A comprehensive study on the role of the Yersinia pestis virulence markers in an animal model of pneumonic plague

We determined the role of Yersinia pestis virulence markers in an animal model of pneumonic plague. Eleven strains of Y. pestis were characterized using PCR assays to detect the presence of known virulence genes both encoded by the three plasmids as well as chromosomal markers. The virulence of all Y. pestis strains was compared in a mouse model for pneumonic plague. The presence of all known virulence genes correlated completely with virulence in the Balb/c mouse model. Strains which lacked HmsF initially exhibited visible signs of disease whereas all other strains (except wild-type strains) did not exhibit any disease signs. Forty-eight hours post-infection, mice which had received HmsF– strains regained body mass and were able to control infection; those infected with strains possessing a full complement of virulence genes suffered from fatal disease. The bacterial loads observed in the lung and other tissues reflected the observed clinical signs as did the cytokine changes measured in these animals. We can conclude that all known virulence genes are required for the establishment of pneumonic plague in mammalian animal models, the role of HmsF being of particular importance in disease progression

Drug Design for CNS Diseases: Polypharmacological Profiling of Compounds Using Cheminformatic, 3D-QSAR and Virtual Screening Methodologies.

HIGHLIGHTS Many CNS targets are being explored for multi-target drug designNew databases and cheminformatic methods enable prediction of primary pharmaceutical target and off-targets of compoundsQSAR, virtual screening and docking methods increase the potential of rational drug design The diverse cerebral mechanisms implicated in Central Nervous System (CNS) diseases together with the heterogeneous and overlapping nature of phenotypes indicated that multitarget strategies may be appropriate for the improved treatment of complex brain diseases. Understanding how the neurotransmitter systems interact is also important in optimizing therapeutic strategies. Pharmacological intervention on one target will often influence another one, such as the well-established serotonin-dopamine interaction or the dopamine-glutamate interaction. It is now accepted that drug action can involve plural targets and that polypharmacological interaction with multiple targets, to address disease in more subtle and effective ways, is a key concept for development of novel drug candidates against complex CNS diseases. A multi-target therapeutic strategy for Alzheimer's disease resulted in the development of very effective Multi-Target Designed Ligands (MTDL) that act on both the cholinergic and monoaminergic systems, and also retard the progression of neurodegeneration by inhibiting amyloid aggregation. Many compounds already in databases have been investigated as ligands for multiple targets in drug-discovery programs. A probabilistic method, the Parzen-Rosenblatt Window approach, was used to build a "predictor" model using data collected from the ChEMBL database. The model can be used to predict both the primary pharmaceutical target and off-targets of a compound based on its structure. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. Based on all these findings, it is concluded that multipotent ligands targeting AChE/MAO-A/MAO-B and also D1-R/D2-R/5-HT2A -R/H3-R are promising novel drug candidates with improved efficacy and beneficial neuroleptic and procognitive activities in treatment of Alzheimer's and related neurodegenerative diseases. Structural information for drug targets permits docking and virtual screening and exploration of the molecular determinants of binding, hence facilitating the design of multi-targeted drugs. The crystal structures and models of enzymes of the monoaminergic and cholinergic systems have been used to investigate the structural origins of target selectivity and to identify molecular determinants, in order to design MTDLs

Real-Time 3D Ultrasound Reconstruction Using Octrees

Ultrasound is a major medical imaging modality that is widely used in healthcare because of advantages such as the use of nonionizing radiation, ease of operation, real-time imaging from different perspectives, and low operation costs. The most common ultrasound modality produces two-dimensional images (2D) with a 1D-array transducer. However, in recent years, three-dimensional ultrasound (3D US) imaging has become increasingly relevant. There are many reasons behind this shift. For example, 3D US images are easier to register with 3D images from another modality while patients undergo procedures or during presurgical planning. In particular, 3D freehand ultrasound (FUS) imaging yields 3D US images of large anatomical regions at low cost. An area of interest is scanned with a conventional 1D-array transducer, which is tracked with an attached device; the resulting 2D US images are input into a reconstruction algorithm; and the brightness values are assigned to a 3D image. Several 3D reconstruction algorithms in FUS imaging have been proposed and clinically used, and in the present work, we report a new neighbor search-based approach for reconstructing 3D FUS images based on hierarchical octrees with Morton key coding that can be implemented on GPUs using CUDA® kernels to exploit multithreading. Our approach achieves considerably faster throughput for high-resolution 3D images and can reconstruct 3D US images with dimensions of $128\times 128\times 128$ voxels in approximately 0.5 s. The proposed approach is a viable option for obtaining 3D US images in real time based on sets of freehand 2D ultrasound images acquired with 1D-array transducers

The epizootiology of ovine gastrointestinal strongyles in the province of Matanzas, Cuba

International audienceThe gastrointestinal parasitism in Cuba threatens sheep exploitation programs and their control practices rely mainly in the indiscriminate use of anthelmitics. The study was carried out for 2 years (2000–2002) in three ovine farms in Matanzas Province (Dos Mercedes, LABIOFAM and the EEPF “Indio Hatuey” farm) which are representative of sheep industry in the province. Faeces and grass were collected monthly for parasitological analysis in the three units. The ewes body condition score (BCS) were recorded each month based on a five points scale. The three herds were mainly affected by Haemonchus spp. and to a lesser extent by Trichostrongylus colubriformis and Oesophagostomum columbianum. The faecal egg count (FECs) increased during the dry season, while the L3 pasture infestation decreased in this season, reaching the highest values during the rainy season. The relationship between the animal category and the FECs depends on the management system. The ewe reproductive status was related with FEC in which lactating ewes are more susceptible to parasite infection