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Two domains vs single-domain ERA5 dynamical downscaling with WRF over Euro-Cordex improves precipitation hindcast: A 6-year case study over mainland France for agricultural studies
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Unlocking Probiotic Potential: Physicochemical Approaches to Evaluate Probiotic Bacterial Adhesion Potential to the Intestinal Tract
No full textInternational audienceBacterial adhesion in the gut is critical to evaluate their effectiveness as probiotics. Understanding the bacterial adhesion within the complex gut environment is challenging. This study explores the adhesion mechanisms and the adhesion potential of five selected bacterial strains (Escherichia coli, Lactiplantibacillus plantarum, Faecalibacterium duncaniae, Bifidobacterium longum, and Bifidobacterium longum subsp. infantis) at the initial stages when bacterial cells arriving in the gut, using different physicochemical approaches. Bacterial morphology, rheology, and surface properties were evaluated. Surprisingly, previous methods such as bacterial adhesion to hydrocarbon and the interfacial tension between bacterial suspensions and mineral oil did not fully capture the bacterial adhesion to intestinal mucus. Consequently, this study introduced a novel approach to assess bacterial adhesion to mucus, based on contact angle measurements, calculation of surface tension, and work of adhesion. Interestingly, both small and large intestinal mucus are rather hydrophilic, and thus highly hydrophilic bacteria such as E. coli and B. infantis tend to adhere better. Additionally, a multicriteria evaluation of bacterial adhesion to the gut, from the bulk liquid transport stage until the irreversible adhesion, was proposed. E. coli and B. infantis demonstrated the highest overall adhesion potential in the intestinal tract, followed by Lpb. plantarum, B. longum, and F. duncaniae, respectively. This work contributed original physicochemical approaches to comprehensively examine bacterial adhesion in the gut
Econométrie des données spatiales : enjeux d'identification et perspectives
No full textInternational audienceThis article presents a reflection on the field of spatial data econometrics, emphasizing identification issues of spatial interactions and the perspectives opened by the development of geolocated big data. This branch of econometrics enables the analysis of phenomena in which geographic proximity, neighborhood interdependence, and territorial heterogeneity are structuring factors. While standard models—such as SAR and SDM—allow for the formalization of spatial interactions, their empirical implementation raises major identification challenges. Rigorous identification of spatial effects requires clarifying the nature of interactions, addressing endogeneity concerns, and disentangling spatial dependence from spatial heterogeneity. The paper then discusses the challenges that spatial interactions econometrics methods must address, both within a structural methodological approach and in causal inference models, while also considering inference methods developed in other branches of econometrics. Finally, it highlights that the rise of big spatial data and spatial machine learning algorithms represents a decisive opportunity to overcome certain limitations in current modeling.Cet article propose un point d’étape sur l’économétrie des données spatiales en mettant l’accent sur les enjeux d’identification des interactions spatiales et les perspectives ouvertes par le développement des données massives géolocalisées. Ce champ de l‘économétrie a pour objectif l’analyse des phénomènes où la proximité géographique, les interdépendances spatiales et les hétérogénéités territoriales jouent un rôle structurant. Si les modèles habituels, tels que le SAR ou le SDM, permettent de formaliser les interactions spatiales, leur mise en œuvre empirique soulève des difficultés d’identification majeures. Identifier rigoureusement ces interactions suppose de clarifier la nature des interactions, de traiter les problèmes d’endogénéité et de contrôler les sources d’hétérogénéité spatiale. L’article discute ensuite les défis que doit relever les méthodes de l’économétrie des données spatiales tant dans une perspective méthodologique structurelle que dans le cadre des modèles d’inférence causale, tout en intégrant les méthodes d’inférence développées dans d’autres branches de l’économétrie. Notamment, il souligne que l’essor du big spatial data et des algorithmes de spatial machine learning constituent une opportunité décisive pour dépasser certaines limites des approches traditionnelles
Using sodium alginate for protection and colonic delivery the next-generation probiotics (NGPs)
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Effect of heat treatment (moist heat sterilization) on sodium alginate used for probiotics encapsulation
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Impact of emulsion composition on textural and structural properties of dense cold-set gels prepared from fava bean proteins and vegetable oil
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Phytase activity during lactic acid fermentation: kinetics and impact on protein solubility
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Faire barrage aux plantes invasives en milieu agricole. Illustration avec Datura stramonium L., espèce adventice invasive et toxique
No full textInternational audienceThis review presents the economic, environmental and public health consequences resulting from the difficult-to-control presence and expansion of invasive plants in agricultural environments. The case of Datura stramonium L. (common names: thornapple or jimsonweed) is examined in detail, presenting research avenues in biocontrol of this species. Various mechanical and chemical control methods have already been implemented to manage invasive plants, but some have questionable side effects. Biocontrol therefore appears to be an alternative worth exploring because few solutions in this area are currently available and none are specifically adapted to invasive species in France.Cette revue de littérature fait état des conséquences économiques, environnementales et de santé publique causées par la présence et l’expansion difficilement contrôlables de plantes invasives en milieu agricole. Le cas du datura officinal ou datura stramoine ( Datura stramonium L.) est détaillé en présentant les pistes de recherche en biocontrôle de cette espèce. Diverses méthodes de lutte, mécaniques ou chimiques, ont d’ores et déjà été mises en œuvre pour lutter contre les plantes invasives, avec pour certaines des effets secondaires discutables. Dès lors, le biocontrôle apparaît comme une alternative complémentaire à explorer car peu de solutions dans ce domaine sont actuellement disponibles et aucune n’est spécifiquement adaptée à des espèces invasives en France
Impact of Polyethylene Glycol on C-phycocyanin Stability
No full textInternational audienceProtein stability depends on both subunit folding and inter-subunit interactions, which are modulated by environmental conditions and cosolutes. This study examined how polyethylene glycols (PEG) of different molecular weights affect the structural stability of the multimeric protein C-phycocyanin (CPC). Using differential scanning calorimetry (DSC), fluorescence spectroscopy, and rheology, we analyzed CPC in the presence of PEG 4 000 g/mol (PEG4) and PEG 35 000 g/mol (PEG35). Fluorescence spectroscopy showed that both PEGs increased the emission intensity of CPC without shifting the emission maximum, indicating changes without major alterations of the global structure. DSC revealed a marked decrease in the enthalpy of unfolding, particularly with PEG35, despite only slight changes in denaturation temperatures. Rheology demonstrated effects of CPC on PEG solution viscosity. These results suggest that the smaller size and lower hydration of PEG4 allow it to intimately penetrate the hydration shell of CPC. In contrast, the larger molecular weight and higher hydration number of PEG35 induce protein-protein association and loss of solubility. Altogether, these results show that PEG molecular weight governs CPC stability: PEG4 may destabilize CPC via crowding and hydration-shell disruption, whereas PEG35 is likely to reduce CPC solubility through depletion-driven aggregation without altering its folded structure