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Collagen/polyester-polyurethane porous scaffolds for use in meniscal repair
No full textInternational audienceFocusing on the regeneration of damaged knee meniscus, we propose a hybrid scaffold made of poly(ester-urethane) (PEU) and collagen that combines suitable mechanical properties with enhanced biological integration. To ensure biocompatibility and degradability, the degradable PEU was prepared from a poly(ε-caprolactone), L-lysine diisocyanate prepolymer (PCL di-NCO) and poly(lactic-co-glycolic acid) diol (PLGA). The resulting PEU (M = 52 000 g mol) was used to prepare porous scaffolds using the solvent casting (SC)/particle leaching (PL) method at an optimized salt/PEU weight ratio of 5 : 1. The morphology, pore size and porosity of the scaffolds were evaluated by SEM showing interconnected pores with a uniform size of around 170 μm. Mechanical properties were found to be close to those of the human meniscus (E ∼ 0.6 MPa at 37°C). To enhance the biological properties, incorporation of collagen type 1 (Col) was then performed via soaking, injection or forced infiltration. The latter yielded the best results as shown by SEM-EDX and X-ray tomography analyses that confirmed the morphology and highlighted the efficient pore Col-coating with an average of 0.3 wt% Col in the scaffolds. Finally, in vitro L929 cell assays confirmed higher cell proliferation and an improved cellular affinity towards the proposed scaffolds compared to culture plates and a gold standard commercial meniscal implan
L’intégration culture-élevage, une opportunité pour l’élevage et la transition agroécologique des systèmes agricoles
No full textInternational audienceLivestock farming, particularly in its so-called “industrial” forms, is widely criticized today for its environmental impacts. However, other more virtuous forms of livestock farming do exist, and livestock farming can prove to be essential in addressing food production challenges, providing ecosystem services, and supporting socio-territorial dynamics, as long as it is integrated into a diversified agricultural landscape. Agroecology urges us to better valorize the cultivated and reared diversity within farms and territories. Crop-livestock integration corresponds to agricultural practices capable of exploiting synergies between animal and crop components of this diversity, through closing nutrient cycles (fertilization, feeding) and functional complementarities (biological pest control, weeding). These practices, deployed within diversified farms and/or among specialized farms in a territory, help reduce dependence on inputs (purchased feed, chemical fertilizers, pesticides, fuel for mechanization) and improve resource use efficiency. They can also enhance resilience by diluting risks associated with uncertainties (climate, economic) and improve ecosystem productivity through product diversity. However, these practices are not yet part of the dominant agricultural model, and their development will require overcoming certain technical, territorial, and socio-economic barriers which, while not insurmountable, currently limit their deployment.L’élevage, dans ses formes dites « industrielles », est aujourd’hui largement critiqué pour ses impacts environnementaux. Pour autant, d’autres formes d’élevage plus vertueuses existent, et l’élevage peut s’avérer indispensable pour répondre aux enjeux de production alimentaire, de fourniture de services écosystémiques et de dynamiques socioterritoriales, pour autant qu’il s’intègre dans un paysage agricole diversifié. L’agroécologie nous invite à mieux valoriser la diversité cultivée et élevée dans les exploitations et dans les territoires. L’intégration culture-élevage correspond aux pratiques agricoles à même d’exploiter les synergies entre composantes animales et végétales de cette diversité, à travers le bouclage des cycles de nutriments (fertilisation, alimentation) et les complémentarités fonctionnelles (lutte biologique, désherbage). Ces pratiques déployées au sein d’exploitations diversifiées et/ou entre exploitations spécialisées d’un territoire permettent ainsi de réduire la dépendance aux intrants (aliments achetés, fertilisants chimiques, phytosanitaires, carburants pour la mécanisation) et d’améliorer l’efficience d’utilisation des ressources. Elle peut également accroître la résilience en diluant les risques liés aux aléas (climatiques, économique), et améliorer la productivité du milieu par la diversité des produits. Pour autant, ces pratiques ne font pas (encore) partie du modèle agricole dominant et leur développement nécessitera de lever certains freins techniques, territoriaux et socioéconomiques qui, à défaut d’être rédhibitoires, en limitent aujourd’hui le déploiement
Detection of Anaplasma and Ehrlichia bacteria in humans, wildlife, and ticks in the Amazon rainforest.
