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Targeted discovery of sesquiterpene indole alkaloids from Greenwayodendron suaveolens
No full textInternational audienceThroughout the past decades, annonaceous plants have been of particular interest to the natural product community because of their therapeutic value and their richness in isoquinoline alkaloids. Taking advantage from our laboratory historical collection of these compounds, a MS/MS database of 322 isoquinolines and other metabolites from Annonaceae was implemented and named IQAMDB. The present report describes the dereplication of known alkaloids from stem barks of Greenwayodendron suaveolens (Engl. & Diels) Verdc. leveraging IQAMDB-informed feature-based molecular networking further refined by in silico annotation and taxonomic weighting. This strategy annotated over 30 compounds and streamlined the isolation of three sesquiterpene indole alkaloids (SIA) (1–3). Structure elucidation and absolute configuration assignment by a combination of NMR, TDDFT-ECD or X-ray diffraction determined these compounds to be greenwaylactam D (1) and greenwaylactam E (2), previously undescribed Witkop-Winterfeldt oxidized diastereoisomers of the previously reported greenwaylactam A, and polyveodrine (3), that discloses an unprecedented relative configuration for a SIA. The isolated compounds were evaluated for their antibacterial and antifungal activities against Staphylococcus aureus, Pseudomonas aeruginosa, Candida albicans, Mycobacterium marinum as well as their antiviral activity against Zika virus. Polyveodrine exhibited moderate antimycobacterial activity against M. marinum, whereas greenwaylactam D (1) demonstrated moderate antiviral activity against Zika virus under non-cytotoxic concentrations.Graphical abstractThree new sesquiterpene indole alkaloids were targeted following a MS-based dereplicative logic and subsequently isolated from stem barks of Greenwayodendron suaveolens. The structure elucidation relied on a combination of spectroscopic techniques and computational methods. The isolated compounds were evaluated for their anti-infective activity
Global transport of stratospheric aerosol produced by Ruang eruption from EarthCARE ATLID, limb-viewing satellites and ground-based lidar observations
No full textInternational audienceThe Atmospheric LIDar (ATLID) instrument of the ESA’s Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) satellite mission launched in May 2024 provides high-resolution vertical profiling of aerosols and clouds at 355 nm. Fully operational since July 2024, ATLID has been witness to a significant perturbation of stratospheric aerosol budget following the eruptions of Ruang volcano (Indonesia) in late April 2024. Using ATLID together with limb-viewing satellite instruments (OMPS-LP and SAGE III), we quantify the stratospheric aerosol perturbation generated by the Ruang eruption and characterize the global transport of volcanic aerosols. To evaluate the ATLID performance in the stratosphere, its data are compared with collocated ground-based lidar observations at various locations in both hemispheres and overpass-coordinated balloon flights carrying AZOR backscatter sonde. The intercomparison with suborbital observations suggests excellent performance of ATLID in the stratosphere and proves its capacity to accurately resolve fine structures in the vertical distribution of stratospheric aerosols. Using various satellite observations, we show that Ruang’s eruptive sequence in April 2024 produced eruptive columns reaching 25 km altitude, and resulted in a doubling of the tropical stratospheric aerosol abundance for several months. The eruption timing in austral Fall and its high-altitude reach fostered efficient poleward transport into the southern extratropics during austral Winter 2024. By the time of the austral Fall 2025, the sulphate aerosols from Ruang have spread across the entire Southern hemisphere and were most probably entrained by the 2025 Antarctic polar vortex, potentially enhancing the polar stratospheric cloud occurrence
Development and Validation of an Enhanced GPS Tomography Algorithm for Reunion Island
