Antiretroviral-naive and -treated HIV-1 patients can harbour more resistant viruses in CSF than in plasma

Objectives The neurological disorders in HIV-1-infected patients remain prevalent. The HIV-1 resistance in plasma and CSF was compared in patients with neurological disorders in a multicentre study. Methods Blood and CSF samples were collected at time of neurological disorders for 244 patients. The viral loads were >50 copies/mL in both compartments and bulk genotypic tests were realized. Results On 244 patients, 89 and 155 were antiretroviral (ARV) naive and ARV treated, respectively. In ARV-naive patients, detection of mutations in CSF and not in plasma were reported for the reverse transcriptase (RT) gene in 2/89 patients (2.2%) and for the protease gene in 1/89 patients (1.1%). In ARV-treated patients, 19/152 (12.5%) patients had HIV-1 mutations only in the CSF for the RT gene and 30/151 (19.8%) for the protease gene. Two mutations appeared statistically more prevalent in the CSF than in plasma: M41L (P = 0.0455) and T215Y (P = 0.0455). Conclusions In most cases, resistance mutations were present and similar in both studied compartments. However, in 3.4% of ARV-naive and 8.8% of ARV-treated patients, the virus was more resistant in CSF than in plasma. These results support the need for genotypic resistance testing when lumbar puncture is performe

DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France

We evaluated the effect of DMTs on Covid-19 severity in patients with MS, with a pooled-analysis of two large cohorts from Italy and France. The association of baseline characteristics and DMTs with Covid-19 severity was assessed by multivariate ordinal-logistic models and pooled by a fixed-effect meta-analysis. 1066 patients with MS from Italy and 721 from France were included. In the multivariate model, anti-CD20 therapies were significantly associated (OR = 2.05, 95%CI = 1.39–3.02, p < 0.001) with Covid-19 severity, whereas interferon indicated a decreased risk (OR = 0.42, 95%CI = 0.18–0.99, p = 0.047). This pooled-analysis confirms an increased risk of severe Covid-19 in patients on anti-CD20 therapies and supports the protective role of interferon

Caractérisation des réservoirs pétroliers par les données sismiques, avec l'aide de la géomodélisation

Seismic characterization of hydrocarbon reservoirs is based on various techniques: lithoseismic, geomodeling, geostatistics, evolutionary algorithms, and petrophysics. Seismic information is first used for the description of the reservoir structure, but then its relationship with facies description is a difficult task. The aim of this thesis is to develop new tools for seismic reservoir characterization.A first work has consisted in evaluating the impact of structural uncertainties on petroelastic inversion and its consequences in terms of facies classification. Then, we consider seismic modeling as an aid to reservoir model evaluation. This modeling step will make the connection between the reservoir simulators (or geomodelers) and the seismic response of the reservoir.Then we develop two alternative approaches for petroelastic and petrophysical inversion. The first one uses the gradual deformation method to generate reservoir property realizations. This method generates properties at the reservoir scale, conditioned by the wells, while respecting a cost function based on the comparison of actual and synthetic seismic data. The second method is based on supervised classification principle and uses neural networks to analyze the waveform of seismic traces. A first step is to generate a volume containing all possible petrophysical models for the concerned field. These models are analyzed by the neural networks. The neurons identified are applied on the actual data to recognize similar petrophysical/seismic relationships. All methods are tested and validated on actual reservoirs, chosen for their specific features (structural complexity, reservoir lithology).La caractérisation sismique des réservoirs pétroliers nécessite l'intégration de plusieurs techniques telles que la lithosismique, la géomodélisation, la géostatistique, l'utilisation des algorithmes évolutionnaires et la pétrophysique. L'information sismique est d'abord utilisée pour la description de l'architecture externe des réservoirs car son utilisation pour la description des faciès ne se fait pas sans difficultés. L'objectif de cette thèse est d'apporter des outils nouveaux pour aider à l'utilisation de l'information sismique pour caractériser les réservoirs.Un premier travail a consisté à évaluer l'impact des incertitudes structurales sur les inversions pétroélastiques et les conséquences en terme de classification de faciès. Ensuite, nous considérons la modélisation sismique comme aide à l'évaluation du modèle réservoir. Cette modélisation permettra de faire le lien entre les simulateurs réservoir ou les géomodeleurs et la réponse sismique du réservoir. Nous développons ensuite deux approches alternatives aux méthodes traditionnelles en inversion pétroélastique et pétrophysique. La première utilise la méthode géostatistique des déformations graduelles pour créer des réalisations de propriétés réservoirs. Elle permet de créer des propriétés à l'échelle réservoir, conditionnées aux puits, tout en respectant une fonction coût basée sur la comparaison des données sismiques réelles et issues de ces réalisations. La seconde méthode repose sur le principe de la classification supervisée et utilise des réseaux de neurones pour analyser la forme des traces sismiques. Une première étape consiste à générer un volume d'apprentissage contenant tous les modèles pétrophysiques envisageables pour un champ donné. Ces modèles sont analysés par les réseaux de neurones. Les neurones ainsi identifiés sont appliqués aux données réelles, pour identifier des relations pétrophysique/sismique identiques aux données d'apprentissage.Toutes les méthodologies sont validées sur plusieurs réservoirs choisis pour leurs particularités géologiques (complexité structurale, lithologie du réservoir)

