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CRISPR-Cas9 gene-editing to assess the role of RF-amide−related peptide 3 in ovine seasonal breeding
No full textInternational audienceSeasonal breeding is an adaptive strategy that ensures the birth of the offspring during the best time of year and allows energy saving in times of food scarcity and adverse environmental conditions. At temperate and polar latitudes, photoperiod is the main synchroniser of seasonal functions, which exerts its action through melatonin. Within the pars tuberalis of the anterior pituitary, melatonin triggers a series of events that lead to enhanced local triiodothyronine (T3) production in the medio-basal hypothalamus specifically under long days and ultimately drive the appropriate GnRH output at the median eminence. How T3 governs GnRH output is mostly unknown but neuronal populations that respectively produce KISS1 and RFRP3 appear to be involved. However, while the role of KISS1 as a major GnRH secretagogue is undisputed, the function of RFRP3 in the control of (seasonal) breeding remains enigmatic, with conflicting results hinting at elusive mechanisms. Therefore, we launched an extensive series of experiments in sheep, aimed at invalidating the NPVF gene, which encodes RFRP3, using CRISPR-Cas9 technology.Here, we report on the generation of six sheep for which the NPVF gene has been successfully edited. Four of these animals bear at least one allele expected to behave as a null and constitute founders for distinct ovine lines. These founder sheep will now enter a standard breeding scheme in order to obtain male and female homozygotes for distinct mutations. These animals are expected to provide a clear delineation of the function of RFRP3 in seasonal breeding.</p
Twin Births in 42 Sub-Saharan African Countries from 1986 to 2016: Frequency, Trends and Factors of Variation
No full textInternational audienceAbstract Since the 1970s, twin birth rates have increased sharply in developed countries. In Africa, where the rate is the highest globally, its evolution and variation are poorly understood. This article aims to estimate the twinning rate in sub-Saharan African (SSA) countries throughout 1986–2016 and analyze its spatial, temporal, and ethnic variations. It also seeks to identify social and demographic factors associated with a high probability of twin births and outline a forecast of the twinning rate. We used data from 174 Demographic and Health Surveys from 42 countries. We supplemented them with the UN World Population Prospects (WPP). The twinning rate was calculated by reporting the number of twin births per thousand total births. We used logistic regression to analyze the factors associated with twin births. We projected the twinning rate based on WPP. The overall SSA twinning rate is 17.4 per 1000, but it has changed very little over time, and we expect it will grow a little between 2015 and 2050, increasing at most from 17.4 per 1000 to 18.4 per 1000. We also show significant differences in the twinning rate in SSA according to mother ethnicity. Most ethnic groups with high twinning rates belong to the large Bantu ethnic family. SSA remains the ‘land of twins’, with the twinning rate changing slowly. However, specific health policies must target twin births in SSA to address the public health challenges they present
Schwannomes extra- et intracrâniens traités par irradiation stéréotaxique fractionnée : résultats d’une étude rétrospective et multicentrique
No full textInternational audiencePurposeLimited data exist on the role of fractionated stereotactic radiotherapy in the therapeutic strategy for neurinomas, particularly for extracranial locations. The objective of this study was to describe intra- and extracranial schwannomas using stereotactic body radiotherapy.Materials and methodsA multicentric, non-interventional study was conducted using retrospectively collected data between January 2007 and September 2021. Patients who received fractionated stereotactic radiotherapy were included. Patient characteristics, data on localization, acute and chronic toxicity, local control, as well as progressive-free survival were collected.ResultsA total of 72 patients were included