No full textInternational audienceIt is well known that GPS signals are affected by the amount of water vapor contained in the troposphere. This phenomenon creates delays, which can be converted into a corresponding integrated water vapor content along the receiver–satellite path (Slant Integrated Water Vapor, SIWV). Moreover, when a dense network of GPS stations is available, we obtain an ensemble of such SIWV paths that crisscross over the network area. Hence, by defining a three-dimensional regular grid composed of different boxes, called voxels, over our area of interest, and using a tomographic inversion method, we can retrieve the water vapor density in each voxel of the grid. Thus, this allows us to obtain a 3-D field of water vapor density above our area of interest.Here, we implement this approach on Reunion Island (a South West Indian Ocean Volcanic tropical island about 2500km²), which counts approximately 40 GPS stations. We had take into account for some local specificities: 1°/ the orography of this volcanic island is extremely sharp with high altitude gradients between neighboring stations, and 2°/ the spatial distribution of the GPS stations is very heterogeneous with a high density (about half of the stations) distributed around the active volcano of Piton de la Fournaise. Therefore, two developments were carried out. First, regarding the tomographic geometry, we use Voronoï diagram to implement a grid adapted to the spatial distribution of the GPS stations. Second, the tomographic inversion method itself was improved using the more robust truncated singular value decomposition (TSVD) approach using the L-curve technique to define the analysis threshold (Moeller, 2017).To validate these developments, the results obtained from the tomographic inversion was compared to 30 water vapor profiles obtained during a radio sounding campaign conducted in Saint-Philippe (SE of the island, close to the Piton de la Fournaise) between May 2025 and July 2025
Aurélia Dumas et Fabienne Martin-Juchat, Les Communications affectives en organisations
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How to Mitigate the Effect of Observer Error When Unraveling Species‐Environment Associations? A Case Study With Tropical Tree Communities From Western Central Africa
No full textInternational audienceAims: Unraveling species–environment associations proves challenging in species‐rich tropical rainforests due to erroneous species identifications (observer error, OE ), which negatively affect multivariate analyses. OE occurs more frequently at species level—confusing one species with another—than at broader taxonomic depth (genus or family) and disproportionately affects rare species. Therefore, many studies broaden the taxonomic resolution (using genus or family as surrogates for species) or remove rare species prior to analysis. However, it remains unclear which approach best mitigates the effect of OE . Location: Gabon. Methods: We used a dataset comprising 19,287 trees in 99 forest plots across Gabon and introduced increasing proportions of OE at species, genus and family depth. We used redundancy analysis to quantify the overall strength of species–environment associations as adjusted R 2 and quantified the relative importance of predictors as ratios between partial R 2 for soil, climate, human activity and spatial predictors, at species, morphospecies, genus and family resolution. We modelled R 2 decline through exponential decay functions and tested for differences across depth and resolution using two‐way ANOVA . We compared R 2 decay after independently introducing OE among rare and common species. Results: R 2 declined consistently under OE . Models remained significant to 30%–60% error rate, depending on depth or taxonomic resolution. Relative predictor importance was altered only when error proportions exceeded 75%. Analysis at genus or family resolution caused R 2 decay to steepen. When introduced among rare species, R 2 decay was less pronounced. Paradoxically, rare species contributed little to R 2 despite having stronger associations with the environment. Conclusion: Moderate to high instances of observer error jeopardise our ability to detect significant species–environment associations. Broadening taxonomic resolution and removing rare species inflates R 2 due to dimensionality reduction. To mitigate the effect of OE , we recommend analysing floristic datasets at fine taxonomic resolutions (species or morphospecies) and retaining rare species
CONCEPTION ET MISE EN ŒUVRE D'UNE MÉTAHEURISTIQUE ÉVOLUTIVE DE TYPE VEUVE NOIRE POUR L'OPTIMISATION DE FONCTIONS NUMÉRIQUES EN INGÉNIERIE