Caractérisation des réservoirs pétroliers par les données sismiques avec l'aide de la géomodélisation

La caractérisation sismique des réservoirs pétroliers nécessite l'intégration de plusieurs techniques (lithosismique, géomodélisation, géostatistique et pétrophysique). L'information sismique est d'abord utilisée pour décrire la structure des réservoirs car son utilisation pour la description des faciès ne se fait pas sans difficultés. L'objectif de cette thèse est d'apporter des outils nouveaux basés sur l'utilisation de l'information sismique pour caractériser les réservoirs. Un premier travail a consisté à évaluer l'impact des incertitudes structurales et leurs conséquences en terme de classification de faciès. Ensuite, nous considérons la modélisation sismique comme aide à l'évaluation du modèle réservoir pour faire le lien entre les simulateurs et la réponse sismique du réservoir. Nous développons ensuite deux approches alternatives aux méthodes traditionnelles en caractérisation réservoir. La première utilise les déformations graduelles pour créer des réalisations de propriétés réservoirs. Ces propriétés sont à l'échelle réservoir, conditionnées aux puits, et respectent une fonction coût basée sur la comparaison des données sismiques réelles et synthétiques. La seconde méthode repose sur la classification supervisée par réseaux de neurones pour analyser la forme des traces sismiques. Une première étape consiste à générer tous les modèles pétrophysiques envisageables et à les analyser par réseaux de neurones. Les neurones ainsi identifiés sont appliqués aux données réelles, pour trouver des relations pétrophysiques/sismiques identiques aux données d'apprentissage. Tous les travaux sont validés sur des champs réels, choisis pour leurs particularités géologiques (lithologie du réservoir, complexité structurale).Seismic characterization of hydrocarbon reservoirs is based on various techniques : lithoseismic, geomodeling, geostatistics, evolutionary algorithms, and petrophysics. Seismic information is first used for the description of the reservoir structure, but then its relationship with facies description is a dificult task. The aim of this thesis is to develop new tools for seismic reservoir characterization. A first work has consisted in evaluating the impact of structural uncertainties on petroelastic inversion and its consequences in terms of facies classification. Then, we consider seismic modelling as an aid to reservoir model evaluation. This modeling step will make the connection between the reservoir simulators (or geomodelers) and the seismic response of the reservoir. Then we develop two alternative approaches for petroelastic and petrophysical inversion. The first one uses the gradual deformation method to generate reservoir property realizations. This method generates properties at the reservoir scale, conditioned by the wells, while respecting a cost function based on the comparison of actual and synthetic seismic data. The second method is based on supervised classification principle and uses neural networks to analyze the waveform of seismic traces. A first step is to generate a volume containing all possible petrophysical models for the concerned field. These models are analyzed by the neural networks. The neurons identified are applied on the actual data to recognize similar etrophysical/seismic relationships. All methods are tested and validated on actual reservoirs, chosen for their specific features (structural complexity, reservoir lithology).PAU-BU Sciences (644452103) / SudocSudocFranceF

Systems biology combining human- and animal-data miRNA and mRNA data identifies new targets in ureteropelvic junction obstruction

International audienceAbstractBackgroundAlthough renal fibrosis and inflammation have shown to be involved in the pathophysiology of obstructive nephropathies, molecular mechanisms underlying evolution of these processes remain undetermined. In an attempt towards improved understanding of obstructive nephropathy and improved translatability of the results to clinical practice we have developed a systems biology approach combining omics data of both human and mouse obstructive nephropathy.ResultsWe have studied in parallel the urinary miRNome of infants with ureteropelvic junction obstruction and the kidney tissue miRNome and transcriptome of the corresponding neonatal partial unilateral ureteral obstruction (UUO) mouse model. Several hundreds of miRNAs and mRNAs displayed changed abundance during disease. Combination of miRNAs in both species and associated mRNAs let to the prioritization of five miRNAs and 35 mRNAs associated to disease. In vitro and in vivo validation identified consistent dysregulation of let-7a-5p and miR-29-3p and new potential targets, E3 ubiquitin-protein ligase (DTX4) and neuron navigator 1 (NAV1), potentially involved in fibrotic processes, in obstructive nephropathy in both human and mice that would not be identified otherwise.ConclusionsOur study is the first to correlate a mouse model of neonatal partial UUO with human UPJ obstruction in a comprehensive systems biology analysis. Our data revealed let-7a and miR-29b as molecules potentially involved in the development of fibrosis in UPJ obstruction via the control of DTX4 in both man and mice that would not be identified otherwise

