A hierarchical approach to model parameter optimization for developmental systems.

In the context of Systems Biology, computer simulations of gene regulatory networks provide a powerful tool to validate hypotheses and to explore possible system behaviors. Nevertheless, modeling a system poses some challenges of its own: especially the step of model calibration is often difficult due to insufficient data. For example when considering developmental systems, mostly qualitative data describing the developmental trajectory is available while common calibration techniques rely on high-resolution quantitative data. Focusing on the calibration of differential equation models for developmental systems, this study investigates different approaches to utilize the available data to overcome these difficulties. More specifically, the fact that developmental processes are hierarchically organized is exploited to increase convergence rates of the calibration process as well as to save computation time. Using a gene regulatory network model for stem cell homeostasis in Arabidopsis thaliana the performance of the different investigated approaches is evaluated, documenting considerable gains provided by the proposed hierarchical approach.

Stochastic stability and the evolution of coordination in spatially structured populations.

Animals can often coordinate their actions to achieve mutually beneficial outcomes. However, this can result in a social dilemma when uncertainty about the behavior of partners creates multiple fitness peaks. Strategies that minimize risk ("risk dominant") instead of maximizing reward ("payoff dominant") are favored in economic models when individuals learn behaviors that increase their payoffs. Specifically, such strategies are shown to be "stochastically stable" (a refinement of evolutionary stability). Here, we extend the notion of stochastic stability to biological models of continuous phenotypes at a mutation-selection-drift balance. This allows us to make a unique prediction for long-term evolution in games with multiple equilibria. We show how genetic relatedness due to limited dispersal and scaled to account for local competition can crucially affect the stochastically-stable outcome of coordination games. We find that positive relatedness (weak local competition) increases the chance the payoff dominant strategy is stochastically stable, even when it is not risk dominant. Conversely, negative relatedness (strong local competition) increases the chance that strategies evolve that are neither payoff nor risk dominant. Extending our results to large multiplayer coordination games we find that negative relatedness can create competition so extreme that the game effectively changes to a hawk-dove game and a stochastically stable polymorphism between the alternative strategies evolves. These results demonstrate the usefulness of stochastic stability in characterizing long-term evolution of continuous phenotypes: the outcomes of multiplayer games can be reduced to the generic equilibria of two-player games and the effect of spatial structure can be analyzed readily.

Etude des liens entre l'alexithymie, l'expérience dépressive et la dépendance interpersonnelle chez des sujets addictifs [Relationships between alexithymia, depression and interpersonal dependency in addictive subjects].

In the scientific literature, the term of addiction is currently used to describe a whole range of phenomena characterized by an irresistible urge to engage in a series of behaviors carried out in a repetitive and persistent manner despite accruing adverse somatic, psychological and social consequences for the individual. It has been suggested that subjects presenting such behaviors would share specific features of personality which support the appearance or are associated with these addictive behaviors. Dimensions such as alexithymia and depression have been particularly well investigated. The aim of this study was to explore the hypothesis of a specific psychopathological model relating alexithymia and depression in different addictive disorders such as alcoholism, drug addiction or eating disorders. Alexithymic and depressive dimensions were explored and analyzed through the statistical tool of path analysis in a large clinical sample of addicted patients and controls. The results of this statistical method, which tests unidirectional causal relationships between a certain number of observed variables, showed a good adjustment between the observed data and the ideal model, and support the hypothesis that a depressive dimension can facilitate the development of dependence in vulnerable alexithymic subjects. These results can have clinical implications in the treatment of addictive disorders.

The association between cigarettes smoking, cannabis use and alcohol consumption in a population of young men: results of a population-based survey.

