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Microbiome metabolic modeling as a tool for innovation in fermented foods
No full textInternational audienceAt the crossroads of a growing interest in fermented foods as part of a healthy, sustainable diet and advances in multi-omics technologies stands the need for developing new types of fermented foods while improving traditional ones. The scientific path toward these challenges lies in our capacity to rationalize and predict microbial interactions. For this, genome or metagenome-scale metabolic modeling represents a promising approach. We assess its benefits and limits through rare examples in the field of food microbiomes and advocate for community-level metabolic engineering as the superior strategy. We underline their power as a cornerstone in comprehensive and rational strategies for optimization of microbial consortia assembly, whether they are used in bottom-up or top-down approaches. We raise the challenges and bottlenecks of integrating the dynamics of microbial communities and present how we foresee their potential for shaping the future of fermented foods and regulatory science, bridging gaps between knowledge and innovation
Relations entre ruralité et biodiversité. Le succès de la patrimonialisation en commun de la plaine de Versaillespour une meilleure protection de sa biodiversité
No full textInternational audienc
High-frequency fluorescence monitoring in karst aquifers: A multivariate approach for early detection of anthropogenic contamination of water resources
No full textInternational audienceKarst aquifers play an essential role in drinking water supply, but their vulnerability to anthropogenic pollution, particularly during rainfall events, requires adapted monitoring methods. In this study, we developed an approach combining high-frequency in situ measurements and laboratory analyses to characterise the intensity and occurrence of organic matter fluorescence peaks, in particular Tryptophan-Like Fluorescence (TLF) peaks, associated with faecal contamination. We adapted a background noise correction method based on multiple regression applied to multispectral signals from field fluorometers. A specific calibration in TLF equivalents of the signals from an optical sensor measuring fluorescence at 285 nm is used to quantify contamination peaks. This method was tested on a dataset including 95 samples analysed in the laboratory and high-frequency data spanning 2015–2025 at 15-minute intervals from the Lez karst spring (France), showing its effectiveness in correcting optical interferences and detecting low pollution episodes. The analysis of time series underlined the importance of high-frequency monitoring to capture rapid water flow dynamics, while confirming the indispensable complementarity of laboratory analyses to better discriminate the fluorophores controlling the intensity of high-frequency in situ signals. The results highlight critical contamination periods, particularly in autumn and spring, and confirms the suitability of TLF for Early Warning System (EWS) applications. This approach broadens the methods used for water quality management in karst environments and proposes a methodological framework transferable to other sites
Modeling breeding programs considering social behavior in large groups of farmed fish
No full textBreeding programs are essential in aquaculture, improving economically and environmentally important traits. In aquaculture systems, animals are raised in large groups, where social interactions are frequent and can influence individual performance. In these circumstances, indirect genetic effects can play an important role in the response to selection, and consequently, their effects on selection outcomes must be analyzed.This study aimed to evaluate the implications of heterogeneous social interaction effects on fish breeding programs using stochastic simulations. We simulated a fish breeding program with 2000 selection candidates from 1000 families formed by a partial mating design of 100 males and 100 females. Social interactions were simulated, affected by the target phenotype and two latent-personality traits. We investigated how genetic gains and phenotypic variances are affected by the magnitude and direction of social interaction effects on the target phenotype, different selection strategies, and the genetic correlations between the target phenotype and personality traits. Our results showed that increased social interaction effects lead to greater phenotypic variability in the target trait. Under mass selection, the genetic means of personality traits change, and these changes depend on the strength and direction of genetic correlations between the focal and personality traits. Conversely, group selection did not increase phenotypic variability but reduced genetic gain for the focal trait compared to mass selection. Moreover, group selection did not alter the genetic means of personality traits. However, this approach increased the rate of inbreeding per generation, which could be mitigated by optimizing the number of families per group..</div
Problèmes d'affectation dans les réseaux de fonctions de coût
No full textInternational audienceTo efficiently solve exact discrete optimization problems, branch and bound algorithms require tight bounds. In constraint programming, for optimization, soft arc consistencies typically derive much stronger bounds than those offered by domain or bound consistencies applied to a cost variable. The reason is that soft local consistencies exchange marginal cost information between variables whereas domain consistencies rely only on shrinking domains, which is less informative. However, CP solvers equipped with soft arc consistencies have so far offered limited support for efficient processing of global constraints. In this work, we show how we can efficiently enforce soft local consistency over the ALLDIFFERENT constraint, relying on algorithms for the Linear Assignment Problem (LAP). We implement this propagator in toulbar2, the state-of-theart weighted CP solver exploiting soft local consistencies for bounding. On problems that include ALLDIFFERENT constraints, we show that, equipped with this new propagator, toulbar2 outperforms state-of-the-art domain consistencybased CP as well as integer programming solvers for the Quadratic Assignment Problem and shows better performance for miniCOP instances of the 2024 XCSP competition with ALLDIFFERENT constraints.</div
