University of Toulouse
  • Toulouse, France
Recent publications
In late 2015, an epizootic of Highly Pathogenic Avian Influenza (H5Nx) was registered in Southwestern France, including more than 70 outbreaks in commercial poultry flocks. Phylogenetic analyses suggested local emergence of H5 viruses which differed from A/goose/Guangdong/1/1996 clade 2.3.4.4b lineage and shared a unique polybasic cleavage site in their hemagglutinin protein. The present work provides an overview of the pathobiological picture associated with this epizootic in naturally infected chickens, guinea fowls and ducks. Upon necropsy examination, selected tissues were sampled for histopathology, immunohistochemistry and quantitative Real Time Polymerase Chain Reaction. In Galliformes, HPAIVs infection manifested as severe acute systemic vasculitis and parenchymal necrosis and was associated with endothelial expression of viral antigen. In ducks, lesions were mild and infrequent, with sparse antigenic detection in respiratory and digestive mucosae and leukocytes. Tissue quantifications of viral antigen and RNA were higher in chickens and guinea fowls compared to duck. Subsequently, recombinant HA (rHA) was generated from a H5 HPAIV isolated from an infected duck to investigate its glycan-binding affinity for avian mucosae. Glycan-binding analysis revealed strong affinity of rHA for 3’Sialyl-LacNAc and low affinity for Sialyl-Lewis X , consistent with a duck-adapted virus similar to A/Duck/Mongolia/54/2001 (H5N2). K222R and S227R mutations on rHA sequence shifted affinity towards Sialyl-Lewis X and led to an increased affinity for chicken mucosa, confirming the involvement of these two mutations in the glycan-binding specificity of the HA. Interestingly, the rHA glycan binding pattern of guinea fowl appeared intermediate between duck and chicken. The present study presents a unique pathobiological description of the H5 HPAIVs outbreaks that occurred in 2015–2016 in Southwestern France.
Introduction Neurofibromatosis type 1 (NF1) is considered a model of neurodevelopmental disorder because of the high frequency of learning deficits, especially developmental coordination disorder. In neurodevelopmental disorder, Nicolson and Fawcett formulated the hypothesis of an impaired procedural learning system that has its origins in cortico-subcortical circuits. Our aim was to investigate the relationship between cortico-striatal connectivity and procedural perceptual-motor learning performance and motor skills in NF1 children. Methods Seventeen NF1 and 18 typically developing children aged between 8 and 12 years old participated in the study. All were right-handed and did not present intellectual or attention deficits. In all children, procedural perceptual-motor learning was assessed using a bimanual visuo-spatial serial reaction time task (SRTT) and motor skills using the Movement Assessment Battery for Children (M-ABC). All participants underwent a resting-state functional MRI session. We used a seed-based approach to explore cortico-striatal connectivity in somatomotor and frontoparietal networks. A comparison between the groups’ striato-cortical connectivity and correlations between connectivity and learning (SRTT) and motor skills (M-ABC) were performed. Results At the behavioral level, SRTT scores are not significantly different in NF1 children compared to controls. However, M-ABC scores are significantly impaired within 9 patients (scores below the 15th percentile). At the cerebral level, NF1 children present a higher connectivity in the cortico-striatal regions mapping onto the right angular gyrus compared to controls. We found that the higher the connectivity values between these regions, differentiating NF1 and controls, the lower the M-ABC scores in the whole sample. No correlation was found for the SRTT scores. Conclusion NF1 children present atypical hyperconnectivity in cortico-striatal connections. The relationship with motor skills could suggest a sensorimotor dysfunction already found in children with developmental coordination disorder. These abnormalities are not linked to procedural perceptual-motor learning assessed by SRTT.
Fracture hospitalizations of people ≥ 65 years old living in France increased annually from 2015 until 2019 (average: 1.8%), until being reduced in 2020 (- 1.4%) with an abrupt decrease during the lockdown period. Decreased exposure to the risk of falling during COVID-19 year 2020 may have reflected in lower incidence of fractures.
