Investigation of grain orientations of melt-textured HTSC with addition of uranium oxide, Y2O3 and Y2BaCuO5

Local grain orientations were studied in melt-textured YBCO samples processed with various amounts of depleted uranuim oxide (DU) and Y 2O3 by means of electron backscatter diffraction (EBSD) analysis. The addition of DU leads to the formation of Ucontaining nanoparticles (Y2Ba4CuUOx) with sizes of around 200 nm, embedded in the superconducting Y-123 matrix. The orientation of the Y 2BaCuO5 (Y-211) particles, which are also present in the YBCO bulk microstructure, is generally random as is the case in other melttextured Y-123 samples. The presence of Y-211 particles, however, also affects the orientation of the Y-123 matrix in these samples

Autoantibodies against type I IFNs in patients with critical influenza pneumonia

In an international cohort of 279 patients with hypoxemic influenza pneumonia, we identified 13 patients (4.6%) with autoantibodies neutralizing IFN-alpha and/or -omega, which were previously reported to underlie 15% cases of life-threatening COVID-19 pneumonia and one third of severe adverse reactions to live-attenuated yellow fever vaccine. Autoantibodies neutralizing type I interferons (IFNs) can underlie critical COVID-19 pneumonia and yellow fever vaccine disease. We report here on 13 patients harboring autoantibodies neutralizing IFN-alpha 2 alone (five patients) or with IFN-omega (eight patients) from a cohort of 279 patients (4.7%) aged 6-73 yr with critical influenza pneumonia. Nine and four patients had antibodies neutralizing high and low concentrations, respectively, of IFN-alpha 2, and six and two patients had antibodies neutralizing high and low concentrations, respectively, of IFN-omega. The patients' autoantibodies increased influenza A virus replication in both A549 cells and reconstituted human airway epithelia. The prevalence of these antibodies was significantly higher than that in the general population for patients 70 yr of age (3.1 vs. 4.4%, P = 0.68). The risk of critical influenza was highest in patients with antibodies neutralizing high concentrations of both IFN-alpha 2 and IFN-omega (OR = 11.7, P = 1.3 x 10(-5)), especially those <70 yr old (OR = 139.9, P = 3.1 x 10(-10)). We also identified 10 patients in additional influenza patient cohorts. Autoantibodies neutralizing type I IFNs account for similar to 5% of cases of life-threatening influenza pneumonia in patients <70 yr old

Asphaltenes diffusion/adsorption through catalyst alumina supports - Influence on catalytic activity

International audienceRefining heavy or extra heavy oil is still an important challenge for petroleum chemistry. The research performed in the field of hydroprocessing technologies covers different sides of the domain laying from the reactor and process aspects to heterogeneous catalysts development. Historically, at a large scale of time, the worldwide trend seems to indicate a decline of light conventional crude oil availability, the latest being gradually replaced by heavier non-conventional resources that contain asphaltenes and high concentrations of nitrogen and sulfur compounds. It emphasizes the need for conversion of the heaviest feeds and for improving the corresponding refining catalysts. One point raised here to progress deals with the role of the support (alumina), peculiarly about the role of the nanoporous texture on the accessibility of the feedstock molecules to the active sites. Among these large molecules to be considered, asphaltenes play a major role and are often pointed out to be responsible for the industrial issues: plugging porosity, coking support and metal sulphide active phase, poisoning hydrogenating metal. The macrostructure of asphaltenes is complex, characterized by a multi-scale aggregation behavior, strongly influenced by environmental parameters, as for instance the temperature. We have tried in this contribution to confront the abilities of various monomodal and bimodal alumina supports to let asphaltenes diffuse and adsorb into their porosity. An experimental device dedicated to assess the diffusion and adsorption of carriers has been used. The influence, on the mass transfer and the penetration depth, of various parameters such as temperature, asphaltene concentration of the solution, and alumina porous texture was appraised. It is clearly shown that extrudates requires several days do reach an equilibrium, suggesting a very low diffusion kinetic. The diffusion kinetic can be speed-up using an adapted support, especially with high pore diameter and macroporous pores but even if the extrudates of macroporous support might be likely to adsorb till its chemical saturation, i.e. an asphaltene content equal to 1.4 mg/m2 consistent with previous publications for those species. As a consequence, NiMoP-B14 is the best catalyst for all the reactions reaching 50% of gain for HDAsC7 and 40% in HDV. It highlights a clear link is established between catalytic performances and diffusion and could be usefull for designing the best carriers to be used in heavy feed hydrporocessing

An AAV-SGCG Dose-Response Study in a γ-Sarcoglycanopathy Mouse Model in the Context of Mechanical Stress