No full textInternational audienceTick-borne bacteria of the genera Ehrlichia and Anaplasma cause several emerging human infectious diseases worldwide. In this study, we conduct an extensive survey for Ehrlichia and Anaplasma infections in the rainforests of the Amazon biome of French Guiana. Through molecular genetics and metagenomics reconstruction, we observe a high indigenous biodiversity of infections circulating among humans, wildlife, and ticks inhabiting these ecosystems. Molecular typing identifies these infections as highly endemic, with a majority of new strains and putative species specific to French Guiana. They are detected in unusual rainforest wild animals, suggesting they have distinctive sylvatic transmission cycles. They also present potential health hazards, as revealed by the detection of Candidatus Anaplasma sparouinense in human red blood cells and that of a new close relative of the human pathogen Ehrlichia ewingii , Candidatus Ehrlichia cajennense, in the tick species that most frequently bite humans in South America. The genome assembly of three new putative species obtained from human, sloth, and tick metagenomes further reveals the presence of major homologs of Ehrlichia and Anaplasma virulence factors. These observations converge to classify health hazards associated with Ehrlichia and Anaplasma infections in the Amazon biome as distinct from those in the Northern Hemisphere
Trajectoire d'un e-business model évolutif : le cas de Jumia en Afrique
No full textInternational audienceLes analyses des trajectoires de développement des e-business models en Afrique ont été menées jusque-là de manière fragmentée, sans prendre en compte toutes les dimensions de déploiement international, d’adaptation aux spécificités des contextes locaux, des problématiques de création et de partage de la valeur. Notre ambition, dans ce chapitre, est de fédérer ces différentes analyses pour proposer un modèle de lecture intégrée. Pour cela, nous nous sommes appuyés sur l’étude du cas de Jumia, connu comme l’« Amazon africain ». Nous adoptons une démarche qualitative exploratoire basée essentiellement sur la collecte et l’analyse de données secondaires pour vérifier la pertinence d’une proposition de modèle théorique (VIAZ), alliant trois dimensions identifiées par des recherches antérieures : la question de la valeur (V), le processus d’imitation-adaptation (IA) et la démarche d’internationalisation (Z). À travers l’examen de la trajectoire de développement de Jumia en Afrique, nos résultats montrent d’abord une pertinence séparée des trois composantes du modèle VIAZ ainsi que sa cohérence globale. Des liens sont identifiés entre les contraintes de financement, les choix de recentrage stratégique et de déploiement international d’une part ; et les contraintes d’adaptation, de création, de partage de valeur d’autre part. Le succès du e-business model semble aussi tributaire de la capacité de Jumia à intégrer les compétences locales et à développer des capacités d’apprentissages et de réplication de composantes « modulables » du modèle
Alyxia Banks ex R.Br. in New Caledonia: a clarification of several species complexes, nomenclatural notes, and a description of three new species
No full textInternational audienceThe genus Alyxia Banks ex R.Br. is partially revised for New Caledonia, with 31 species recognised. The species complex Alyxia tisserantii Montrouz. is discussed and divided into seven species with existing names, and the synonymy is updated accordingly. Alyxia loeseneriana var. macrocarpa Boiteau is elevated to species status due to new flowering material with the name A. paniensis Lannuzel nom. nov., stat. nov. created to accommodate it, due to the preexisting Alyxia macrocarpa Koord. Detailed study of Alyxia caletioides (Baill.) Guillaumin ex Däniker revealed it was in fact made up of two distinct taxa; a new separate species, Alyxia urceolata Lannuzel, sp.nov. is therefore described. Two new species are also described following their recent collection: Alyxia humboldtensis Lannuzel & Gâteblé, sp.nov. is restricted to the summit of Mount Humboldt, and Alyxia minimiflora Lannuzel, sp.nov. is known from schistaceous cliffs around Nouméa. Finally, several nomenclatural issues are discussed, and an updated key to the genus in New Caledonia is provided
Comprendre la dynamique des forêts tropicales grâce à la télédétection et à l'apprentissage profond
No full textProtection of tropical forests is key to achieving global climate and biodiversity conservation goals. They play an essential role in carbon sequestration, water cycling, and nutrient exchanges, thereby regulating atmospheric composition and global climate patterns. However, they are under interlinked threats from deforestation and climate change, exacerbating biodiversity loss and potentially pushing these systems toward ecological tipping points. Computer visiontechniques based on deep learning have emerged as potent tools for monitoring, conservation, and prediction efforts within these expansive and intricate ecosystems. This thesis uses these emerging technologies to understand forest dynamics at scales ranging from the phenology of individual tree crowns to large-scale deforestation. Chapter 1 introduces tropical forests, explores their ecological and societal value, and discusses the technological challenges andopportunities of studying them, with a focus on deep learning as applied to remote sensing data. In Chapter 2 develops a tool to predict deforestation patterns based on convolutional neural networks (CNNs), working with freely accessible data to successfully forecast spatiotemporal patterns in the Southern Peruvian Amazon. Predicting the location of deforestation is difficult as it results from complex interactions within human-ecological systems but doing so may enable effective, adaptable prevention measures and conservation planning. The models, through their ability to discern deforestation drivers such as new access routes from remote sensing data, highlight the potentially transformational role of deep learning in conservation. In Chapter 3, I develop a new approach named “Detectree2”, building on the Mask R-CNN architecture, which is capable of accurately detecting and delineating individual tree crowns from airborne RGB imagery taken over dense tropical forests. The foundation for any remote sensing study of individual tree dynamics is accurate tree delineation. Trialled in diverse geographies, including Malaysian Borneo and French Guiana, I show this tool holds promise for large-scale forest studies. The performance of