with 17 being treated with surgery beforehand. Intracranial localizations concerned nerve VIII (36 lesions), but also nerve IV, V, X and mixed nerves (XII). Extracranial localizations could be cervical, thoracic or lumbar. Treatment regimens were mainly delivering 36 Gy in nine fractions of 4 Gy (23.6 %) and 21 Gy in three fractions of 7 Gy (48.6 %). The median follow-up was 49.2 months. Local control was 84.8 % at 3 and 81.8 % at 5 years. Localization and dose schedule did not affect local control (P = 0.67 and P = 0.46 respectively). Besides surgery, no other factors were associated with local control (P = 0.01). Two patients (5.0 %) experienced improvement in their hearing symptoms, while 35 (87.5 %) remained stable.ConclusionOur large multicentre study results add to evidence that fractionated stereotactic radiotherapy is a safe and effective treatment option for managing intracranial schwannomas but also extracranial localizations, including those of larger sizes.Objectif de l’étudeAprès la radiochirurgie des neurinomes, les études des 20 dernières années ont montré des taux de contrôle local favorables pour la radiothérapie stéréotaxique fractionnée. Il existe cependant peu de données sur le rôle de la radiothérapie stéréotaxique fractionnée dans la stratégie thérapeutique des neurinomes, en particulier pour les localisations extracrâniennes. L’objectif de cette étude était de décrire les résultats cliniques et le contrôle local.Matériel et méthodesUne étude multicentrique, non-interventionnelle, a été réalisée à partir de données collectées rétrospectivement au centre Oscar-Lambret à Lille et au centre hospitalier universitaire Amiens-Picardie en France entre janvier 2007 et septembre 2021. Les caractéristiques des patients, la localisation, la toxicité aiguë et chronique, le contrôle local, ainsi que la survie sans progression ont été recueillis.RésultatsEn tout, 72 patients ont été inclus, dont 17 avaient eu une chirurgie au préalable. Les lésions intracrâniennes intéressaient principalement le nerf VIII (36 lésions), mais aussi les nerfs IV, V, X et XII. Les localisations extracrâniennes se situaient aussi bien en regard des vertèbres cervicales, que thoraciques ou lombaires. La taille maximale moyenne d’une lésion était de 22,5 mm (intervalle : 8,0–51,0 mm). Les schémas d’irradiation stéréotaxique à visée thérapeutique délivraient principalement 36 Gy en neuf fractions de 4 Gy (23,6 %) et 21 Gy en trois fractions de 7 Gy (48,6 %). Le suivi médian était de 49,2 mois. Le taux de contrôle local était de 84,8 % et est resté à 81,8 % après trois à cinq ans. Le taux de survie sans progression à un an était de 92,8 %. La localisation et le schéma de dose n’ont pas affecté le contrôle local (respectivement p = 0,67 et p = 0,46). En dehors de la chirurgie, aucun autre facteur n’a été associé au contrôle local (p = 0,01). Deux patients ont connu une amélioration de leurs symptômes auditifs (soit 5,0 %), tandis que 35 sont restés stables (soit 87,5 %).ConclusionNos résultats concordent avec ceux d’études antérieures et peuvent apporter la preuve que la radiothérapie stéréotaxique fractionnée est une option thérapeutique sûre et efficace pour traiter les schwannomes intracrâniens mais aussi extracrâniens (y compris ceux de grande taille). Il peut être nécessaire de normaliser le suivi par IRM et d’inclure systématiquement une analyse volumétrique précise
Speckle Energy Spectrum in a Complex Radar Viewing Geometry From the Spaceborne SWIM Observations and from Model
No full textInternational audienceThe estimation of speckle noise or its suppression is a crucial need to estimate geophysical parameters from radar remote sensing. This is particularly important for the ocean wave spectra retrieval from measured radar backscatter coefficients, as speckle noise can completely dominate the signal in certain conditions. Such measurements are performed by the spaceborne SWIM radar, a near-nadir looking, conical scanning instrument carried by the CFOSAT satellite dedicated to the measurement of directional spectra of ocean waves from the analysis of backscattered fluctuations. In this study, we compare empirical results on the speckle spectrum obtained from the SWIM observations