International audienceSarcoglycanopathies are rare autosomic limb girdle muscular dystrophies caused by mutations in one of the genes coding for sarcoglycans. Sarcoglycans form a complex, which is an important part of the dystrophin-associated glycoprotein complex and which protects the sarcolemma against muscle contraction-induced damage. Absence of one of the sarcoglycans on the plasma membrane reduces the stability of the whole complex and perturbs muscle fiber membrane integrity. There is currently no curative treatment for any of the sarcoglycanopathies. A first clinical trial to evaluate the safety of a recombinant AAV2/1 vector expressing γ-sarcoglycan using an intramuscular route of administration showed limited expression of the transgene and good tolerance of the approach. In this report, we undertook a dose-effect study in mice to evaluate the efficiency of an AAV2/8-expressing γ-sarcoglycan controlled by a muscle-specific promoter with a systemic mode of administration. We observed a dose-related efficiency with a nearly complete restoration of gamma sarcoglycan (SGCG) expression, histological appearance, biomarker level, and whole-body strength at the highest dose tested. In addition, our data suggest that a high expression threshold level must be achieved for effective protection of the transduced muscle, while a suboptimal transgene expression level might be less protective in the context of mechanical stress

Integrated time-lapse and single-cell transcription studies highlight the variable and dynamic nature of human hematopoietic cell fate commitment.

Individual cells take lineage commitment decisions in a way that is not necessarily uniform. We address this issue by characterising transcriptional changes in cord blood-derived CD34+ cells at the single-cell level and integrating data with cell division history and morphological changes determined by time-lapse microscopy. We show that major transcriptional changes leading to a multilineage-primed gene expression state occur very rapidly during the first cell cycle. One of the 2 stable lineage-primed patterns emerges gradually in each cell with variable timing. Some cells reach a stable morphology and molecular phenotype by the end of the first cell cycle and transmit it clonally. Others fluctuate between the 2 phenotypes over several cell cycles. Our analysis highlights the dynamic nature and variable timing of cell fate commitment in hematopoietic cells, links the gene expression pattern to cell morphology, and identifies a new category of cells with fluctuating phenotypic characteristics, demonstrating the complexity of the fate decision process (which is different from a simple binary switch between 2 options, as it is usually envisioned)

Temporary Reduction of Membrane CD4 with the Antioxidant MnTBAP Is Sufficient to Prevent Immune Responses Induced by Gene Transfer

International audienceUnexpectedly, the synthetic antioxidant MnTBAP was found to cause a rapid and reversible downregulation of CD4 on T cells in vitro and in vivo. This effect resulted from the internalization of membrane CD4 T cell molecules into clathrin-coated pits and involved disruption of the CD4/p56(Lck) complex. The CD4 deprivation induced by MnTBAP had functional consequences on CD4-dependent infectious processes or immunological responses as shown in various models, including gene therapy. In cultured human T cells, MnTBAP-induced downregulation of CD4 functionally suppressed gp120- mediated lentiviral transduction in a model relevant for HIV infection. The injection of MnTBAP in mice reduced membrane CD4 on lymphocytes in vivo within 5 days of treatment, preventing OVA peptide T cell immunization while allowing subsequent immunization once treatment was stopped. In a mouse gene therapy model, MnTBAP treatment at the time of adenovirus-associated virus (AAV) vector administration, successfully controlled the induction of anti-transgene and anti-capsid immune responses mediated by CD4(+) T cells, enabling the redosing mice with the same vector. These functional data provide new avenues to develop alternative therapeutic immunomodulatory strategies based on temporary regulation of CD4. These could be particularly useful for AAV gene therapy in which novel strategies for redosing are needed

Single-cell gene expression in ‘high’, ‘medium’, and ‘low’ CD133 cells.

<p>(A) t-stochastic neighbour embedding (t-SNE) map of single-cell transcriptional data. Each point represents a single cell highlighted in a different colour for ‘high’, ‘medium’, and ‘low’ CD133 cells. ‘High’ and ‘low’ cells are in separated clusters corresponding to cluster #1 and #2 in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001867#pbio.2001867.g001" target="_blank">Fig 1B</a>. ‘Medium’ CD133 cells are distributed in and between these 2 clusters, indicating their intermediate character. (B) Scatter plot representation of PU1 and GATA1 expression in individual cells of the ‘high’, ‘medium’, and ‘low’ CD133 fraction. Note that GATA1 is not expressed in ‘high’ cells. Coexpression of the 2 genes is observed only in some ‘medium’ and ‘low’ cells. (Underlying data can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001867#pbio.2001867.s011" target="_blank">S1 Data</a>.)</p

Quantitative analysis of dynamic phenotypes as determined by time-lapse data.