No full textThis study presents the design and implementation of an enhanced evolutionary metaheuristicinspired by the Latrodectus spider’s reproductive behaviour, tailored for high-precision optimization of complex numerical functions in engineering. While the canonical Black Widow Optimization Algorithm (BWOA) leverages aggressive cannibalistic selection to accelerate convergence, its propensity for premature solution elimination impedes robustness in engineering applications. To address this, we propose ACR-BWOA, a novel variant featuring three adaptive innovations : Dynamic Cannibalism Rate Control via exponentially decaying elimination intensityCR(t) = CR0 · e−λt , Elitist Solution Shielding preserving top-performing juveniles and probabilistic male survival and Hybrid Local Intensification using embedded Nelder-Mead refinement.Implemented in Python and tested across 15 benchmark functions (CEC 2017) and real-worldengineering cases – including photovoltaic array configuration and pressure vessel design ACRBWOA, demonstrates 99.1% retention of elite solutions (vs. 68.3 % in standard BWOA) whilemaintaining population diversity, superior precision with 0.05–2.3 % lower error rates on multimodal engineering functions. Accelerated convergence from 17 to 32 % through targeted exploitation, validated via Friedman statistical tests. The algorithm’s design eliminates the traditionaltrade-off between selective pressure and solution preservation, achieving 98.5 % faster constrainthandling in structural optimization problems. ACR-BWOA, establishes a new paradigm for bioinspired metaheuristics in engineering, where strategic cannibalism reduction enhances reliabilitywithout compromising computational efficiency.Cette étude présente la conception et la mise en œuvre d'une métaheuristique évolutive améliorée, inspirée du comportement reproducteur de l'araignée Latrodectus, adaptée à l'optimisation de haute précision de fonctions numériques complexes en ingénierie. Alors que l'algorithme d'optimisation de la veuve noire (BWOA) canonique exploite une sélection cannibaliste agressive pour accélérer la convergence, sa propension à l'élimination prématurée des solutions entrave sa robustesse dans les applications d'ingénierie.Pour y remédier, nous proposons l'ACR-BWOA, une variante novatrice présentant trois innovations adaptatives :Le contrôle dynamique du taux de cannibalisme via une intensité d'élimination à décroissance exponentielle : CR(t) = CR0 · e−λt. La protection des solutions élitistes (Elitist Solution Shielding) préservant les juvéniles les plus performants et la survie probabiliste des mâles.L'intensification locale hybride utilisant un raffinement de Nelder-Mead intégré.Implémenté en Python et testé sur 15 fonctions de référence (CEC 2017) ainsi que sur des cas d'ingénierie réels — incluant la configuration de réseaux photovoltaïques et la conception de réservoirs sous pression — l'ACR-BWOA démontre une rétention de 99,1 % des solutions d'élite (contre 68,3 % pour le BWOA standard) tout en maintenant la diversité de la population. Il affiche une précision supérieure avec des taux d'erreur inférieurs de 0,05 à 2,3 % sur les fonctions d'ingénierie multimodales. La convergence est accélérée de 17 à 32 % grâce à une exploitation ciblée, validée par des tests statistiques de Friedman. La conception de l'algorithme élimine le compromis traditionnel entre pression sélective et préservation des solutions, atteignant une gestion des contraintes 98,5 % plus rapide dans les problèmes d'optimisation structurelle. L'ACR-BWOA établit un nouveau paradigme pour les métaheuristiques bio-inspirées en ingénierie, où la réduction stratégique du cannibalisme renforce la fiabilité sans compromettre l'efficacité computationnelle
Plant-wax n-alkanes from the central Congo Basin as palaeo-environmental and -climatic proxies
No full textInternational audienceThe central Congo Basin is home to the world's largest tropical peatland complex and is covered with swamp forest. In the face of climate change and future human activities in the region, it is important to understand the factors that determine the nature and dynamics of the peatland vegetation cover. One way to gain insight into these factors is to reconstruct the history of the central Congo Basin peatlands. Analysing lipid biomarkers extracted from peat cores such as plant wax n-alkanes enables past environmental and climatic conditions to be reconstructed. However, there is currently no information on how the production of plant waxes by different plant species