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Finding meaning in the meaningless. How narrative meaning-making relates to post-traumatic growth and post-traumatic stress disorder in victims of the Strasbourg Christmas market attack
No full textInternational audienceBackground: Traumatic events may deeply modify one's views on oneself, others and the world. Finding meaning after traumatic events may be determinant to psychological adjustment and post-traumatic growth.Objectives: Our study aims at investigating the association of narrative meaning-making with post-traumatic growth and post-traumatic stress disorder among individuals exposed to a terrorist attack.Methods: We recruited participants exposed to December 2018 Strasbourg Christmas market attack. The participants narrated three memories: their experience of the terrorist attack (TAM) and two self-defining memories (SDMs). Each narrative was assessed in terms of meaning-making. A total meaning score was calculated to express the cumulated presence of meaning in the three memories. Post-traumatic growth and PTSD were assessed by the Post-traumatic Growth Inventory (PTGI) and the Post-traumatic Checklist for DSM-5 (PCL-5), respectively.Results: Thirty-six participants took part to the study and 108 memories were recorded. Post-traumatic growth was relevantly associated with meaning-making for TAMs (Pr (meaning > no meaning) = 0.993) and with the total meaning score (Pr (β > 0) = 0.998); while PTSD was not (Pr (meaning > no meaning) = 0.941 and = 0.618, respectively). In multivariate analyses, both meaning-making for TAMs (Pr (meaning > no meaning) = 0.984) and the total meaning score (Pr (meaning > no meaning) = 0.976) remained associated with post-traumatic growth.Conclusions: A general meaning-making ability after striking life-events may contribute to the emergence of post-traumatic growth after a traumatic event. Our findings suggest new directions emphasizing on meaning-making in trauma-focused therapies
Plant Hydraulic Architecture for a Mechanistic Representation of Soil‐Plant‐Atmosphere Water Transfer in the Land Surface Model ORCHIDEE (r9107)
No full textInternational audienceLand surface models (LSMs) typically represent soil moisture control on stomatal conductance through an empirical sensitivity function, without considering plant hydrology. This study proposes integrating water transfer representation within the soil-plant-atmosphere continuum in the ORCHIDEE land surface model. This new configuration includes vegetation hydraulic architecture and a stomatal control based on leaf water potential ψ leaf ) , along with a mechanistic representation of water absorption by roots via radial diffusion around the roots. An adaptive numerical scheme is implemented to prevent numerical instabilities during hydric stress, reducing hourly instabilities by a factor of 2. The implementation and the standard configuration of ORCHIDEE are calibrated and evaluated at FLUXNET sites with eddy-covariance flux measurements. A detailed assessment is carried out at two well-documented forest sites (FR-Hes and FR-Pue), where both configurations perform similarly regarding the seasonal dynamics of latent heat flux (RMSEs of 16.0 W/m 2 for the potential-based configuration and 15.8 W/m 2 for the standard configuration at FR-Hes). An evaluation of leaf water potential at FR-Pue shows correlations of 0.87 and 0.72 for predawn and midday ψ leaf respectively. A second evaluation across 135 sites from the FLUXNET2015 database highlights similar performances for both configurations. Finally, a global assessment of the differences between the two schemes emphasizes the good performance of the hydraulic architecture model. Overall, the new hydraulic architecture provides a more mechanistic description of stomatal conductance response to soil water stress and paves the way for incorporating physiological processes controlling tree mortality and using in situ observations to calibrate plant responses to water stress.Plain Language Summary Land surfaces models (LSMs), which aim at representing the exchanges between the land surfaces and the atmosphere, usually represent the rate of water exchanges between the vegetation and the atmosphere according to soil water stress defined as an empirical function and without considering the plant water status. Here, we propose to represent the water transfers from the soil-root interface toward the leaves via a hydraulic architecture model, accounting for potential water storage in the plant. This model provides a more mechanistic description of the response of stomatal conductance to soil water stress and opens for the representation of important physiological processes such as cavitation. In order to evaluate the model, a detailed analysis has been performed at two forest sites. It enabled to understand the behavior of the new configuration and to verify its capacity to reproduce observations of water exchanges with the atmosphere. An extended analysis over 135 FLUXNET sites illustrated the overall good performances of the model. Finally, a study at global scale highlighted significant differences between the new hydraulic architecture and the standard model with respect to energy, water and carbon fluxes