using three different types of acquisition and a theoretical model. We show that a cross-spectral method is efficient for estimating the speckle energy spectrum with a look separation of the order of 13 ms, but shows some limits when this time lag is increased to about 40ms because of the limited footprint overlap. In the case of an azimuthal scanning geometry like SWIM, the speckle energy increases by several order of magnitude in a sector of about ±15° close to the along-track direction. From the theoretical model, we conclude that this is due to the decrease of the Doppler bandwidth in this look geometry and that the variance of the surface scatterer velocities limits the speckle energy increase. It also explains the sensitivity to wind speed of the speckle energy in this azimuthal sector. The almost linear decrease of speckle energy with wavenumber is explained by the spectral response of the radar impulse, slightly modified by range decimation and resampling applied in the first steps of processing. Close to the along-track direction, the variation of speckle energy with latitude is mainly explained by the variation in the integration time imposed by the SWIM on-board command. The model results also show that the impact of Earth rotation on the speckle noise is small. Finally, we show that the speckle correction has an impact on the shape of the wave spectrum derived from the SWIM inversion
Involvement of common risk factors in the associations between lifetime unemployment exposure, major health outcomes and mortality: a retrospective and prospective study in a large population-based French cohort
No full textInternational audienceObjectives Uncertainty exists as to what extent common risk factors are involved in the associations of unemployment with major health outcomes and mortality. Design A retrospective and prospective observational study. Setting A large population-based French cohort (CONSTANCES). Participants 99 430 adults at baseline who have been exposed to unemployment during their lifetime and 54 679 of them who were followed for 7 years after baseline. Primary outcome measures Testing the mediating roles of several risk factors at baseline in the associations of lifetime unemployment exposure with cardiovascular disease, cancer and mortality rates during a 7-year follow-up. Direct and indirect effects were calculated for each risk factor and all together using logistic regression models adjusted for major confounders including sex, age, parental histories of cardiovascular disease and cancer, social position and working conditions. Results Estimates (95% CIs) of the direct and indirect effects for smoking are 0.0083 (0.0044 to 0.0122), p<0.0001 and 0.0010 (0.0007 to 0.0014), p<0.0001 on cardiovascular disease rate; 0.0059 (0.0028 to 0.0089), p=0.0002 and 0.0007 (0.0004 to 0.0010), p<0.0001 on cancer rate; 0.0105 (0.0058 to 0.0151), p<0.0001 and 0.0010 (0.0005 to 0.0014), p<0.0001 on all-cause mortality. The figures for alcohol consumption are, respectively, 0.0076 (0.0034 to 0.0118), p=0.0004 and 0.0004 (0.0002 to 0.0005), p=0.0006; 0.0067 (0.0035 to 0.0100), p<0.0001 and 0.0004 (0.0002 to 0.0005), p<0.0001; 0.0114 (0.0064 to 0.0164), p<0.0001 and 0.0004 (0.0001 to 0.0006), p=0.0009. For depressive symptoms, 0.0084 (0.0040to 0.0128), p=0.0002 and 0.0007 (0.0002 to 0.0011), p=0.005; 0.0053 (0.0017 to 0.0089), p=0.004 and 0.0001 (−0.0002 to 0.0005), p=0.51; 0.0088 (0.0031 to 0.0144), p=0.002 and 0.0010 (0.0004 to 0.0015), p=0.0005. For leisure-time physical inactivity, 0.0083 (0.0044 to 0.0122), p<0.0001 and 0.0003 (0.0001 to 0.0005), p=0.0006; 0.0057 (0.0026 to 0.0088), p=0.0004 and 0.0002 (0.0001 to 0.0003), p=0.002; 0.0105 (0.0058 to 0.0152), p<0.0001 and 0.0004 (0.0002 to 0.0007), p<0.0001. For blood triglycerides, 0.0080 (0.0042 to 0.0119), p<0.0001 and 0.0005 (0.0004 to 0.0007), p<0.0001; 0.0057 (0.0026 to 0.0087), p=0.0003 and 0.0001 (−0.0001 to 0.0002), p=0.32; 0.0103 (0.0057 to 0.0149), p<0.0001 and 0.0002 (0.0000 to 0.0004), p=0.06. The figures for all risk factors when tested together were 0.0075 (0.0022 to 0.0128), p=0.005 and 0.0020 (0.0011 to 0.0027), p<0.0001; 0.0052 (0.0011 to 0.0093), p=0.01 and 0.015 (0.0009 to 0.0020), p<0.0001; 0.0102 (0.0035 to 0.0169), p=0.003 and 0.0022 (0.0011 to 0.0031), p<0.0001. Conclusions These analyses show that common risk factors such as smoking, alcohol consumption, depressive symptoms, leisure-time physical inactivity and blood triglycerides mediate up to 10% of the associations of lifetime unemployment exposure with cardiovascular disease, cancer and mortality rates when tested separately and approximately 20% when tested all together. This highlights the existence of other major mediating pathways that have yet to be identified