influences the abundance and isotopic composition of n-alkanes in peat and other archives in the Congo Basin. In this study we analysed plant wax n-alkane abundances, delta C-13 and delta D values according to photosynthetic pathways (C-3 vs. C-4), angiosperm subclasses (dicotyledons vs. monocotyledons), and source water delta D values in the dominant plant types (trees, shrubs, and herbs) in the peatland area of the Cuvette Department in the Republic of the Congo. Our dataset enables the definition of a new n-alkane distribution index, named GRIND, that distinguishes between C-3 (mostly dicotyledons) and C-4 (monocotyledons) plants as follows: (n-C-27 + n-C-33 + n-C-35)/(n-C-25 + n-C-27 + n-C-29 + n-C-31 + n-C-33 + n-C-35). This index may therefore be used to analyse Central African peat deposits and derive the relative abundance of C-3 and C-4 plant waxes in the past, independently of delta C-13 measurements. Furthermore, delta C-13 values from the central Congo Basin and other African sites suggest that environments with high relative humidity (> 80%) are characterised by very negative delta C-13 values (i.e., < -37 parts per thousand) of n-C-29 and n-C-31 alkanes. This observation highlights the potential of n-alkane delta C-13 in deriving climatic information under high relative humidity conditions in Central African lowlands, and contribute to palaeo-climatic reconstructions. Finally, the delta D values of n-C-29 and n-C-31 alkanes demonstrate that, despite contrasting apparent fractionation values associated with photosynthetic pathways and plant functional types - which can be accounted for using delta C-13 and pollen data in sedimentary deposits - they reliably reflect the delta D of environmental water. This confirms that plant wax n-alkane delta D values are effective tools for reconstructing palaeo-climatic changes in equatorial regions
First genomic analysis of a strain of Ralstonia pseudosolanacearum isolated from Mayotte island
No full textSource Agritrop Cirad (https://agritrop.cirad.fr/616889/)International audienceObjectives : The Ralstoni solanacearum species complex (RSSC) encompasses phytopathogenic bacteria responsible for bacterial wilt, a devastating disease affecting a wide range of agriculturally important crops. In the South-West Indian Ocean, lineage I-18 of R. pseudosolanacearum has emerged as a particularly destructive pathogen, posing a serious threat to regional food security. In this context, we report the complete genome sequence of isolate RUN2161, collected in Mayotte. This first genome from this island provides a valuable resource for unraveling the evolutionary and epidemiological mechanisms driving the emergence and spread of highly epidemic strains in agriculture. Data description: The genome of strain RUN2161 from Mayotte was sequenced using Illumina short reads and Nanopore long reads. A hybrid assembly was performed resulting in a complete genome of 5,989,529 bp with a G + C content of 66.7%. Functional annotation identified 5,268 CDS, 12 rRNAs, 61 tRNA genes, and 4 ncRNAs, assembled into one chromosome, one megaplasmid and one plasmid. Accessory plasmids are uncommon in RSSC. The RUN2161 plasmid contains Type IV secretion system genes, commonly found on conjugative plasmids, but less commonly, it also carries Type II secretion system genes involved in secretion of toxins and degradative enzymes, which could contribute to epidemiological success
La gestion des conduites dépressives chez les adolescentes victimes du traumatisme lié au harcèlement sexuel en milieu scolaire
No full textInternational audienceThis article focuses on the management of depressive behaviors in adolescent girls who are victims of trauma related to sexual harassment in schools. Sexual harassment disrupts the psychological dynamics of the subject and predisposes them to decompensation. In schools, young girls who are exposed to this traumatic reality try, as much as possible, to find necessary strategies to reduce the emotional burden induced by the cruel act they suffer. After using interviews and tests with four adolescent girls who met the inclusion criteria in this work, we collected the data and analyzed them using the thematic content analysis technique. The results we obtained show that if young girls have a poor understanding of the context of rape, they can certainly express discouragement and guilt, a feeling of failure and dissatisfaction, but are not limited to this level. They make efforts to confront the problem, manage the emotional experience, and can even, on occasion, rely on a family framework which allows them to find a better life