Non-invasive diagnosis and follow-up in liver transplantation

International audienceThe field of liver transplantation directly or indirectly embodies all liver diseases, in addition to specific ones related to organ rejection (cellular and humoral). The recommended non-invasive methods for determining the indication for liver transplantation are the Model for End-stage Liver Disease score, and the alpha-foetoprotein score in case of hepatocellular carcinoma. Radiological methods are the cornerstones for the diagnosis of vascular and biliary complications after liver transplantation. The possible diseases of the liver graft after transplantation are multiple and often intertwined. Non-invasive diagnostic methods have been poorly evaluated in this context, apart from the recurrence of hepatitis C. Liver biopsy remains the gold standard for evaluating graft lesions in the majority of cases, especially graft rejection

Time to Conversion to an Everolimus‐Based Regimen: Renal Outcomes in Liver Transplant Recipients From the EVEROLIVER Registry

International audienceLongterm use of a calcineurin inhibitor (CNI)-based regimen is one of the major reasons for chronic renal failure in liver transplantation recipients (LTRs). The Everolimus Liver registry (EVEROLIVER) evaluated renal function in LTRs who were converted to everolimus (EVR). This observational registry included all LTRs receiving EVR across 9 centers from France. Data are being collected in an electronic database over 10 years (12 visits/patient) to evaluate efficacy, renal function (estimated glomerular filtration rate [eGFR]), and safety of EVR use in clinical practice, and the current analysis is reporting up to 60 months of findings. Until September 2017, 1045 patients received EVR after a mean time of 3.6 ± 5.1 years. CNI withdrawal was feasible in 57.7% of patients as of month 60. Mean eGFR improved in patients with baseline eGFR <60 mL/minute/1.73 m2 and was maintained in those with baseline eGFR ≥60 mL/minute/1.73 m2 . Among patients with chronic kidney disease (CKD; baseline eGFR <60 mL/minute/1.73 m2 ), 55% converted to EVR within 3 months (early conversion) and 39.4% converted between 4 and 12 months after transplantation (mid-conversion) experienced improvement in eGFR (≥60 mL/minute/1.73 m2 ) at month 36. Only 20.9% and 17.4% among those converted beyond 12 months (late conversion) experienced improvement respectively at month 36 and 60. A logistic regression analysis in patients with CKD stage ≥3 demonstrated that late conversion, age, and female sex were associated with nonimprovement of eGFR (≥60 mL/minute/1.73 m2 ). Data from this real-life use of EVR indicate that renal function was maintained from the preconversion period until month 36 even in patients with advanced CKD. However, early rather than late conversion appears to be a safe approach to preserve longterm renal function in LTRs

Mapping of the amniotic fluid proteome of fetuses with congenital anomalies of the kidney and urinary tract identifies plastin 3 as a protein involved in glomerular integrity

Congenital anomalies of the kidney and the urinary tract (CAKUT) are the first cause of chronic kidney disease in childhood. Several genetic and environmental origins are associated with CAKUT, but most pathogenic pathways remain elusive. Considering the amniotic fluid (AF) composition as a proxy for fetal kidney development, we analyzed the AF proteome from non-severe CAKUT (n = 19), severe CAKUT (n = 14), and healthy control (n = 22) fetuses using LC-MS/MS. We identified 471 significant proteins that discriminated the three AF groups with 81% precision. Among them, eight proteins independent of gestational age (CSPG4, LMAN2, ENDOD1, ANGPTL2, PRSS8, NGFR, ROBO4, PLS3) were associated with both the presence and the severity of CAKUT. Among those, five were part of a protein-protein interaction network involving proteins previously identified as being potentially associated with CAKUT. The actin-bundling protein PLS3 (plastin 3) was the only protein displaying a gradually increased AF abundance from control, via non-severe, to severe CAKUT. Immunohistochemistry experiments showed that PLS3 was expressed in the human fetal as well as in both the fetal and the postnatal mouse kidney. In zebrafish embryos, depletion of PLS3 led to a general disruption of embryonic growth including reduced pronephros development. In postnatal Pls3-knockout mice, kidneys were macroscopically normal, but the glomerular ultrastructure showed thickening of the basement membrane and fusion of podocyte foot processes. These structural changes were associated with albuminuria and decreased expression of podocyte markers including Wilms' tumor-1 protein, nephrin, and podocalyxin. In conclusion, we provide the first map of the CAKUT AF proteome that will serve as a reference for future studies. Among the proteins strongly associated with CAKUT, PLS3 did surprisingly not specifically affect nephrogenesis but was found as a new contributor in the maintenance of normal kidney function, at least in part through the control of glomerular integrity. (c) 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd