separated by a sharp ecotone (rather than a gradient). However, for a broad range of parameters, learning reduces the degree of genetically-based local adaptation following the expansion and facilitates maintenance of genetic variation within local populations. Thus, in heterogeneous environments learning may facilitate evolutionary range expansions and maintenance of the potential of local populations to respond to subsequent environmental changes.

TCRep 3D: an automated in silico approach to study the structural properties of TCR repertoires.

TCRep 3D is an automated systematic approach for TCR-peptide-MHC class I structure prediction, based on homology and ab initio modeling. It has been considerably generalized from former studies to be applicable to large repertoires of TCR. First, the location of the complementary determining regions of the target sequences are automatically identified by a sequence alignment strategy against a database of TCR Vα and Vβ chains. A structure-based alignment ensures automated identification of CDR3 loops. The CDR are then modeled in the environment of the complex, in an ab initio approach based on a simulated annealing protocol. During this step, dihedral restraints are applied to drive the CDR1 and CDR2 loops towards their canonical conformations, described by Al-Lazikani et. al. We developed a new automated algorithm that determines additional restraints to iteratively converge towards TCR conformations making frequent hydrogen bonds with the pMHC. We demonstrated that our approach outperforms popular scoring methods (Anolea, Dope and Modeller) in predicting relevant CDR conformations. Finally, this modeling approach has been successfully applied to experimentally determined sequences of TCR that recognize the NY-ESO-1 cancer testis antigen. This analysis revealed a mechanism of selection of TCR through the presence of a single conserved amino acid in all CDR3β sequences. The important structural modifications predicted in silico and the associated dramatic loss of experimental binding affinity upon mutation of this amino acid show the good correspondence between the predicted structures and their biological activities. To our knowledge, this is the first systematic approach that was developed for large TCR repertoire structural modeling.

Rational design of 4-aryl-1,2,3-triazoles for indoleamine 2,3-dioxygenase 1 inhibition.

Indoleamine 2,3-dioxygenase 1 (IDO1) is an important therapeutic target for the treatment of diseases such as cancer that involve pathological immune escape. Starting from the scaffold of our previously discovered IDO1 inhibitor 4-phenyl-1,2,3-triazole, we used computational structure-based methods to design more potent ligands. This approach yielded highly efficient low molecular weight inhibitors, the most active being of nanomolar potency both in an enzymatic and in a cellular assay, while showing no cellular toxicity and a high selectivity for IDO1 over tryptophan 2,3-dioxygenase (TDO). A quantitative structure-activity relationship based on the electrostatic ligand-protein interactions in the docked binding modes and on the quantum chemically derived charges of the triazole ring demonstrated a good explanatory power for the observed activities.

EADock: docking of small molecules into protein active sites with a multiobjective evolutionary optimization.

In recent years, protein-ligand docking has become a powerful tool for drug development. Although several approaches suitable for high throughput screening are available, there is a need for methods able to identify binding modes with high accuracy. This accuracy is essential to reliably compute the binding free energy of the ligand. Such methods are needed when the binding mode of lead compounds is not determined experimentally but is needed for structure-based lead optimization. We present here a new docking software, called EADock, that aims at this goal. It uses an hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 A around the center of mass of the ligand position in the crystal structure, and on the contrary to other benchmarks, our algorithm was fed with optimized ligand positions up to 10 A root mean square deviation (RMSD) from the crystal structure, excluding the latter. This validation illustrates the efficiency of our sampling strategy, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures could be explained by the presence of crystal contacts in the experimental structure. Finally, the ability of EADock to accurately predict binding modes on a real application was illustrated by the successful docking of the RGD cyclic pentapeptide on the alphaVbeta3 integrin, starting far away from the binding pocket.

Merkel cells and the individuality of friction ridge skin

There is no definite theory yet for the mechanism by which the pattern of epidermal ridges on fingers, palms and soles forming friction ridge skin (FRS) patterns is created. For a long time growth forces in the embryonal epidermis have been believed to be involved in FRS formation. More recent evidence suggests that Merkel cells play an important part in this process as well. Here we suggest a model for the formation of FRS patterns that links Merkel cells to the epidermal stress distribution. The Merkel cells are modeled as agents in an agent based model that move anisotropically where the anisotropy is created by the epidermal stress tensor. As a result ridge patterns are created with pattern defects as they occur in real FRS patterns. As a consequence we suggest why the topology of FRS patterns is indeed unique as the arrangement of pattern defects is sensitive to the initial configuration of Merkel cells.

Nouveau programme de formation en médecine interne générale: implications pour les médecins de premier recours [The new postgraduate training program in general internal medicine: implications for the primary care physician].

The Swiss postgraduate training program in general internal medicine is now designed as a competency-based curriculum. In other words, by the end of their training, the residents should demonstrate a set of predefined competences. Many of those competences have to be learnt in outpatient settings. Thus, the primary care physicians have more than ever an important role to play in educating tomorrows doctors. A competency-based model of training requires a regular assessment of the residents. The mini-CEX (mini-Clinical Evaluation eXercise) is the assessment tool proposed by the Swiss institute for postgraduate and continuing education. The mini-CEX is based on the direct observation of the trainees performing a specific task, as well as on the ensuing feedback. This article aims at introducing our colleagues in charge of residents to the mini-CEX, which is a useful tool promoting the culture of feedback in medical education.