Application de la Classification AutomatiqueClassique et Floue au Partage Equitable desRessources Divisibles Homogènes
No full textThis thesis applies clustering, both classical and fuzzy, to fair division for homogeneous divisibleresources, in situations where individuals have not contributed to the creation of the resource.On this basis, we designed an original fair division approach, APCR, which integrates classification intothe redistribution process in order to reduce inequalities and improve the conditions of the poorest individuals.Within the APCR framework, we created and developed several allocation algorithms (PRRC/D, PRRC/F,PRRG/D, PRRG/F, PCO), which we applied and compared with existing rules P and PA. The JM index thatwe introduced proves in this thesis to be an essential tool for distributive justice. We also developed the MIalgorithm (Index Method) as a social choice method that maximizes the sum of the values of the poorestindividuals.The study shows that the PRRC/D allocation algorithm is the least unequal and therefore the mostfavorable to poor individuals according to the JM index. The index also reveals that our algorithms in aclassical environment (PRRC/D, PRRG/D) are more favorable to the less well-off than those in a fuzzyenvironment (PRRC/F, PRRG/F). Clustering highlights that PRRC/D, PRRC/F, and PCO are closer toeach other, while PRRG/D and PRRG/F are closer to traditional rules. Moreover, MI as a social choicemethod confirms the collective preference for PRRC/D. Finally, to handle larger datasets, we also developeda package and functions in R. One of these functions made it possible to automatically compute sharesaccording to the PCO rule; the results obtained were identical to those determined manually, confirming therobustness, speed, and reliability of the computer implementation.These results highlight the originality of our contributions : the APCR, its allocation algorithms, the JMindex, the MI method, and the development of software tools in R, which constitute scientific and practicaladvances in favor of a fairer, faster, and more automated redistribution of resources.Cette thèse applique la classification automatique, classique et floue, au partage équitable des ressourcesdivisibles homogènes, dans le cas où les individus n’ont pas contribué à la création de la ressource.Sur cette base, nous avons conçu une approche de partage originale, APCR, qui intègre la classificationdans le processus de redistribution afin de réduire les inégalités et d’améliorer les conditions des plus pauvres.Dans le cadre de l’APCR, nous avons créé et développé plusieurs algorithmes de partage (PRRC/D, PRRC/F,PRRG/D, PRRG/F, PCO) que nous avons appliqués et comparés aux règles existantes P et PA. L’indice JMque nous avons mis en place se révèle dans cette thèse comme un outil indispensable de justice distributive.Nous avons développé l’algorithme MI (Méthode d’Indice) comme une méthode de choix sociale quimaximise la somme des valeurs des pauvres.Il ressort de cette étude que l’algorithme de partage PRRC/D est le moins inégalitaire et donc la plusfavorable aux individus pauvres selon l’indice JM. Ce dernier révèle aussi que nos algorithmes en environnement classique (PRRC/D, PRRG/D) sont plus en faveur des moins nantis que ceux en environnement flou(PRRC/F, PRRG/F). La classification automatique met en évidence que PRRC/D, PRRC/F et PCO sont plusproches entre eux, tandis que PRRG/D et PRRG/F se rapprochent des règles traditionnelles. En outre, MI entant que méthode de choix social confirme la préférence collective pour PRRC/D. Enfin, en vue de traiter desensembles de données de plus grande taille, nous avons également développé un package et des fonctions enR. L’une de ces fonctions a permis de calculer automatiquement les parts selon la règle PCO; les résultatsobtenus se sont révélés identiques à ceux déterminés manuellement, confirmant la robustesse, la rapidité et lafiabilité de l’implémentation informatique.Ces résultats soulignent l’originalité de nos contributions : l’APCR, ses algorithmes de partage, l’indiceJM, la méthode MI et le développement d’outils logiciels en R qui constituent des avancées scientifiques etpratiques en faveur d’une redistribution plus juste, plus rapide et automatisée des ressources