Characterization of hemizygous deletions in Citrus using array-Comparative Genomic Hybridization and microsynteny comparisons with the poplar genome

<p>Abstract</p> <p>Background</p> <p>Many fruit-tree species, including relevant <it>Citrus </it>spp varieties exhibit a reproductive biology that impairs breeding and strongly constrains genetic improvements. In citrus, juvenility increases the generation time while sexual sterility, inbreeding depression and self-incompatibility prevent the production of homozygous cultivars. Genomic technology may provide citrus researchers with a new set of tools to address these various restrictions. In this work, we report a valuable genomics-based protocol for the structural analysis of deletion mutations on an heterozygous background.</p> <p>Results</p> <p>Two independent fast neutron mutants of self-incompatible clementine (<it>Citrus clementina </it>Hort. Ex Tan. cv. Clemenules) were the subject of the study. Both mutants, named 39B3 and 39E7, were expected to carry DNA deletions in hemizygous dosage. Array-based Comparative Genomic Hybridization (array-CGH) using a <it>Citrus </it>cDNA microarray allowed the identification of underrepresented genes in these two mutants. Subsequent comparison of citrus deleted genes with annotated plant genomes, especially poplar, made possible to predict the presence of a large deletion in 39B3 of about 700 kb and at least two deletions of approximately 100 and 500 kb in 39E7. The deletion in 39B3 was further characterized by PCR on available <it>Citrus </it>BACs, which helped us to build a partial physical map of the deletion. Among the deleted genes, <it>ClpC</it>-like gene coding for a putative subunit of a multifunctional chloroplastic protease involved in the regulation of chlorophyll <it>b </it>synthesis was directly related to the mutated phenotype since the mutant showed a reduced chlorophyll <it>a</it>/<it>b </it>ratio in green tissues.</p> <p>Conclusion</p> <p>In this work, we report the use of array-CGH for the successful identification of genes included in a hemizygous deletion induced by fast neutron irradiation on <it>Citrus clementina</it>. The study of gene content and order into the 39B3 deletion also led to the unexpected conclusion that microsynteny and local gene colinearity in this species were higher with <it>Populus trichocarpa </it>than with the phylogenetically closer <it>Arabidopsis thaliana</it>. This work corroborates the potential of <it>Citrus </it>genomic resources to assist mutagenesis-based approaches for functional genetics, structural studies and comparative genomics, and hence to facilitate citrus variety improvement.</p

Les syndromes hématologiques d'origine toxique chez les carnivores domestiques (étude clinique et synthèse bibliographique)

Les carnivores domestiques sont exposés à de nombreux produits potentiellement toxiques dans leur environnement : produits reconnus toxiques ou médicaments. La toxicité hématologique se manifeste par une augmentation ou une diminution du nombre de cellules sanguines périphériques d'une ou plusieurs lignées cellulaires. Ces cytopénies ont diverses causes : centrales par atteinte médullaire ou périphériques par destruction dans le sang, et conséquences : anémie, hémorragie, immunosuppression Ces modifications de la numération et formule sanguine sont prévisibles ou idiosyncrasiques. Différentes causes de toxicité hématologique à l'exclusion des antivitamines K sont répertoriées ou détaillées, d'après les données fournies par le Centre National d'Informations Toxicologiques Vétérinaires de Lyon (CNITV) entre 1991 et 2004, sous forme d'étude clinique des atteintes centrales puis périphériques, après avoir dressé le diagnostic différentiel des variations du nombre de cellules sanguines.TOULOUSE-EN Vétérinaire (315552301) / SudocSudocFranceF

Significance of the CAPRI risk score to predict heart failure hospitalization post-TAVI: The CAPRI-HF study

International audienc

Primary cutaneous diffuse large B-cell lymphoma, NOS and leg type: Clinical, morphologic and prognostic differences