: Ce que la science du climat dit — et ce que nous faisons déjà
No full textAllocation prononcée à l’occasion de l’Assemblée Générale de l'AMAP de Bagneux (92)Ce texte ne vise ni à convaincre par l’alarme, ni à prescrire des comportements, mais à mettre en regard ce que dit la science du climat et ce que les AMAPiens pratiquent déjà collectivement. Il est écrit à la fois en tant que chercheur et en tant que membre engagé dans le maintien d’une agriculture paysanne locale
Protein valuation is positively associated with habitual intake of protein of animal origin in a sample of French adults
No full textInternational audienceBalancing our dietary intakes in favour of plant protein sources would reduce overall protein intake. Low-protein diets have shown to reinforce specific appetite for protein. The role of protein appetite as a determinant of the choice of specific protein sources in free-living humans has not been extensively studied, and the relationship between the strength of protein appetite and the amount of protein from various dietary sources has not yet been quantified. We used an on-line questionnaire to measure the association between habitual intakes of principal protein sources and protein valuation in a cohort of healthy French meat-eating adults, aged between 18 and 65 years. Protein valuation is the propensity to systematically prefer foods that are higher in protein and is measured using a 2-alternative forced-choice task. Participants (final sample: N = 86) who had higher habitual intakes of protein displayed a significantly higher protein valuation. There was a significant positive association between protein valuation and intakes of various food groups of animal origin, especially meat, while this association between protein valuation and intake of plant-based foods was negative and significant. Our study suggests that protein valuation may be a determinant of preferences for protein and specific protein sources. Nutritional determinants of protein preferences should be taken into account in the context of a population-wide shift to more plant-based diets in order to facilitate this shift for all
Root phenolics as potential drivers of preformed defenses and reduced disease susceptibility in a paradigm bread wheat mixture
No full textInternational audiencePlant-plant interactions modulate foliar disease susceptibility in intraspecific mixtures. However, the molecular events including signals and responses underlying the reduction in disease susceptibility remain largely unexplored. Here, we developed an experimental system that can abolish root-mediated interactions between plants in a model of bread wheat varietal mixture. We then performed transcriptomic and metabolomic analyses to uncover the molecular responses linked to decreased susceptibility to Septoria tritici blotch in plant-plant interactions. Our analysis revealed that disrupting root chemical interactions impaired the reduction in susceptibility to Septoria and identified phenolic compounds as potential key mediators. The plant-plant interactions under study triggered significant molecular changes in specialized metabolism, biotic interactions, transporters, and responses to resources. Disrupting root interactions canceled both the macroscopic and molecular responses, thus providing a strong link between them. These insights provide a deeper understanding of the molecular basis of plant-plant interactions and the processes involved in reducing disease susceptibility in intraspecific mixtures
Do skewed sex ratios reduce son preference?
No full texthttps://voxdev.org/topic/institutions-political-economy/do-skewed-sex-ratios-reduce-son-preferenc
A Soil–Plant–Atmosphere Continuum model coupled to CFD to simulate plant energy and water exchanges in heterogeneous microclimates
No full textInternational audienceEstimating plant growth conditions in agrivoltaic, agroforestry, or urban environments are applied examples exhibiting the need to consider the intricate relationships between spatially heterogeneous microclimate conditions (short-wave and long-wave radiation, wind, turbulence, and air temperature), plant and soil energy balances with air and water exchanges. To capture these connections, the Soil–Plant–Atmosphere Continuum model from A. Tuzet has been implemented in the computational fluid dynamics software code_saturne, which simulates spatially heterogeneous and time-varying fluid flows, along with short-wave and long-wave radiation. This coupling is compared to experimental measurements from two French sites of the Integrated Carbon Observatory System (ICOS). Our model achieves significant outcomes in assessing energy exchanges, maintaining a relative error of less than 20% compared to ICOS measurements. In addition to accurately reproducing variations of latent and sensible heat fluxes due to radiation, the coupling of the water balance and stomatal conductance models demonstrates its capability to predict the evolution of soil water content over several days. Finally, an extrapolative study of fictive environments with plants beneath obstacles reveals promising opportunities to understand how obstacle-induced shadows and wakes affect plant temperature. This leads the way for further research in agrivoltaic, agroforestry, or urban configurations with spatial scales from approximatively 10m2 up to 1000m2 and temporal scales ranging from single moments to several consecutive days