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Background: Quality of life and psychological well-being are readily hampered by depression. The changes that students face during college life impact their psychological health and well-being, including the emergence of mental health problems like depression Aim: To determine the relationship between depressive symptoms, sociodemographic parameters and psychological well-being in undergraduate university students. Material and Methods: Five hundred eighty university students of both sexes, from the Metropolitan and IX Regions of Chile answered the Beck Depression Inventory (BDI-IA) and the Ryff's psychological well-being scale. Results: Twenty eight percent of respondents had clinically significant depressive symptoms, and these were more frequent in women. There was an inverse and statistically significant relationship between psychological well-being and depressive symptoms. This fact was especially marked in dimensions of autonomy, positive relationships with others and purpose in life. Conclusions: There is a high frequency of depressive symptoms among these students. We discuss whether psychological well-being and depressive symptomatology represent two extremes within a continuum or they are two independent dimensions that can account for differential causal mechanisms linked to mental health and illness.

Collective cell migration is fundamental for life and a hallmark of cancer. Neural crest (NC) cells migrate collectively, but the mechanisms governing this process remain controversial. Previous analyses in Xenopus indicate that cranial NC (CNC) cells are a homogeneous population relying on cell-cell interactions for directional migration, while chick embryo analyses suggest a heterogeneous population with leader cells instructing directionality. Our data in chick and zebrafish embryos show that CNC cells do not require leader cells for migration and all cells present similar migratory capacities. In contrast, laser ablation of trunk NC (TNC) cells shows that leader cells direct movement and cell-cell contacts are required for migration. Moreover, leader and follower identities are acquired before the initiation of migration and remain fixed thereafter. Thus, two distinct mechanisms establish the directionality of CNC cells and TNC cells. This implies the existence of multiple molecular mechanisms for collective cell migration.

International audience; The Wnt/beta signaling pathway has an important role in neuroprotection and bone formation. The activation of this pathway induces the accumulation of beta-catenin in the nucleus of the cell, which interacts with a TCF/LEF transcription factor to activate the expression of the so called Wnt target genes. Some proteins implied in neuroprotection such as CamK4, and other ones related to bone formation, e.g. Runx2, are Wnt targets. Modeling the stimulatory effects of the Wnt pathway on neuroprotection functions and bone formation allow us to analyze in silico the physiological responses to treatments of degenerative disorders such as Alzheimer's disease and osteoporosis. To obtain in-silico new Wnt target genes and insights about regulation, we built an statistical method based on CART. It is trained by the information about the transcription factor binding site motifs in the nearby regions of known Wnt target genes. Between the new Wnt target, we found genes that protect cells against amyloid beta toxicity: e.g. calcium/calmodulin-dependent protein kinase IV (CamK4), for which there exist strong evidences for up-regulation in response to both Wnt ligands and lithium.

International audience; Nowadays the stored information of non-coding human genome regions is being strongly exploited to model the regulation processes. The key to explain complex biological responses, to anticipate and to treat diseases is to understand the regulation factors and the interactions with genes. I summarize the recently published work, developed by C. Hodar, myself, M. Colombres et al. It uses a statistical point of view to study the Wnt pathway that is mainly implicated in cell differentiation, and diseases such as Alzheimer`s (AD) and cancer. We obtain insights on new human genome regions being relevant to control AD or other neurodegenerative disorders. We construct a statistical method based on multiple Classification Trees (CART) to identify new Wnt/beta-catenin pathway target genes, by only using information of known Wnt target (positive) genes and it considers as decision variables the presence of transcription factor binding site motifs in the upstream region of each gene. We propose 89 new Wnt/beta-catenin pathway target genes, we found a group expressed in brain tissue that could be involved in diverse responses to neurodegenerative diseases, like AD. These genes represent new candidates to protect cells against amyloid beta; toxicity, maybe associated to the neuroprotective role of the Wnt signaling pathway and other ones related with cancer. The most relevant were calcium/calmodulin-dependent protein kinase IV (CamK4), with strong evidences for up-regulation in response to both Wnt ligands and lithium, and tropomyosin 1 (alpha) that is associated with neurofibrillary pathology of AD. Our strategy proved to be effective and robust to identify new Wnt/beta-catenin pathway targets. In silico results were biologically validated by RT-qPCR in a sample. Several of the genes represent a new group of transcriptional dependent targets of the canonical Wnt pathway, that could be involved in pathophysiology related to Alzheimer.