Background There is growing interest in using genetic selection to obtain more resilient farm animals (i.e. that are minimally affected by disturbances or rapidly recover from them). The aims of this study were to: (i) estimate the genetic parameters of resilience indicator traits based on egg production data, (ii) assess whether these traits are genetically correlated in purebreds and crossbreds, and (iii) assess the genetic correlations of these traits with egg production (EP) as total number of eggs between 25 and 83 weeks. Purebred hens (33,825 from a White Leghorn (WA) line and 34,397 from a Rhode Island (BD) line were housed in individual cages, while crossbred hens were housed in collective cages of 6 to 8 paternal half-sibs (12,852 WA and 3898 BD crossbred groups, where the name of the group refers to the line used as the sire). Deviations of a hen’s weekly egg production from the average of the corresponding batch were calculated. Resilience indicator traits investigated were the natural logarithm of the variance (LNVAR), the skewness (SKEW), and the lag-one autocorrelation (AUTO-R) of these deviations. Results In both purebred lines, EP was estimated to be lowly heritable (WA: 0.11 and BD: 0.12). Resilience indicators were also estimated to be lowly heritable in both lines (LNVAR: 0.10 and 0.12, SKEW: 0.04 and 0.02, AUTO-R: 0.06 and 0.08 in WA and BD, respectively). In both crossbred groups, EP, AUTO-R, and SKEW were estimated to be less heritable than in purebreds (EP: $$h^{2}$$ h 2 ≤ 0.07; and resilience indicator traits: $$h^{2}$$ h 2 ≤ 0.03), while LNVAR had an $$h^{2}$$ h 2 estimate that was similar to or higher in crossbreds ( $$h^{2}$$ h 2 ranged from 0.13 to 0.21) than in purebreds. In both purebreds and crossbreds, resilience indicator traits were estimated to have favorable genetic correlations with EP and between each other. For all traits and in both lines, estimates of genetic correlations between purebreds and crossbreds ( $$r_{pc}$$ r pc ) differed from 1 and ranged from 0.16 to 0.63. Conclusions These results show that selection for resilience based on EP data can be considered in breeding programs for layers. Genetic improvement of resilience in crossbreds can be achieved by using information on purebreds, but would be greatly enhanced by the integration of information on crossbreds in breeding programs.
Objective The admixture of domestic pig into wild boar populations is controlled until now, by cytogenetic analysis. Even if a first-generation hybrid animal is discernable because of its 37-chromosome karyotype, the cytogenetic method is not applicable in the case of advanced intercrosses. The aim of this study is therefore to evaluate the use of SNP (Single Nucleotide Polymorphism) markers as an alternative technology to characterize recent or past hybridization between the two sub-species. The final goal would be to develop a molecular diagnostic tool. Data description The Geneseek Genomic Profiler High-Density porcine beadchip (GGP70KHD, Illumina, USA), comprising 68,516 porcine SNPs, was used on a set of 362 wild boars with diverse chromosomal statuses collected from different areas and breeding environments in France. We generated approximately 62,192–64,046 genotypes per wild boar. The present dataset might be useful for the community (i) for developing molecular tools to evaluate the admixture of domestic pig into wild boar populations, and (ii) for genetic diversity studies including wild boar species or phylogeny analyses of Suidae populations. Raw data files and a processed matrix data file were deposited in the ArrayExpress at European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI) data portal under accession number E-MTAB-10591.
Background An important goal in animal breeding is to improve longitudinal traits. The objective of this study was to explore for longitudinal residual feed intake (RFI) data, which estimated breeding value (EBV), or combination of EBV, to use in a breeding program. Linear combinations of EBV (summarized breeding values, SBV) or phenotypes (summarized phenotypes) derived from the eigenvectors of the genetic covariance matrix over time were considered, and the linear regression method (LR method) was used to facilitate the evaluation of their prediction accuracy. Results Weekly feed intake, average daily gain, metabolic body weight, and backfat thickness measured on 2435 growing French Large White pigs over a 10-week period were analysed using a random regression model. In this population, the 544 dams of the phenotyped animals were genotyped. These dams did not have own phenotypes. The quality of the predictions of SBV and breeding values from summarized phenotypes of these females was evaluated. On average, predictions of SBV at the time of selection were unbiased, slightly over-dispersed and less accurate than those obtained with additional phenotypic information. The use of genomic information did not improve the quality of predictions. The use of summarized instead of longitudinal phenotypes resulted in predictions of breeding values of similar quality. Conclusions For practical selection on longitudinal data, the results obtained with this specific design suggest that the use of summarized phenotypes could facilitate routine genetic evaluation of longitudinal traits.