Background and objectives : Primary cutaneous diffuse large B-cell lymphoma, NOS (PCLBCL/NOS) is a rare PCLBCL. Only few data are available for this tumor. The aim of this study was to identify clinical and/or immunohistochemical markers (in addition to Bcl-2) that characterize PCLBCL/NOS, assist in differentiating it from PCLBCL, leg type (PCLBCL/LT) and help to assess the clinical course/prognosis. Patients and methods : Bcl-2 -PCLBCL/NOS) cases (n = 14 were compared with Bcl-2(+) PCLBCL/LT cases (n = 29). Results : PCLBCL/NOS patients were younger, predominantly male and had better survival rates than patients with PCLBCL/LT. Patients with PCLBCL/NOS presented more often with larger plaques limited to one or two contiguous body regions, whereas PCLBCL/LT cases often presented with disseminated lesions. Neoplastic cells had a higher proliferation rate (Ki67) in PCLBCL/LT patients. The tumor microenvironment of PCLBCL/NOS had a more prominent CD3 + infiltrate. Overall survival data for the whole cohort (n = 37) revealed that female gender and Bcl-2 expression correlated with a worse survival rate. Bcl-6 expression and centroblastic subtype correlated with better outcomes. None of the other markers studied (e. g. GCB/non-GCB subtype) correlated with survival rate. Conclusions : PCLBCL/NOS and PCLBCL/LT differ in their clinical behavior and outcomes. Bcl-2 still seems to be the best marker for discriminating between these two subgroups. Bcl-2, female gender and Bcl-6 represent prognostic markers for PCLBCL

Prolonged SARS-CoV-2 RNA virus shedding and lymphopenia are hallmarks of COVID-19 in cancer patients with poor prognosis

International audiencePatients with cancer are at higher risk of severe coronavirus infectious disease 2019 (COVID-19), but the mechanisms underlying virus–host interactions during cancer therapies remain elusive. When comparing nasopharyngeal swabs from cancer and noncancer patients for RT-qPCR cycle thresholds measuring acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in 1063 patients (58% with cancer), we found that malignant disease favors the magnitude and duration of viral RNA shedding concomitant with prolonged serum elevations of type 1 IFN that anticorrelated with anti-RBD IgG antibodies. Cancer patients with a prolonged SARS-CoV-2 RNA detection exhibited the typical immunopathology of severe COVID-19 at the early phase of infection including circulation of immature neutrophils, depletion of nonconventional monocytes, and a general lymphopenia that, however, was accompanied by a rise in plasmablasts, activated follicular T-helper cells, and non-naive Granzyme B + FasL + , Eomes high TCF-1 high , PD-1 + CD8 + Tc1 cells. Virus-induced lymphopenia worsened cancer-associated lymphocyte loss, and low lymphocyte counts correlated with chronic SARS-CoV-2 RNA shedding, COVID-19 severity, and a higher risk of cancer-related death in the first and second surge of the pandemic. Lymphocyte loss correlated with significant changes in metabolites from the polyamine and biliary salt pathways as well as increased blood DNA from Enterobacteriaceae and Micrococcaceae gut family members in long-term viral carriers. We surmise that cancer therapies may exacerbate the paradoxical association between lymphopenia and COVID-19-related immunopathology, and that the prevention of COVID-19-induced lymphocyte loss may reduce cancer-associated death

The Polarity and Specificity of Antiviral T Lymphocyte Responses Determine Susceptibility to SARS-CoV-2 Infection in Patients with Cancer and Healthy Individuals

International audienceAbstract Vaccination against coronavirus disease 2019 (COVID-19) relies on the in-depth understanding of protective immune responses to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). We characterized the polarity and specificity of memory T cells directed against SARS-CoV-2 viral lysates and peptides to determine correlates with spontaneous, virus-elicited, or vaccine-induced protection against COVID-19 in disease-free and cancer-bearing individuals. A disbalance between type 1 and 2 cytokine release was associated with high susceptibility to COVID-19. Individuals susceptible to infection exhibited a specific deficit in the T helper 1/T cytotoxic 1 (Th1/Tc1) peptide repertoire affecting the receptor binding domain of the spike protein (S1-RBD), a hotspot of viral mutations. Current vaccines triggered Th1/Tc1 responses in only a fraction of all subject categories, more effectively against the original sequence of S1-RBD than that from viral variants. We speculate that the next generation of vaccines should elicit Th1/Tc1 T-cell responses against the S1-RBD domain of emerging viral variants. Significance: This study prospectively analyzed virus-specific T-cell correlates of protection against COVID-19 in healthy and cancer-bearing individuals. A disbalance between Th1/Th2 recall responses conferred susceptibility to COVID-19 in both populations, coinciding with selective defects in Th1 recognition of the receptor binding domain of spike. See related commentary by McGary and Vardhana, p. 892. This article is highlighted in the In This Issue feature, p. 87