Understanding the Sargassum phenomenon in the Tropical Atlantic Ocean: From satellite monitoring to stranding forecast
No full textInternational audienceSince 2011, massive strandings of holopelagic Sargassum have occurred on the coasts of the Caribbean and of West Africa. Although open ocean Sargassum mats are oases of biodiversity, their stranding has a number of negative ecological, economic and health consequences. To limit these impacts, Sargassum needs to be collected as quickly as possible to avoid its decomposition, which requires accurate predictions of the date, location and abundance of the strandings. Two complementary approaches have been developed for this purpose: satellite remote sensing technique, to detect Sargassum aggregations, and modeling, to forecast Sargassum displacement and growth. The objective of this review is to provide a synthesis of the current knowledge related to Sargassum monitoring in the tropical Atlantic Ocean. To better understand the issues surrounding Sargassum and its monitoring, the first two parts are devoted to an overview of the ecology of the two most prevailing holopelagic Sargassum species, to the current issues related to their strandings, to the causes of their occurrence in the tropical Atlantic Ocean and to their seasonal and interannual variabilities. The methods used to detect Sargassum from satellite images and their limitations are examined. The transport and biogeochemical models developed for seasonal forecast and stranding predictions are described along with their limitations. As both detection and modeling rely on validation data to assess their accuracy, previous works providing in situ characterization of Sargassum are also reviewed here. The last part provides recommendations to further increase knowledge on holopelagic Sargassum and improve the predictions of their strandings
Hypergraphes de connaissances neuro-symboliques : représentation des connaissances et apprentissage en intelligence artificielle neuro-symbolique
No full textThe integration of symbolic reasoning and neural learning in Artificial Intelligence (AI) has become increasingly important as the demand for models capable of handling complex, dynamic, and interconnected data grows. While traditional approaches have made progress in these domains separately, a unified framework that combines these paradigms is crucial for advancing AI's ability to interpret, learn, and predict in real-world environments.Despite the advancements in symbolic and neural models, existing literature reveals a gap in frameworks that effectively merge the two, particularly in the context of spatio-temporal knowledge representation and learning. Traditional knowledge graphs (KGs), though useful, struggle with capturing high-order relationships and dynamic, temporal changes. This limitation necessitates a novel approach that can incorporate higher-order logic and flexible structure to model real-world complexities.The objective of this study is to develop and validate a Neuro-Symbolic Knowledge Hypergraph framework that extends traditional knowledge graphs into Higher-Ordered Knowledge Graphs (HOKGs) capable of representing n-ary and temporal relationships. The framework integrates Monadic Second-Order Temporal Logic (MSOTL) for temporal reasoning and Hypergraph Neural Networks (HGNNs) for learning and predictive modeling, bridging the symbolic and neural paradigms.The methodology involves formulating a robust hypergraph structure that encodes spatio-temporal and semantic relationships using MSOTL. It is then coupled with hypergraph neural networks, incorporating convolution and attention mechanisms for effective learning and inference. The