Detailed analysis and follow-up studies of a high-throughput screening for indoleamine 2,3-dioxygenase 1 (IDO1) inhibitors.

Indoleamine 2,3-dioxygenase 1 (IDO1) is a key regulator of immune responses and therefore an important therapeutic target for the treatment of diseases that involve pathological immune escape, such as cancer. Here, we describe a robust and sensitive high-throughput screen (HTS) for IDO1 inhibitors using the Prestwick Chemical Library of 1200 FDA-approved drugs and the Maybridge HitFinder Collection of 14,000 small molecules. Of the 60 hits selected for follow-up studies, 14 displayed IC50 values below 20 μM under the secondary assay conditions, and 4 showed an activity in cellular tests. In view of the high attrition rate we used both experimental and computational techniques to identify and to characterize compounds inhibiting IDO1 through unspecific inhibition mechanisms such as chemical reactivity, redox cycling, or aggregation. One specific IDO1 inhibitor scaffold, the imidazole antifungal agents, was chosen for rational structure-based lead optimization, which led to more soluble and smaller compounds with micromolar activity.

The Implied Book and the Narrative Text. On a Blind Spot in Narratological Theory - from a Media Studies Perspective

The article is concerned with the formal definition of a largely unnoticed factor in narrative structure. Based on the assumptions that (1) the semantics of a written text depend, among other factors, directly on its visual alignment in space, that (2) the formal structure of a text has to meet that of its spatial presentation and that (3) these assumptions hold true also for narrative texts (which, however, in modern times typically conceal their spatial dimensions by a low-key linear layout), it is argued that, how ever low-key, the expected material shape of a given narrative determines the configuration of its plot by its author. The ,implied book' thus denotes an author's historically assumable, not necessarily conscious idea of how his text, which is still in the process of creation, will be dimensionally presented and under these circumstances visually absorbed. Assuming that an author's knowledge of this later (potentially) substantiated material form influences the composition, the implied book is to be understood as a text-genetically determined, structuring moment of the text. Historically reconstructed, it thus serves the methodical analysis of structural characteristics of a completed text.

Changes in the risk of death after HIV seroconversion compared with mortality in the general population.

CONTEXT: Mortality among human immunodeficiency virus (HIV)-infected individuals has decreased dramatically in countries with good access to treatment and may now be close to mortality in the general uninfected population. OBJECTIVE: To evaluate changes in the mortality gap between HIV-infected individuals and the general uninfected population. DESIGN, SETTING, AND POPULATION: Mortality following HIV seroconversion in a large multinational collaboration of HIV seroconverter cohorts (CASCADE) was compared with expected mortality, calculated by applying general population death rates matched on demographic factors. A Poisson-based model adjusted for duration of infection was constructed to assess changes over calendar time in the excess mortality among HIV-infected individuals. Data pooled in September 2007 were analyzed in March 2008, covering years at risk 1981-2006. MAIN OUTCOME MEASURE: Excess mortality among HIV-infected individuals compared with that of the general uninfected population. RESULTS: Of 16,534 individuals with median duration of follow-up of 6.3 years (range, 1 day to 23.8 years), 2571 died, compared with 235 deaths expected in an equivalent general population cohort. The excess mortality rate (per 1000 person-years) decreased from 40.8 (95% confidence interval [CI], 38.5-43.0; 1275.9 excess deaths in 31,302 person-years) before the introduction of highly active antiretroviral therapy (pre-1996) to 6.1 (95% CI, 4.8-7.4; 89.6 excess deaths in 14,703 person-years) in 2004-2006 (adjusted excess hazard ratio, 0.05 [95% CI, 0.03-0.09] for 2004-2006 vs pre-1996). By 2004-2006, no excess mortality was observed in the first 5 years following HIV seroconversion among those infected sexually, though a cumulative excess probability of death remained over the longer term (4.8% [95% CI, 2.5%-8.6%] in the first 10 years among those aged 15-24 years). CONCLUSIONS: Mortality rates for HIV-infected persons have become much closer to general mortality rates since the introduction of highly active antiretroviral therapy. In industrialized countries, persons infected sexually with HIV now appear to experience mortality rates similar to those of the general population in the first 5 years following infection, though a mortality excess remains as duration of HIV infection lengthens.

The evolution of judgement bias in indirect reciprocity.

Indirect reciprocity is a form of reciprocity where help is given to individuals based on their reputation. In indirect reciprocity, bad acts (such as not helping) reduce an individual's reputation while good acts (such as helping) increase an individual's reputation. Studies of indirect reciprocity assume that good acts and bad acts are weighted equally when assessing the reputation of an individual. As different information can be processed in different ways, this is not likely to be the case, and it is possible that an individual could bias an actor's reputation by putting more weight to acts of defection (not helping) than acts of co-operation (helping) or vice versa. We term this difference 'judgement bias', and build an individual-based model of image scoring to investigate the conditions under which it may evolve. We find that, if the benefits of co-operation are small, judgement bias is weighted towards acts perceived to be bad; if the benefits are high, the reverse is true. Our result is consistent under both scoring and standing strategies, and we find that allowing judgement bias to evolve increases the level of co-operation in the population.