Dating ancient iron smelting in West Africa: archaeomagnetism and methodological challenges at Tchogma 1, Togo (17th-20th century)
No full textInternational audienc
Genetic risk-dependent brain markers of resilience to childhood Trauma
No full textInternational audienceResilience to developing emotional disorders is critical for adolescent mental health, especially following childhood trauma. Yet, brain markers of resilience remain poorly understood. By analyzing brain responses to angry faces in a large-scale longitudinal adolescent cohort (IMAGEN), we identified two functional networks located in the orbitofrontal and occipital regions. In girls with high genetic risks for depression, higher orbitofrontal-related network activation was associated with a reduced impact of childhood trauma on emotional symptoms at age 19, whereas in those with low genetic risks, lower occipital-related network activation had a similar association. These findings reveal genetic risk-dependent brain markers of resilience (GRBMR). Longitudinally, the orbitofrontal-related GRBMR predicted subsequent emotional disorders in late adolescence, which were generalizable to an independent prospective cohort (ABCD). These findings demonstrate that high polygenic depression risk relates to activations in the orbitofrontal network and to resilience, with implications for biomarkers and treatment
Etude d’un lot métallurgique (creusets et alliages) issu des fouilles du château de Blain
No full textRapport d'étud
Développement d'un nouvel outil de conception in silico de ligands par fragments avec une stratégie de repositionnement
No full textFragment-Based Ligand Design (FBLD) is a widely adopted approach in academic laboratories and pharmaceutical companies. Frags2Drugs (F2D), an innovative in silico FBLD tool aimed at designing novel protein kinase inhibitors, was previously developed. However, its applicability domain is limited solely to protein kinases, restricting its widespread adoption.This thesis proposes universal Frags2Drugs (uF2D), a structure-based molecular generator which expands the applicability domain of F2D to encompass the entire proteome.The uF2D methodology comprises two distinct components: a fragment hit identification tool and a linker generator. For fragment hit identification, an existing computational FBLD tool named CrystalDock, originally designed for fragment-to-lead optimization, has been thoroughly evaluated, re-implemented, and adapted. Fragment hits are identified by repositioning fragments with similar protein local environment found in cocrystallized protein-ligand complex structures. Multiple datasets have been compiled to systematically evaluate the performance of CrystalDock across varying levels of difficulty. A deep learning-based linker generator, DiffLinker, has also been evaluated.Although the program still requires refinement and parameter optimization, a prototype version of uF2D has been proposed, laying the foundation for future FBLD methodology development.La conception de ligands par fragments (FBLD) est une approche largement adoptée dans les laboratoires académiques et les entreprises pharmaceutiques. Frags2Drugs (F2D), un outil in silico innovant visant à concevoir de nouveaux inhibiteurs de protéines kinases et basé sur l'information structurale de fragments, a déjà été développé. Cependant, son domaine d'application est restreint aux protéines kinases, ce qui limite sa généralisation. Cette thèse propose universal Frags2Drugs (uF2D), un générateur de molécules bioactives tenant compte des structures de protéines, ce qui étend le domaine d'application de F2D à l'ensemble du protéome. La méthodologie uF2D comprend deux composants distincts : un outil d'identification des fragments hits et un générateur de liaisons. Pour l'identification des fragment hits, un outil FBLD computationnel existant, CrystalDock, initialement conçu pour l'optimisation fragment-to-lead, a été évalué, réimplémenté et adapté. Les fragments sont identifiés en repositionnant des fragments présentant un environnement protéique local similaire, présents dans des structures co-cristallisées de complexes protéine-ligand. Plusieurs jeux de données ont été compilés afin d'évaluer systématiquement les performances de CrystalDock à différents niveaux de difficulté. DiffLinker, un générateur de liaisons (linker) basé sur l'apprentissage profond, a également été évalué. Bien que le programme nécessite encore des améliorations et une optimisation de ses paramètres, une version prototype d'uF2D a été présentée, posant les bases du développement futur de la méthodologie FBLD
On-chip photonic crystal tweezers for bacteria and bacteriophage viruses trapping and susceptibility testing
No full textInternational audienc
