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How low can we go with hypocaloric feeding for critically ill patients? For how long can it be continued?
No full textInternational audienc
Bacterial and Fungal Communities in Old Vines and Their Progeny: Insights into Microbial Inheritance Through Mass Selection
No full textInternational audienceMass selection is increasingly promoted in viticulture to enhance resilience by restoring intra-varietal diversity, yet its effects on the structure and inheritance of plant-associated microbiomes remain poorly understood. Here, we investigated bacterial and fungal communities associated with old grapevine mother plants and their progeny across four Bordeaux estates practicing mass selection, using a fully in situ experimental design. Root and leaf microbiomes were characterized by metabarcoding and analyzed using multivariate ordination, hierarchical clustering, and assembly-process metrics (βNTI and NST). Microbial community composition and structure were primarily shaped by plant compartment and vineyard origin, whereas generation effects were significant but weak. Microbial resemblance between mother vines and their offspring was limited and highly context-dependent, occurring mainly under comparable environmental conditions. Assembly-process analyses revealed heterogeneous deterministic signals, particularly in root-associated bacterial communities, but did not consistently result in phylogenetic similarity between generations. Although inheritance signals were generally weak, their recurrence across multiple vineyards and contrasted field conditions highlights their ecological relevance. By integrating environmental variability, this in situ approach mitigates the adaptive bias in plant–microbiome interactions and shows that mass selection does not rely on systematic microbial transmission but rather operates within a nuanced framework of environmentally mediated interactions
Entre droit et diplomatie, la détention des personnes poursuivies par la Cour Pénale Internationale
No full textInternational audienc
The STRAT clinical risk score to predict early ischaemic stroke post-TAVI: The FRANCE-TAVI registry
No full textInternational audienceBackgroundPractitioners recommending transcatheter aortic valve implantation (TAVI) currently lack reliable tools to predict periprocedural risk of ischaemic stroke.AimsWe aimed to develop and internally validate a clinical risk score to accurately stratify this risk.MethodsUsing data from the nationwide, multicentre FRANCE-TAVI registry, we developed a clinical predictive risk score for 30-day ischaemic stroke post-TAVI using multivariable logistic regression analysis. The model was internally validated through cross-validation techniques.ResultsAmong 62,747 patients, 1712 (2.7%) experienced ischaemic stroke within 30 days. Nine clinical predictors were identified: female sex, age > 85 years, weight < 60 kg, symptomatic status, history of stroke or transient ischaemic attack, multiple (i.e. > 1) episodes of acute heart failure, severe mobility reduction, diabetes and creatinine clearance < 60 mL/min. The resulting scoring model demonstrated good accuracy (Brier score 0.18), moderate discrimination (C-index 0.63) and excellent calibration as assessed by calibration plots, calibration-in-the-large and calibration slope. The score categorized patients into low – (90.2% of the population), intermediate – (8.0%) and high-risk (1.8%) groups. Observed stroke rates increased progressively across these groups, from 2.25% in the low-risk group to 6.51% in the intermediate-risk group and 10.10% in the high-risk group.ConclusionsThis newly developed STRAT score is a clinical, practical and effective tool for predicting early ischaemic stroke in patients undergoing TAVI. It was derived and internally validated in the FRANCE-TAVI registry and may help tailor preventive strategies. Further studies are necessary to externally validate this score and evaluate its impact on clinical decision-making
Pulse fragmentation-induced uncertainty in forest LAI mapping using UAV LiDAR
No full textInternational audienceClose-range airborne LiDAR captures high-density, high-accuracy point clouds, offering strong potential for spatially explicit Leaf Area Index (LAI) estimation in complex forests. However, key challenges in the modelling process — particularly LiDAR detection rates and accounting for the wood component — remain inadequately explored. Using simulated UAV LiDAR data generated with the Discrete Anisotropic Radiative Transfer (DART) model and realistic forest mock-ups, we evaluate how these factors influence LAI estimates. Simulated point clouds are processed with the open-source ray-tracing tool AMAPVox to assess (1) the bias introduced by incomplete detection and (2) the effectiveness of using a wood mask to exclude woody contributions. Our results show that pulse fragmentation promotes incomplete detection, which biases LAI estimates; the magnitude of this bias depends on the return-weighting strategy. For example, removing returns with small reflectance, which collectively contribute less than 5% of the backscattered energy, results in an overestimation of LAI by 10% to 20%. An alternative very simple and highly scalable weighting strategy consisting of selecting the strongest return per pulse is also explored and is shown to be effective in most cases albeit slightly less accurate. Additionally, segmentation accuracy declines as the proportion of mixed leaf-wood points increases. These findings suggest that small footprint LiDAR systems are better suited for LAI mapping: their smaller footprints reduce beam fragmentation (mitigating echo-weighting uncertainties) and minimize mixed points while improving geolocation accuracy — critical for robust leaf/wood classification. These insights advance best practices for LiDAR-based forest monitoring
Data from long-term experiments in temperate croplands to evaluate soil organic carbon models
No full textInternational audienceSoil organic carbon (SOC) models need independent evaluation against field measurements, but those latter are rarely publicly available and harmonized. In this study, we collected and shared data from 167 agronomic treatments in 34 agronomic long-term experiments (LTEs) located in temperate croplands, allowing the evaluation of several soil organic C models such as RothC, Century, AMG, MIMICS, ICBM, Millenial, and CTOOL. The dataset includes climate data, soil properties, C inputs from crops (n = 4588 records) and organic amendments, irrigation data, monthly soil cover, as well as SOC stock measurements in the topsoil layer (n = 1328 records). Climate, soil moisture, and soil temperature data were extracted from daily climate databases. Carbon inputs from crops were calculated from observed yields and harvest index, with some harvest index values estimated, combined with crop allometric coefficients from the literature. Descriptions of LTE, agronomic treatments, methodological metadata, and a part of the code, accompanies the dataset. The dataset can be reused to evaluate single SOC models, or to evaluate an ensemble of models
Influência das redes sociotécnicas na diversidade de sistemas agroflorestais de cacau no nordeste do Pará, Brasil
No full textSource Agritrop Cirad (https://agritrop.cirad.fr/617031/) * Autres projets (id;sigle;titre): ;Sustenta & Inova;(EU) Restaurer les zones altérées dans les territoires amazoniens//International audienceThis article analyses the influence of the socio-technical networks associated with agroforestry systems (AFS) on the diversity of cacao agroforestry systems (CAFS) in the Eastern Brazilian Amazon, in the municipalities of Irituia and Tomé-Açu. Fieldwork was carried out through semi-structured interviews, participatory activities and agrarian diagnostics. Three types of CAFS were identified: Group 1 was “market-oriented”; Group 2 was related to “food sovereignty”; and Group 3 was “syntropic”. The socio-technical networks appeared fragmented: an institutional network in Tomé-Açu focused on cacao intensification, while an agroecological network, predominantly in Irituia, pertained to cooperatives and local associations. Group 1, as part of the institutional network, uses intensive techniques. The second and third groups adopt alternative strategies: Group 2 uses crop diversification and certified markets, while Group 3 focuses on syntropic agriculture to regenerate degraded land. Connecting these networks could facilitate knowledge and practice exchanges, contributing to more resilient and sustainable production systems.Este artigo analisa a influência das redes sociotécnicas associadas aos sistemas agroflorestais (SAFs) sobre a diversidade dos sistemas agroflorestais cacaueiros (SAFCs) na Amazônia Oriental, nos municipios de Irituia e Tomé-Açu. O trabalho de campo foi feito por entrevistas semiestruturadas, atividades participativas e diagnósticos agrários. Três tipos de SAFCs emergiram da análise: Grupo 1 “orientado para o mercado”; Grupo 2 “soberania alimentar”; e Grupo 3, “sintrópico”. As redes sociotécnicas aparecem fragmentadas: uma rede institucional em Tomé-Açu, voltada para a intensificação do cacau, e uma rede agroecológica, predominante em Irituia, vinculada a cooperativas e associações locais. O grupo 1, inserido na rede institucional, adota técnicas agrícolas intensivas. Os grupos 2 e 3 empregam estratégias alternativas: o grupo 2 prioriza a diversificação de culturas e mercados certificados, enquanto o grupo 3 se concentra na agricultura sintrópica para regenerar áreas degradadas. Uma melhor articulação entre essas redes poderia facilitar a troca de conhecimentos e práticas, contribuindo para sistemas de produção mais resilientes e sustentáveis
Why do we work together? Motivations for collaboration in multifunctional conservation-oriented landscapes
No full textSource Agritrop Cirad (https://agritrop.cirad.fr/617022/)International audienceAround the world, many environmental and social problems often appear together, such as biodiversity loss, soil degradation, and livelihood precarity. Integrated landscape approaches have emerged as a powerful way to tackle these intertwined crises at the scale of whole landscapes, but success depends on a factor often overlooked: the motivation of people to collaborate. The objective of this study is to review and synthesize the available scientific evidence of the reasons why actors choose to collaborate in multifunctional protected landscapes. Building on existing literature, we developed an analytical framework that views collaboration as a dynamic interplay between actor-level motivators (ranging from non-material relations to nature, community or organizational ties, to material benefits) and network-level motivators (shared goals, interdependence, trusted networks, effective interactions, and clear achievements). These drivers are further shaped by broader forces such as agency, legal frameworks, social and political context, the socioeconomic conditions, and biophysical contexts. Our findings reveal a crucial insight: sustainable collaboration cannot rest on a single motivator, such as financial gain, but thrives when a “bundle of motivators” is activated. To help organizations unlock this potential, we identify seven practical levers to strengthen collaboration and maximize the impact of integrated landscape approaches. By understanding and intentionally fostering these layered motivations, landscape management can move from fragmented efforts to transformative, long-term solutions for both people and nature
DATASAPROX: standardised dataset from protocolled sampling of saproxylic beetles in continental France and Corsica
No full textInternational audienceAs part of the DATASAPROX project, we created an occurrence dataset of the saproxylic beetles from continental France and Corsica focused on protocolled data from flight interception traps. For this, we solicited the main national data producers and collected their raw data as well as the associated trapping metadata (e.g. type of trap). Once retrieved, all data went through selection and reformatting steps, including the removal of duplicates between datasets and the standardisation of taxonomic information according to the TAXREF v.18 format. We considered data from specific aerial interception traps: crossed window (©Polytrap, ©Pimul, ©Crosstrap, ©Portrap), multi-funnel (Lindgren) and window (single glass) traps. We aggregated a dataset constituting 675,525 records from 21 data producers and providers, including 485 identified projects. This dataset includes a total of 71 families, 153 subfamilies, 738 genera and 2039 species of saproxylic beetles. Data points encompass all 96 counties from continental France and Corsica for a total of 8969 geographic points and 66,202 samples. This new standardised dataset on saproxylic beetles offers new opportunities for ecological studies and conservation applications
Bacterial reporter-paired scRNA sequencing reveals cross talk between zinc starvation and zinc toxicity in macrophage antibacterial defense
No full textInternational audienceMechanisms by which macrophages deploy antibacterial zinc toxicity are poorly understood. To gain insight into this antimicrobial pathway, we developed bacterial reporter-paired single-cell RNA sequencing of human monocyte-derived macrophages (HMDM) infected with an Escherichia coli zinc-stress reporter strain. We identified HMDM subpopulations harboring zinc-stressed E. coli and corresponding mammalian genes predicted to be associated with either zinc toxicity or survival of zinc-stressed bacteria. Consistent with the latter, SLC30A4 that encodes zinc exporter ZNT4 was enriched in one subpopulation of HMDM containing zinc-stressed E. coli and its overexpression in human macrophages increased intracellular E. coli survival. At a population level, SLC30A4 expression was rapidly downregulated in human macrophages responding to E. coli and its ectopic expression in macrophages attenuated zinc starvation of intracellular E. coli. This is consistent with a model in which macrophages switch off SLC30A4 to engage zinc starvation, while also deploying zinc toxicity against bacteria adapting to a low-zinc environment. Consistent with this, intramacrophage E. coli rapidly upregulated znuA messenger RNA (mRNA) that is induced during zinc limitation, with zntA mRNA that is induced during zinc stress peaking later. Moreover, E. coli cultured under conditions of zinc limitation displayed greatly enhanced zinc sensitivity. Susceptibility of zinc-sensitive E. coli to killing by macrophages was also attenuated when zinc uptake by E. coli was inactivated, confirming the coordinated actions of zinc starvation and zinc toxicity in macrophage antibacterial responses. Strategies that enhance zinc starvation of intracellular bacteria could be exploited in the design of host-directed therapeutics that amplify macrophage-mediated antibacterial zinc toxicity