Virus du type pox pathogènes pour les invertébrés

Vago Constantin. Virus du type pox pathogènes pour les invertébrés. In: Bulletin de l'Académie Vétérinaire de France tome 123 n°1, 1970. pp. 59-64

Production of the soluble pattern recognition receptor PTX3 by myeloid, but not plasmacytoid, dendritic cells

PTX3 is a prototypic of long pentraxin consisting of an N-terminal portion coupled to a C-terminal pentraxin domain, the latter related to short pentraxins (C-reactive protein and serum amyloid P component). PTX3 is a soluble pattern recognition receptor, which plays a non-redundant role in resistance against selected pathogens and in female fertility. The present study was designed to analyze the production of PTX3 by human dendritic cells (DC) and to define the role of different innate immunity receptors in its induction. Human monocyte-derived DC produced copious amounts of PTX3 in response to microbial ligands engaging different members of the Toll-like receptor (TLR) family (TLR1 through TLR6), whereas engagement of the mannose receptor had no substantial effect. DC were better producers of PTX3 than monocytes and macrophages. Freshly isolated peripheral blood myeloid DC produced PTX3 in response to diverse microbial stimuli. In contrast, plasmacytoid DC exposed to influenza virus or to CpG oligodeoxynucleotides engaging TLR9, did not produce PTX3. PTX3-expressing DC were present in inflammatory lymph nodes from HIV-infected patients. These results suggest that DC of myelomonocytic origin are a major source of PTX3, a molecule which facilitates pathogen recognition and subsequent activation of innate and adaptive immunity

First Record of Fusarium verticillioides as an Entomopathogenic Fungus of Grasshoppers

Fusarium verticillioides (Saccardo) Nirenberg (Ascomycota: Hypocreales) is the most common fungus reported on infected corn kernels and vegetative tissues, but has not yet been documented as being entomopathogenic for grasshoppers. Grasshoppers and locusts represent a large group of insects that cause economic damage to forage and crops. Tropidacris collaris (Stoll) (Orthoptera: Acridoidea: Romaleidae) is a large and voracious grasshopper that in recent years has become an increasingly recurrent and widespread pest in progressively more greatly extended areas of some of in Argentina's northern provinces, with chemical insecticides being currently the only means of control. During February and March of 2008–09, nymphs and adults of T. collaris were collected with sweep nets in dense woodland vegetation at a site near Tres Estacas in western Chaco Province, Argentina, and kept in screened cages. F. verticillioides was isolated from insects that died within 10 days and was cultured in PGA medium. Pathogenicity tests were conducted and positive results recorded. Using traditional and molecular-biological methods, an isolate of F. verticillioides was obtained from T. collaris, and its pathogenecity in the laboratory was shown against another harmful grasshopper, Ronderosia bergi (Stål) (Acridoidea: Acrididae: Melanoplinae). The mortality caused by F. verticillioides on R. bergi reached 58 ± 6.53% by 10 days after inoculation. This is the first record of natural infection caused by F. verticillioides in grasshoppers

Trivial centralizers for Axiom A diffeomorphisms

We show there is a residual set of non-Anosov $C^{\infty}$ Axiom A diffeomorphisms with the no cycles property whose elements have trivial centralizer. If $M$ is a surface and $2\leq r\leq \infty$, then we will show there exists an open and dense set of of $C^r$ Axiom A diffeomorphisms with the no cycles property whose elements have trivial centralizer. Additionally, we examine commuting diffeomorphisms preserving a compact invariant set $\Lambda$ where $\Lambda$ is a hyperbolic chain recurrent class for one of the diffeomorphisms.Comment: 18 page

Prediction of incident cardiovascular events using machine learning and CMR radiomics.

OBJECTIVES: Evaluation of the feasibility of using cardiovascular magnetic resonance (CMR) radiomics in the prediction of incident atrial fibrillation (AF), heart failure (HF), myocardial infarction (MI), and stroke using machine learning techniques. METHODS: We identified participants from the UK Biobank who experienced incident AF, HF, MI, or stroke during the continuous longitudinal follow-up. The CMR indices and the vascular risk factors (VRFs) as well as the CMR images were obtained for each participant. Three-segmented regions of interest (ROIs) were computed: right ventricle cavity, left ventricle (LV) cavity, and LV myocardium in end-systole and end-diastole phases. Radiomics features were extracted from the 3D volumes of the ROIs. Seven integrative models were built for each incident cardiovascular disease (CVD) as an outcome. Each model was built with VRF, CMR indices, and radiomics features and a combination of them. Support vector machine was used for classification. To assess the model performance, the accuracy, sensitivity, specificity, and AUC were reported. RESULTS: AF prediction model using the VRF+CMR+Rad model (accuracy: 0.71, AUC 0.76) obtained the best result. However, the AUC was similar to the VRF+Rad model. HF showed the most significant improvement with the inclusion of CMR metrics (VRF+CMR+Rad: 0.79, AUC 0.84). Moreover, adding only the radiomics features to the VRF reached an almost similarly good performance (VRF+Rad: accuracy 0.77, AUC 0.83). Prediction models looking into incident MI and stroke reached slightly smaller improvement. CONCLUSIONS: Radiomics features may provide incremental predictive value over VRF and CMR indices in the prediction of incident CVDs. KEY POINTS: • Prediction of incident atrial fibrillation, heart failure, stroke, and myocardial infarction using machine learning techniques. • CMR radiomics, vascular risk factors, and standard CMR indices will be considered in the machine learning models. • The experiments show that radiomics features can provide incremental predictive value over VRF and CMR indices in the prediction of incident cardiovascular diseases