BACKGROUND: Cigarette smoking is often initiated at a young age as well as other risky behaviors such as alcohol drinking, cannabis and other illicit drugs use. Some studies suggest that cigarette smoking may have an influence on other risky behaviors but little is known about the chronology of occurrence of those different habits. The aim of this study was to assess, by young men, what were the other risky behaviors associated with cigarette smoking and the joint prevalence and chronology of occurrence of those risky behaviors. METHODS: Cross-sectional analyses of a population-based census of 3526 young men attending the recruitment for the Swiss army, aged between 17 and 25 years old (mean age: 19 years old), who filled a self reported questionnaire about their alcohol, cigarettes, cannabis and other illicit drugs habits. Actual smoking was defined as either regular smoking (¡Ý1 cigarette/day, on every day) or occasional smoking, binge drinking as six or more drinks at least twice a month, at risk drinking as 21 drinks or more per week, recent cannabis use as cannabis consumption at least once during the last month, and use of illicit drugs as consumption once or more of illicit drugs other than cannabis. Age at begin was defined as age at first use of cannabis or cigarette smoking. RESULTS: In this population of young men, the prevalence of actual smoking was 51.2% (36.5% regular smoking, 14.6% occasionnal smoking). Two third of participamnts (60.1%) declared that they ever used cannabis, 25.2% reported a recent use of cannabis. 53.8% of participants had a risky alcohol consumption considered as either binge or at risk drinking. Cigarette smoking was significantly associated with recent cannabis use (Odds Ratio (OR): 3.85, 95% Confidence Interval (CI): 3.10- 4.77), binge drinking (OR: 3.48, 95% CI: 3.03-4.00), at risk alcohol drinking (OR: 4.04, 95% CI: 3.12-5.24), and ever use of illicit drugs (OR: 4.34, 95% CI: 3.54-5.31). In a multivariate logistic regression, odds ratios for smoking were increased for cannabis users (OR 3.10,, 95% CI: 2.48-3.88), binge drinkers (OR: 1.77, 95% CI: 1.44-2.17), at risk alcohol drinkers (OR 2.26, 95% CI: 1.52-3.36) and ever users of illicit drugs (OR: 1.56, 95% CI: 1.20-2.03). The majority of young men (57.3%) initiated smoking before cannabis and mean age at onset was 13.4 years old, whereas only 11.1% began to use cannabis before smoking cigarettes and mean age at onset was slightly older (14.4 years old). 31.6% started both cannabis and tobacco at the same age (15 years old). About a third of participants (30.5%) did have a cluster of risky behaviours (smoking, at risk drinking, cannabis use) and 11.0% did cumulate smoking, drinking, cannabis and ever use of illegal drugs. More than half of the smokers (59.6%) did cumulate cannabis use and at risk alcohol drinking whereas only 18.5% of non-smokers did. CONCLUSIONS: The majority of young smokers initiated their risky behaviors by first smoking and then by other psychoactive drugs. Smokers have an increased risk to present other risky behaviors such as cannabis use, at risk alcohol consumtion and illicit drug use compared to nonsmokers. Prevention by young male adults should focus on smoking and also integrate interventions on other risky behaviors.

Supervised injection services : what has been demonstrated? : a systematic literature review

BACKGROUND: Supervised injection services (SISs) have been developed to promote safer drug injection practices, enhance health-related behaviors among people who inject drugs (PWID), and connect PWID with external health and social services. Nevertheless, SISs have also been accused of fostering drug use and drug trafficking. AIMS: To systematically collect and synthesize the currently available evidence regarding SIS-induced benefits and harm. METHODS: A systematic review was performed via the PubMed, Web of Science, and ScienceDirect databases using the keyword algorithm [("SUPERVISED" OR "SAFER") AND ("INJECTION" OR "INJECTING" OR "SHOOTING" OR "CONSUMPTION") AND ("FACILITY" OR "FACILITIES" OR "ROOM" OR "GALLERY" OR "CENTRE" OR "SITE")]. RESULTS: Seventy-five relevant articles were found. All studies converged to find that SISs were efficacious in attracting the most marginalized PWID, promoting safer injection conditions, enhancing access to primary health care, and reducing the overdose frequency. SISs were not found to increase drug injecting, drug trafficking or crime in the surrounding environments. SISs were found to be associated with reduced levels of public drug injections and dropped syringes. Of the articles, 85% originated from Vancouver or Sydney. CONCLUSION: SISs have largely fulfilled their initial objectives without enhancing drug use or drug trafficking. Almost all of the studies found in this review were performed in Canada or Australia, whereas the majority of SISs are located in Europe. The implementation of new SISs in places with high rates of injection drug use and associated harms appears to be supported by evidence.