A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task

Background: Recent studies have demonstrated the use of convolutional neural networks (CNNs) to classify images of melanoma with accuracies comparable to those achieved by board-certified dermatologists. However, the performance of a CNN exclusively trained with dermoscopic images in a clinical image classification task in direct competition with a large number of dermatologists has not been measured to date. This study compares the performance of a convolutional neuronal network trained with dermoscopic images exclusively for identifying melanoma in clinical photographs with the manual grading of the same images by dermatologists. Methods: We compared automatic digital melanoma classification with the performance of 145 dermatologists of 12 German university hospitals. We used methods from enhanced deep learning to train a CNN with 12,378 open-source dermoscopic images. We used 100 clinical images to compare the performance of the CNN to that of the dermatologists. Dermatologists were compared with the deep neural network in terms of sensitivity, specificity and receiver operating characteristics. Findings: The mean sensitivity and specificity achieved by the dermatologists with clinical images was 89.4% (range: 55.0%-100%) and 64.4% (range: 22.5%-92.5%). At the same sensitivity, the CNN exhibited a mean specificity of 68.2% (range 47.5%-86.25%). Among the dermatologists, the attendings showed the highest mean sensitivity of 92.8% at a mean specificity of 57.7%. With the same high sensitivity of 92.8%, the CNN had a mean specificity of 61.1%. Interpretation: For the first time, dermatologist-level image classification was achieved on a clinical image classification task without training on clinical images. The CNN had a smaller variance of results indicating a higher robustness of computer vision compared with human assessment for dermatologic image classification tasks. (C) 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task

Background: Recent studies have successfully demonstrated the use of deep-learning algorithms for dermatologist-level classification of suspicious lesions by the use of excessive proprietary image databases and limited numbers of dermatologists. For the first time, the performance of a deep-learning algorithm trained by open-source images exclusively is compared to a large number of dermatologists covering all levels within the clinical hierarchy. Methods: We used methods from enhanced deep learning to train a convolutional neural network (CNN) with 12,378 open-source dermoscopic images. We used 100 images to compare the performance of the CNN to that of the 157 dermatologists from 12 university hospitals in Germany. Outperformance of dermatologists by the deep neural network was measured in terms of sensitivity, specificity and receiver operating characteristics. Findings: The mean sensitivity and specificity achieved by the dermatologists with dermoscopic images was 74.1% (range 40.0%-100%) and 60% (range 21.3%-91.3%), respectively. At a mean sensitivity of 74.1%, the CNN exhibited a mean specificity of 86.5% (range 70.8%-91.3%). At a mean specificity of 60%, a mean sensitivity of 87.5% (range 80%-95%) was achieved by our algorithm. Among the dermatologists, the chief physicians showed the highest mean specificity of 69.2% at a mean sensitivity of 73.3%. With the same high specificity of 69.2%, the CNN had a mean sensitivity of 84.5%. Interpretation: A CNN trained by open-source images exclusively outperformed 136 of the 157 dermatologists and all the different levels of experience (from junior to chief physicians) in terms of average specificity and sensitivity. (C) 2019 The Author(s). Published by Elsevier Ltd

Long-term neurological symptoms after acute COVID-19 illness requiring hospitalization in adult patients: insights from the ISARIC-COVID-19 follow-up study

in this study we aimed to characterize the type and prevalence of neurological symptoms related to neurological long-COVID-19 from a large international multicenter cohort of adults after discharge from hospital for acute COVID-19