The main aim of this thesis is to develop an approach that allows us to describe biological systems with theoretical sustenance and good results in practice. Biological functions are the result of the interaction of many processes, that connect different hierarchy levels going from macroscopic to microscopic level. Each process works in different way, with its own goal, complexity and hierarchy level. In addition, it is common to observe that changes in the conditions, such as nutrients or environment, modify the behavior of the systems. So, to describe the behavior of a biological system over time, it is convenient to combine different types of models: continuous models for gradual changes, discrete models for instantaneous changes, deterministic models for completely predictable behaviors, and stochastic or non- deterministic models to describe behaviors with imprecise or incomplete information. In this thesis we use the theory of Composition and Hybrid Systems as basis, and the BioRica framework as tool to model biological systems and analyze their emergent properties in silico. With respect to Hybrid Systems, we considered continuous models given by sets of differential equations or more general dynamics. We used Stochastic Transition Systems to describe the dynamics of model changes, allowing coe fficient switches that control the parameters of the continuous model, and strong switches that choose different models. Composition, reconciliation and reusing of models allow us to build complete and consistent descriptions of complex biological systems by combining them. Compositions of hybrid systems are hybrid systems, and the re nement of a model forming part of a composed system results in a re nement of the composed system. To implement our approach ideas we complemented the theory of our approach with the improving of the BioRica framework. We contributed to do that giving a BioRica speci cation of Hybrid Systems that assures integrity of models, allowing composition, reconciliation, and reuse of models with SBML speci cation. We applied our approach to describe two systems: wine fermentation kinetics, and cell fate decisions leading to bone and fat formation. In the case of wine fermentation, we reused known models that describe the responses of yeasts cells to different temperatures, quantities of resources and toxins, and we reconciled these models choosing the model with best adjustment to experimental data depending on the initial conditions and fermentation variable. The resulting model can be applied to avoid process problems as stuck and sluggish fermentations. With respect to cell fate decisions the idea is very ambitious. By using accurate models to predict the bone and fat formation in response to activation of pathways such as the Wnt pathway, and changes of conditions affecting these functions such as increments in Homocysteine, one can analyze the responses to treatments for osteoporosis and other bone mass disorders. We think that here we are giving a first step to obtain in silico evaluations of medical treatments before testing them in vivo or in vitro.; Les Fonctions biologiques sont le résultat de l'interaction de beaucoup de processus, avec differents objectives, complexités, niveaux d'hiérarchie, et changements de conditions que modi ent le comportement de systèmes. Nous utilisons des équations diferenciales ou dynamiques plus générales, et Stochastic Systèmes de Transition pour décrire la dynamique de changements des modèles. La composition, réconciliation et reutilisation des modèles nous permettent d'obtenir des descriptions de systèmes biologiques complètes et compatibles et leur combiner. Notre spéci cation de Systèmes Hybrides avec BioRica assures l'intégrité de modèles, et implement notre approche. Nous appliquons notre approche pour décrire in-silico deux systèmes: la dynamique de la fermentation du vin, et des décisions cellulaires associées à la formation de tissu d'os.

National audience; This article presents an initial study of the Guyton Circulatory Model using BioRica. This model consists of 18 connected modules, each of which caracterise a separate physiological subsystem. We have focused the present analysis in the Renin- Angiotensin-Aldosterone System (RAAS). The use of BioRica allowed us to build an hierarchical model for this system by means of directly mapping modules to BioRica nodes. The results of each node were validated by comparison with published results.