Background In animal genetics, linear mixed models are used to deal with genetic and environmental effects. The variance and covariance terms of these models are usually estimated by restricted maximum likelihood (REML), which provides unbiased estimators. A strong hypothesis of REML estimation is the multi-normality of the response variables. However, in practice, even if the marginal distributions of each phenotype are normal, the multi-normality assumption may be violated by non-normality of the cross-sectional dependence structure, that is to say when the copula of the multivariate distribution is not Gaussian. This study uses simulations to evaluate the impact of copula miss-specification in a bivariate animal model on REML estimations of variance components. Result Bivariate phenotypes were simulated for populations undergoing selection, considering different copulas for the dependence structure between the error components. Two multi-trait situations were considered: two phenotypes were measured on the selection candidates, or only one phenotype was measured on the selection candidates. Three generations with random selection and five generations with truncation selection based on estimated breeding values were simulated. When selection was performed at random, no significant differences were observed between the REML estimations of variance components and the true parameters even for the non-Gaussian distributions. For the truncation selections, when two phenotypes were measured on candidates, biases were systematically observed in the variance components for high residual dependence in the case of non-Gaussian distributions, especially in the case of a heavy-tailed or asymmetric distribution when the two traits were measured. Conversely, when only one phenotype was measured on candidates, no difference was observed between the Gaussian and non-Gaussian distributions in REML estimations. Conclusions This study confirms that REML can be used by geneticists to evaluate breeding values in the multivariate case even if the multivariate phenotypes deviate from normality in the situation of random selection or if one trait is not measured for the candidate under selection. Nevertheless, when the two traits are measured, the violation of the normality assumption may lead to non-negligible biases in the REML estimations of the variance-covariance components.
Several preclinical and clinical lines of evidence suggest a role of neuroinflammation in migraine. Neuroimaging offers the possibility to investigate and localize neuroinflammation in vivo in patients with migraine, and to characterize specific inflammatory constituents, such as vascular permeability, and macrophage or microglia activity. Despite all imaging data accumulated on neuroinflammation across the past three decades, an overview of the imaging evidence of neuroinflammation in migraine is still missing. We conducted a systematic review in the Pubmed and Embase databases to evaluate existing imaging data on inflammation in migraine, and to identify gaps in the literature. We included 20 studies investigating migraine without aura ( N = 4), migraine with aura ( N = 8), both migraine with and without aura ( N = 3), or hemiplegic migraine ( N = 5). In migraine without aura, macrophage activation was not evident. In migraine with aura, imaging evidence suggested microglial and parameningeal inflammatory activity. Increased vascular permeability was mostly found in hemiplegic migraine, and was atypical in migraine with and without aura. Based on the weight of existing and emerging data, we show that most studies have concentrated on demonstrating increased vascular permeability as a marker of neuroinflammation, with tools that may not have been optimal. In the future, novel, more sensitive techniques, as well as imaging tracers delineating specific inflammatory pathways may further bridge the gap between preclinical and clinical findings.
Background Post‐intensive care syndrome (PICS) encompasses physical, cognition, and mental impairments persisting after intensive care unit (ICU) discharge. Ultimately it significantly impacts the long‐term prognosis, both in functional outcomes and survival. Thus, survivors often develop permanent disabilities, consume a lot of healthcare resources, and may experience prolonged suffering. This review aims to present the multiple facets of the PICS, decipher its underlying mechanisms, and highlight future research directions. Main text This review abridges the translational data underlying the multiple facets of chronic critical illness (CCI) and PICS. We focus first on ICU-acquired weakness, a syndrome characterized by impaired contractility, muscle wasting, and persisting muscle atrophy during the recovery phase, which involves anabolic resistance, impaired capacity of regeneration, mitochondrial dysfunction, and abnormalities in calcium homeostasis. Second, we discuss the clinical relevance of post-ICU cognitive impairment and neuropsychological disability, its association with delirium during the ICU stay, and the putative role of low-grade long-lasting inflammation. Third, we describe the profound and persistent qualitative and quantitative alteration of the innate and adaptive response. Fourth, we discuss the biological mechanisms of the progression from acute to chronic kidney injury, opening the field for renoprotective strategies. Fifth, we report long-lasting pulmonary consequences of ARDS and prolonged mechanical ventilation. Finally, we discuss several specificities in children, including the influence of the child’s pre-ICU condition, development, and maturation. Conclusions Recent understandings of the biological substratum of the PICS’ distinct features highlight the need to rethink our patient trajectories in the long term. A better knowledge of this syndrome and precipitating factors is necessary to develop protocols and strategies to alleviate the CCI and PICS and ultimately improve patient recovery.