framework is tested on real-world scenarios, specifically in urban agriculture, to demonstrate its predictive capabilities and robustness.Key findings show that the proposed framework significantly enhances the expressiveness and inference capacity compared to traditional KGs. The MSOTL component ensures precise modeling of temporal and spatial relationships, while HGNNs validate predictive accuracy. The case study on urban agriculture highlights the framework's utility, showcasing how it can provide meaningful insights and precise predictions on dynamic agricultural practices.This research has broad implications for AI applications requiring complex, dynamic knowledge representation, such as smart cities, environmental monitoring, and beyond. The proposed hypergraph-based approach opens pathways for integrating higher-order logic, ontology-based knowledge, and deep learning, offering a comprehensive solution to the limitations observed in current knowledge graphs and AI models.L'intégration du raisonnement symbolique et de l'apprentissage neuronal en Intelligence Artificielle (IA) est devenue de plus en plus cruciale à mesure que la demande de modèles capables de gérer des données complexes, dynamiques et interconnectées croît. Alors que les approches traditionnelles ont fait des progrès dans ces domaines séparément, un cadre unifié combinant ces paradigmes est essentiel pour faire progresser la capacité de l'IA à interpréter, apprendre et prédire dans des environnements réels.Malgré les avancées des modèles symboliques et neuronaux, la littérature existante révèle un manque de cadres qui intègrent efficacement les deux, en particulier dans le contexte de la représentation et de l'apprentissage des connaissances spatio-temporelles. Les graphes de connaissances traditionnels (KGs), bien qu'utiles, peinent à capturer les relations d'ordre supérieur et les changements dynamiques et temporels. Cette limitation nécessite une nouvelle approche capable d'intégrer une logique d'ordre supérieur et une structure flexible pour modéliser les complexités du monde réel.L'objectif de cette étude est de développer et de valider un cadre d'Hypergraphe de Connaissances Neuro-Symboliques qui étend les graphes de connaissances traditionnels en Graphes de Connaissances d'Ordre Supérieur (HOKGs), capables de représenter des relations n-aires et temporelles. Le cadre intègre la Logique Temporelle du Second Ordre Monadique (MSOTL) pour le raisonnement temporel et les Réseaux Neuronaux d'Hypergraphes (HGNNs) pour l'apprentissage et la modélisation prédictive, reliant ainsi les paradigmes symboliques et neuronaux.La méthodologie consiste à formuler une structure d'hypergraphe robuste qui encode des relations spatio-temporelles et sémantiques en utilisant la MSOTL. Celle-ci est ensuite couplée aux réseaux neuronaux d'hypergraphes, intégrant des mécanismes de convolution et d'attention pour un apprentissage et une inférence efficaces. Le cadre est testé sur des scénarios réels, en particulier dans l'agriculture urbaine, pour démontrer ses capacités prédictives et sa robustesse.Les résultats clés montrent que le cadre proposé améliore significativement la capacité d'expression et d'inférence par rapport aux KGs traditionnels. La composante MSOTL permet une modélisation précise des relations temporelles et spatiales, tandis que les HGNNs valident l'exactitude prédictive. L'étude de cas sur l'agriculture urbaine met en évidence l'utilité du cadre, démontrant comment il peut fournir des informations significatives et des prédictions précises sur les pratiques agricoles dynamiques.Cette recherche a de vastes implications pour les applications de l'IA nécessitant une représentation des connaissances complexes et dynamiques, telles que les villes intelligentes, la surveillance environnementale, et au-delà. L'approche proposée, basée sur l'hypergraphe, ouvre la voie à l'intégration de logiques d'ordre supérieur, de connaissances basées sur l'ontologie et de l'apprentissage profond, offrant une solution globale aux limites observées dans les graphes de connaissances actuels et les modèles d'IA
Prediction of relapse in a French cohort of outpatients with schizophrenia (FACE-SZ): Prediction, not association.