the detection and delineation, especially for tall trees, enables tracking of tree growth and mortality for the study of carbon dynamics from cheap, widely accessible photographic data. Chapter 4 develops a pipeline for identifying and mapping tropical tree species, building on the Detectree2 approach. This pipeline combines aerial photographic images taken every three weeks using a UAV with hyperspectral survey. Training and testing on a carefully crafted ground truth dataset, the two-step approach applies Detectree2 to multitemporal UAV-RGB data in order to automatically segment trees and then applies Linear Discriminant Analysis (LDA) to hyperspectral data to assign species. This new approach identified over sixty tree species with high confidence, achieving accurate species level mapping over 70% of the total crown area of the landscape. Key to the improved mappingwas the temporal stacking of imagery to delineate tree crowns accurately and a large, rigorously validated dataset of labelled tree crowns to train on. In Chapter 5, I use the data and techniques developed in the previous two Chapters to address ecological questions related to the phenology of tropical forests. Seasonal variation in canopy greenness has been observed from space, but the extent to which all species in diverse forests follow a similar pattern of leaf pigmentchanges, leaf flushing and loss remains unknown. I begin to address that knowledge gap by tracking phenology through drone-mounted sensors, providing a dataset that tracked individual trees in French Guiana at 3-weekly intervals over 34 months. 3,000 tree crowns were mapped and tracked using UAV LiDAR, revealing significant spatiotemporal variability in Projective Area Density (PAD) and distinct species-specific phenological patterns. By juxtaposing PADwith spectral metrics, I start to decipher variation in “leaf amount” and “leaf quality”, offering some insights into how individual tree changes might impact forest productivity. ConcludingChapter 6 discusses ways in which integration of deep learning technologies and remote sensing into ecology research is helping to broaden understanding and conservation capabilities for tropical forests, by providing precise, scalable solutions spanning deforestation prediction, tree level monitoring, species identification, and phenological studies.La protection des forêts tropicales est essentielle pour atteindre les objectifs mondiaux de conservation du climat et de la biodiversité. Elles jouent un rôle essentiel dans le piégeage du carbone, le cycle de l'eau et les échanges de nutriments, régulant ainsi la composition de l'atmosphère et les schémas climatiques mondiaux. Cependant, elles sont soumises aux menaces interdépendantes de la déforestation et du changement climatique, qui exacerbent la perte de biodiversité et risquent de pousser ces systèmes vers des points de basculement écologique. Les techniques de vision par ordinateur basées sur l'apprentissage profond sont devenues des outils puissants pour la surveillance, la conservation et les efforts de prédiction au sein de ces écosystèmes vastes et complexes. Cette thèse utilise ces technologies émergentes pour comprendre la dynamique des forêts à des échelles allant de la phénologie des couronnes d'arbres individuels à la déforestation à grande échelle. Le chapitre 1 présente les forêts tropicales, explore leur valeur écologique et sociétale, et discute des défis et des opportunités technologiques liés à leur étude, en mettant l'accent sur le rôle des technologies de l'information et de la communication (TIC). technologiques de leur étude, en mettant l'accent sur l'apprentissage profond appliqué aux données de télédétection
La gouvernance des services publics d'eau et d'assainissement en France : une (r)évolution sourde ?
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Local people enhance our understanding of Afrotropical frugivory networks.
No full textInternational audienceAfrotropical forests are undergoing massive change caused by defaunation, i.e., the human-induced decline of animal species,1 most of which are frugivorous species.1,2,3 Frugivores' depletion and their functional disappearance are expected to cascade on tree dispersal and forest structure via interaction networks,4,5,6,7 as the majority of tree species depend on frugivores for their dispersal.8 However, frugivory networks remain largely unknown, especially in Afrotropical areas,9,10,11 which considerably limits our ability to predict changes in forest dynamics and structures using network analysis.12,13,14,15 While the academic workforce may be inadequate to fill this knowledge gap before it is too late, local ecological knowledge appears as a valuable source of ecological information and could significantly contribute to our understanding of such crucial interactions for tropical forests.16,17,18,19,20,21 To investigate potential synergies between local ecological knowledge and academic knowledge,20,21 we compiled frugivory interactions linking 286 trees to 100 frugivore species from the academic literature and local ecological knowledge coming from interviews of Gabonese forest-dependent people. Here, we showed that local ecological knowledge on frugivory interactions was substantial and original, with 39% of these interactions unknown by science. We demonstrated that combining academic and local ecological knowledge affects the functional relationship linking frugivore body mass to seed size, as well as the network structure. Our results highlight the benefits of bridging knowledge systems between academics and local communities for a better understanding of the functioning and response to perturbations of Afrotropical forests
Révolutions et choix rationnel : une analyse critique
No full textInternational audienceSince the early studies of Olson (The logic of collective action, Harvard University Press, Cambridge, 1971/1965) and Tullock (Public Choice 11:89–99, 1971), who first defined the paradox of revolution, there has been a great deal of relevant work based on rational choice theory. While the main point of this research is to investigate solutions to this apparent paradox, its overall contribution is the provision of a rich analysis of revolutions in the light of rational choice. This article provides an overview of the literature over the last fifty years, highlighting the richness and complexity of the issues underlying the paradox and, more generally, collective action. The emphasis is placed on the salient points of what this literature and its evolution teach us about revolutionary commitment