It remains challenging to produce new and efficient adsorbents to remove sulfur compounds from waste tire pyrolysis oils. The present work investigated the ex-situ treatment by desulfurization and cracking of volatiles from the pyrolysis of waste tires using an innovative synthetic oil mixture. For this purpose, biochars from the pyrolysis of abundant biomasses (date seeds and spent coffee grounds) were used to improve the quality of these volatiles. Furthermore, the purification efficiency of these biochars was compared to that of commercial activated carbon. Thus, the influence of the operating conditions was studied. Finally, to provide an innovative insight into the desulfurization efficiency, the regeneration of the best performing desulfurization material was carried out. The results show promising desulfurization and cracking capacities of the spent coffee grounds biochar and excellent regeneration performance.
Background Hypotension and blood pressure (BP) variability during endovascular therapy (EVT) for acute ischemic stroke (AIS) due to an anterior large vessel occlusion (LVO) is associated with worse outcomes. However, the optimal BP threshold during EVT is still unknown given the lack of randomized controlled evidence. We designed the DETERMINE trial to assess whether an individualized BP management during EVT could achieve better functional outcomes compared to a standard BP management. Methods The DETERMINE trial is a multicenter, prospective, randomized, controlled, open-label, blinded endpoint clinical trial (PROBE design). AIS patients with a proximal anterior LVO are randomly assigned, in a 1:1 ratio, to an experimental arm in which mean arterial pressure (MAP) is maintained within 10% of the first MAP measured before EVT, or a control arm in which systolic BP (SBP) is maintained within 140–180 mm Hg until reperfusion is achieved or artery closure in case of EVT failure. The primary outcome is the rate of favorable functional outcomes, defined by a modified Rankin Scale (mRS) between 0 and 2 at 90 days. Secondary outcomes include excellent outcome and ordinal analysis of the mRS at 90 days, early neurological improvement at 24 h (National Institutes of Health Stroke Scale), final infarct volume, symptomatic intracranial hemorrhage rates, and all-cause mortality at 90 days. Overall, 432 patients will be included. Discussion DETERMINE will assess the clinical relevance of an individualized BP management before reperfusion compared to the one size fits all approach currently recommended by international guidelines. Trial registration ClinicalTrials.gov , NCT04352296. Registered on 20th April 2020.
Background Feed efficiency during lactation involves a set of phenotypic traits that form a complex system, with some traits exerting causal effects on the others. Information regarding such interrelationships can be used to predict the effect of external interventions on the system, and ultimately to optimize management practices and multi-trait selection strategies. Structural equation models can be used to infer the magnitude of the different causes of such interrelationships. The causal network necessary to fit structural equation models can be inferred using the inductive causation (IC) algorithm. By implementing these statistical tools, we inferred the causal association between the main energy sources and sinks involved in sow lactation feed efficiency for the first time, i.e., daily lactation feed intake (dLFI) in kg/day, daily sow weight balance (dSWB) in kg/day, daily litter weight gain (dLWG) in kg/day, daily back fat thickness balance (dBFTB) in mm/day, and sow metabolic body weight (SMBW) in kg 0.75 . Then, we tested several selection strategies based on selection indices, with or without dLFI records, to improve sow efficiency during lactation. Results The IC algorithm using 95% highest posterior density (HPD 95% ) intervals resulted in a fully directed acyclic graph, in which dLFI and dLWG affected dSWB, the posterior mean of the corresponding structural coefficients (PM λ ) being 0.12 and − 0.03, respectively. In turn, dSWB influenced dBFTB and SMBW, with PM λ equal to 0.70 and − 1.22, respectively. Multiple indirect effects contributed to the variances and covariances among the analyzed traits, with the most relevant indirect effects being those involved in the association between dSWB and dBFTB and between dSWB and SMBW. Selection strategies with or without phenotypic information on dLFI, or that hold this trait constant, led to the same pattern and similar responses in dLFI, dSWB, and dLWG. Conclusions Selection based on an index including only dBFTB and dLWG records can reduce dLFI, keep dSWB constant or increase it, and increase dLWG. However, a favorable response for all three traits is probably not achievable. Holding the amount of feed provided to the sows constant did not offer an advantage in terms of response over the other strategies.