<p>(A) Association between the morphology, switch frequency, cell cycle length, and the type of cell divisions of second- and third-generation cells. Each point represents a single cell. Siblings with different dynamic behaviour and morphology (in green) are usually characterised by high switch frequencies. Siblings with similar dynamic behaviour and morphologies are shown in blue. The morphology is given as a ratio of time spent in round/polarised shape by a cell during the cell cycle. Switch frequency is given in number of morphological transformations per hour. Cell cycle length is in hours. (B) Dynamic phenotype change during the first 2 cell divisions as determined on the basis of time-lapse records. Three different dynamic phenotypes were identified: stable polarised, frequent switchers, and stable round. Cells tended to transmit dynamic phenotypes to daughter cells during cell division. Polarised and frequent switchers produced round cells, and frequent switchers were always produced by polarised mothers. Phenotypic change is not associated with asymmetric division; it can occur at any time in the cell cycle. Since round cells always produce round daughters, the whole process is biased and the proportion of this phenotype increases. (Underlying data can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001867#pbio.2001867.s012" target="_blank">S2 Data</a>.)</p

Transcriptional profile of cord blood-derived CD34+ cells at t = 0 h, t = 24 h, t = 48 h, and t = 72 h after the beginning of the experiment.

<p>(A) CD34+ cells were isolated from human cord blood and cultured in serum-free medium with early acting cytokines. Single-cell quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to analyse single-cell transcription at 0 h, 24 h, 48 h and 72 h. At the same time, individual clones were continuously monitored using time-lapse microscopy. (B) t-distributed stochastic neighbour embedding (t-SNE) map of single-cell transcription data. The 4 panels show analysis of the same data set, with each point representing a single cell highlighted in different colours depending on the given time point. The 2 clusters identified by gap statistics at t = 48 h and t = 72 h are surrounded by an ellipse and numbered #1 and #2 for multipotent and common myeloid progenitor (CMP)-like cells. Note the rapid evolution of the expression profiles. (Underlying data can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001867#pbio.2001867.s011" target="_blank">S1 Data</a>.) (C) A heat map representation of the expression levels of a subset of genes that strongly contributed to the differentiation of the different groups (as detected by principal component analysis [PCA]; see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001867#pbio.2001867.s002" target="_blank">S2 Fig</a>) and cluster analysis of expression profiles at the different time points show the rapid evolution of gene expression. The list of the genes used (shown on the right) includes well-known genes acting during hematopoietic differentiation but also many randomly selected genes. The colour code for expression levels is indicated below. (Underlying data can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001867#pbio.2001867.s011" target="_blank">S1 Data</a>.) (D) Pairwise correlations between the genes analysed using single-cell quantitative reverse transcription polymerase chain reaction (qRT-PCR). Only the gene pairs with a Pearson correlation coefficient higher than 0.8 are indicated for each time point. The 2 clusters identified at t = 48 h and t = 72 h are represented separately. Note the transient increase of the average correlation in cluster #2 at t = 48 h, indicating a state transition. (Underlying data can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001867#pbio.2001867.s011" target="_blank">S1 Data</a>.)</p

Transcriptional profile of cord blood-derived CD34+ cells treated with valproic acid (VPA) at t = 0 h, t = 24 h, t = 48 h, and t = 72 h after the beginning of the experiment as compared to untreated, normal control cells.

<p>(A) A cytometric analysis of the effect of VPA on cord blood CD34+ cells shows an increase in the CD90 protein in most cells, while the CD34 and CD38 markers remain essentially unchanged. (B) Heat map representation of the expression levels of 90 genes as determined by single-cell quantitative reverse transcription polymerase chain reaction (qRT-PCR) in VPA-treated cells at t = 0 h, t = 24 h, t = 48 h, and t = 72 h. The colour codes for the time points of cells are indicated on the right; the colour codes for expression levels are indicated below the heat map. Note the high heterogeneity and lack of clear clustering of the expression patterns. (C) t-distributed stochastic neighbour embedding (t-SNE) plot representation of transcription data obtained for VPA-treated cells compared to untreated normal cells (data for these cells are the same as in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001867#pbio.2001867.g001" target="_blank">Fig 1</a>). The gene expression data obtained in the 2 experiments were mapped together. Each point represents a single cell, and the cells at t = 0 h, t = 24 h, t = 48 h, and t = 72 h are highlighted separately in the 4 panels. The colour codes for VPA-treated (+VPA) and VPA-untreated (−VPA) are indicated below the panels. Clusters #1 and #2, identified at t = 48 h and t = 72 h in −VPA cells (see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001867#pbio.2001867.g001" target="_blank">Fig 1</a>), are indicated on the t = 72 h panel. Note the clear separation of the +VPA and −VPA cells at every time point except t = 24 h. Note also that +VPA cells do not contribute to clusters #1 and #2, indicating that they do not acquire expression profiles typical of these cells. (Underlying data can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001867#pbio.2001867.s011" target="_blank">S1 Data</a>.)</p