No full textInternational audienceBackgroundSchizophrenia (SZ) commonly manifests through multiple relapses, each impeding the path to recovery and incurring personal and societal costs. Despite the identification of various risk factors associated to the risk of relapse, the development of accurate algorithms predictive of relapse has been limited, partly due to inadequate statistical methods. Additionally, despite the wealth of data showing strong associations between inflammation and schizophrenia, the two existing studies failed to demonstrate whether inflammatory parameters could predict relapse. Our goal is then to identify clinical and inflammatory parameters associated with relapse in schizophrenia and to develop model to predict relapse in each patient.MethodsWe have used classical Cox regression, survival penalized regression, as well as survival random forests to analyze clinical and inflammatory biological data collected in the network of the Schizophrenia Expert Centers in France in which individuals with SZ are clinically assessed and followed up annually for 3 years.ResultsAmong 247 individuals with SZ, 71 (29 %) experienced a psychotic relapse during the 3-year follow-up period. The variables most consistently associated with relapses were smoking status, severity of positive symptoms and low global functioning. From a panel of inflammatory parameters, only IL-8 serum levels were associated with time to relapse. The predictive performance, assessed using C-index, was 0.54 using both penalized regression and random forests.ConclusionsWe found several clinical and biological variables consistently associated with relapses across three distinct statistical methods. However, despite these associations, the predictive capacity of these models remained low, highlighting that association does not necessarily mean prediction
Kineothrix sedimenti sp. nov., a 3-hydroxybutyrate-producing bacterium isolated from sediment of the meromictic Lake Pavin
No full textInternational audienceAn anaerobic, spore-forming, 3-hydroxybutyrate (3-HB)- producing bacterium, strain IPX_CKT, was isolated from sediment of a meromictic lake located in Massif Central (France). Cells were rods, forming filamentous chains which were observed moving under the microscope. Strain IPX_CKT utilized a wide variety of carbohydrates, but not raffinose, rhamnose and starch. Hydrogen (H2), 3-HB, acetate and ethanol were the main fermentative end-products from growth in medium containing glucose. Strain IPX_CKT grew optimally at 37 degrees C and pH 7. Its closest phylogenetic relative was Kineothrix alysoides (16S rRNA gene sequence identity 98.7%, isDDH 34.6%, ANIb 87.4%). The genomic DNA G+C content was 43.0 mol%. As for K. alysoides, whole-genome sequencing suggested that strain IPX_CKT is capable of fixing nitrogen (N2). However, strain IPX_CKT carried a five-nif-gene-set (nifHDKEB), not present in K. alysoides. Genome sequence also showed a high number of encoded chemotaxis receptors (42 genes, the second highest in the family Lachnospiraceae after K. alysoides). Based on phenotypic, genomic, phylogenetic and chemotaxonomic analyses, it is proposed that a novel species, Kineothrix sedimenti sp. nov., be created, with strain IPX_CKT (DSM 118044T, CIP 112511T) as the type strain
Transboundary emission contribution to PM<sub>2.5</sub> concentrations in Indian cities
No full textInternational audienceTargeting urban air quality improvements in India, the National Clean Air Program (NCAP) was launched in 2019 to reduce PM 2.5 concentrations by 20%-30% in 122 initial cities over a 7 year period (2017-2024). However, considering the regional nature of air pollution nationwide and the significant emission load from rural areas, a potentially large fraction of urban PM 2.5 might originate from emissions outside of a city's boundary, i.e. transboundary emissions. Here, we couple top-down (STILT-PM 2.5 ) and bottom-up (WRF-Chem) modeling approaches with a new, nationwide, monthly-resolved, and fine-scale (5 km × 5 km) anthropogenic emission inventory to assess the impact of transboundary emissions to urban PM 2.5 concentrations across 143 cities (122 NCAP and 67 million plus -cities with population >1 million, among which 46 cities are also NCAP cities). We find that, on average, ∼85% (STILT-PM 2.5 : 82% [95% CI: 80-85%; IQR: 77%-94%] & WRF-Chem: 89% [95% CI: 87%-91%; IQR: 88%-96%]) of urban PM 2.5 across the 143 cities originates from transboundary emissions, with domestic biomass burning (32%), energy generation (16%) and industry (15%) being the leading average emission sources to the transboundary contribution. In addition, 107 of the 122 NCAP cities from both modeling approaches have annual transboundary PM 2.5 contributions exceeding 80%, indicating that an entire mitigation of within-boundary emissions alone in these cities will not achieve the most conservative targets outlined as part of NCAP. Our findings underscore the need for multi-scale, regional action planning and implementation to achieve PM 2.5 -air quality targets throughout India.</div