Introduction Insula plays an integrating role in sensory, affective, emotional, cognitive and autonomic functions in migraine, especially in migraine with aura (MA). Insula is functionally divided into 3 subregions, the dorsoanterior, the ventroanterior and the posterior insula respectively related to cognition, emotion, and somatosensory functions. This study aimed at investigating functional connectivity of insula subregions in MA. Methods Twenty-one interictal patients with MA were compared to 18 healthy controls (HC) and 12 interictal patients with migraine without aura (MO) and were scanned with functional MRI during the resting state. Functional coupling of the insula was comprehensively tested with 12 seeds located in the right and left, dorsal, middle, ventral, anterior and posterior insula, by using a seed-to-voxel analysis. Results Seed-to-voxel analysis revealed, in MA, a strong functional coupling of the right and left antero-dorsal insula with clusters located in the upper cerebellum. The overlap of these cerebellar clusters corresponded to the vermis VI. These functional couplings were not correlated to duration of MA, frequency of MA attacks nor time since last MA attack, and were not found in MO. Discussion The anterior insula and superior cerebellum, including vermis VI, are components of the central Autonomic Nervous System (ANS) network. As these regions are involved in the control of cardiovascular parasympathetic tone, we hypothesize that this connectivity may reflect the cardiovascular features of MA. Conclusion The anterior dorsal insula is connected with vermis VI in MA patients in the resting state. This connectivity may reflect the cardiovascular features of MA. Trial registration NCT02708797.
What are the underlying cognitive mechanisms that support belief in conspiracies? Common dual-process perspectives suggest that deliberation helps people make more accurate decisions and decreases belief in conspiracy theories that have been proven wrong (therefore, bringing people closer to objective accuracy). However, evidence for this stance is i) mostly correlational and ii) existing causal evidence might be influenced by experimental demand effects and/or a lack of suitable control conditions. Furthermore, recent work has found that analytic thinking tends to increase the coherence between prior beliefs and new information, which may not always lead to accurate conclusions. In two studies (Study 1: N = 1028; Study 2: N = 1000), participants were asked to evaluate the strength of conspiracist (or non-conspiracist) explanations of events. In the first study, which used well-known conspiracy theories, deliberation had no effect. In the second study, which used relatively unknown conspiracy theories, we found that experimentally manipulating deliberation did increase belief accuracy - but only among people with a strong ‘anti-conspiracy’ or strong ‘pro-conspiracy’ mindset from the beginning, and not among those with an intermediate conspiracist mindset. Although these results generally support the idea that encouraging people to deliberate can help to counter the growth of novel conspiracy theories, they also indicate that the effect of deliberation on conspiracist beliefs is more complicated than previously thought.
We study stability of the spectral gap and observable diameter for metric measure spaces satisfying the RCD(1,∞) condition. We show that if such a space has an almost maximal spectral gap, then it almost contains a Gaussian component, and the Laplacian has eigenvalues that are close to any integers, with dimension-free quantitative bounds. Under the additional assumption that the space admits a needle disintegration, we show that the spectral gap is almost maximal iff the observable diameter is almost maximal, again with quantitative dimension-free bounds.
Characterising thin mineral layers on heterogeneous media is a significant challenge in archaeometry. Nevertheless, obtaining such geochemical and mineralogical data can, in many cases, provide valuable information about the original raw-material procurement strategies and document the chaîne opératoire leading to the finished object. In this contribution, we report on the geochemical analysis of a thin layer of red mineral pigment found on a skull from the Mesolithic burial of Campu Stefanu, Corsica. A proton ion beam analysis was conducted at the New AGLAE facilities (Palais du Louvre, Paris) to determine major, minor and trace element compositions. Contribution from the pigment’s elemental composition is statistically differentiated from that of the bone and the sediment. Furthermore, the composition of the pigment is shown to be compatible with that of iron-oxide rich mineral blocks found within the mortuary deposits.
In the fast evolving context of industry 4.0, companies or organizations must continuously evolve and improve. To maintain their business efficiency, they join industrial networks in which they have to collaborate. In more recent context of industry 5.0, humans are placed at the heart of the industrial processes by developing human-centric and society-centric approach. In such a context, human collaboration experiences are numerous and constitute meaningful pieces of knowledge which can be reused within a human-centric approach. This needs to (i) formalize and capitalize collaboration experiences, (ii) enable actors to assess collaboration and, (iii) develop reusing mechanisms. This article proposes an experience feedback approach where collaboration experiences are formalized and directly assessed by actors who have collaborated. Assessment grids are proposed to guide the human evaluations. From the individual evaluations, aggregation mechanisms are proposed to compute the collaboration performance of organizations. Finally, a reusing mechanism allows to learn from prior experiences, identifying the best organizations to make collaborating for a new industrial process.
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388 members
Yvan Lefevre
  • Laboratory of Plasma and Energy Conversion (LAPLACE)
Jean Pierre Poulain
  • Centre d'études et de recherches Travail Organisations Pouvoir
Aurore Perrot
  • IUCT Oncopole
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Toulouse, France