Selection of adequate optimization criteria in chromatographic separations

Computer-assisted optimization of chromatographic separations is still a fruitful activity. In fact, advances in computerized data handling should make the application of systematic optimization strategies much easier. However, in most contemporary applications, the optimization criterion is not considered to be a key issue (Vanbel, J Pharm Biomed, 21:603–610, 1999). In this paper, an update of the importance of selecting adequate criteria in chromatographic separation is presented

Evaluation of 3-(3-chloro-phenyl)-5-(4-pyridyl)-4,5-dihydroisoxazole as a Novel Anti-Inflammatory Drug Candidate

BACKGROUND: 3-(3-chloro-phenyl)-5-(4-pyridyl)-4,5-dihydroisoxazole (DIC) is a five-membered heterocyclic compound containing a N-O bond. The anti-inflammatory effects of this compound were studied both in vitro and in vivo. PRINCIPAL FINDINGS: DIC effectively decreased TNF-α and IL-6 release from LPS-stimulated macrophages in a dose dependent manner. DIC diminished the levels of COX-2 with subsequent inhibition of PGE(2) production. DIC also compromised HMGB1 translocation from the nucleus to the cytoplasm. Moreover, DIC prevented the nuclear translocation of NF-κB and inhibited the MAPK pathway. In vivo, DIC inhibited migration of neutrophils to the peritoneal cavity of mice. CONCLUSIONS: This study presents the potential utilization of a synthetic compound, as a lead for the development of novel anti-inflammatory drugs

Prevalence and Factors Associated with Leishmania infantum Infection of Dogs from an Urban Area of Brazil as Identified by Molecular Methods

Visceral leishmaniasis (VL) is a disease caused by the parasite Leishmania infantum, and dogs are the most important domestic reservoirs of the agent. During recent decades, VL has expanded to large Brazilian urban centers. In the present work, we have demonstrated by using molecular techniques that the rate of canine infection as detected by serology has been considerably underestimated. Two groups of seronegative dogs (infected and non-infected according to molecular methods) were further evaluated from data obtained through interviews with owners of the animals. The factors associated with Leishmania infection in dogs were a family income of less than two minimum salaries, the knowledge of the owner regarding the vector, the dog spending most of its time in the backyard and the dog never having had a previous serological examination. Awareness regarding the factors associated with canine infection will improve health services and the understanding of the disease's expansion in urban areas

General Automatic Human Shape and Motion Capture Using Volumetric Contour Cues

Markerless motion capture algorithms require a 3D body with properly personalized skeleton dimension and/or body shape and appearance to successfully track a person. Unfortunately, many tracking methods consider model personalization a different problem and use manual or semi-automatic model initialization, which greatly reduces applicability. In this paper, we propose a fully automatic algorithm that jointly creates a rigged actor model commonly used for animation - skeleton, volumetric shape, appearance, and optionally a body surface - and estimates the actor's motion from multi-view video input only. The approach is rigorously designed to work on footage of general outdoor scenes recorded with very few cameras and without background subtraction. Our method uses a new image formation model with analytic visibility and analytically differentiable alignment energy. For reconstruction, 3D body shape is approximated as Gaussian density field. For pose and shape estimation, we minimize a new edge-based alignment energy inspired by volume raycasting in an absorbing medium. We further propose a new statistical human body model that represents the body surface, volumetric Gaussian density, as well as variability in skeleton shape. Given any multi-view sequence, our method jointly optimizes the pose and shape parameters of this model fully automatically in a spatiotemporal way

Genomic Surveillance of Yellow Fever Virus Epizootic in São Paulo, Brazil, 2016 – 2018

São Paulo, a densely inhabited state in southeast Brazil that contains the fourth most populated city in the world, recently experienced its largest yellow fever virus (YFV) outbreak in decades. YFV does not normally circulate extensively in São Paulo, so most people were unvaccinated when the outbreak began. Surveillance in non-human primates (NHPs) is important for determining the magnitude and geographic extent of an epizootic, thereby helping to evaluate the risk of YFV spillover to humans. Data from infected NHPs can give more accurate insights into YFV spread than when using data from human cases alone. To contextualise human cases, identify epizootic foci and uncover the rate and direction of YFV spread in São Paulo, we generated and analysed virus genomic data and epizootic case data from NHPs in São Paulo. We report the occurrence of three spatiotemporally distinct phases of the outbreak in São Paulo prior to February 2018. We generated 51 new virus genomes from YFV positive cases identified in 23 different municipalities in São Paulo, mostly sampled from NHPs between October 2016 and January 2018. Although we observe substantial heterogeneity in lineage dispersal velocities between phylogenetic branches, continuous phylogeographic analyses of generated YFV genomes suggest that YFV lineages spread in São Paulo at a mean rate of approximately 1km per day during all phases of the outbreak. Viral lineages from the first epizootic phase in northern São Paulo subsequently dispersed towards the south of the state to cause the second and third epizootic phases there. This alters our understanding of how YFV was introduced into the densely populated south of São Paulo state. Our results shed light on the sylvatic transmission of YFV in highly fragmented forested regions in São Paulo state and highlight the importance of continued surveillance of zoonotic pathogens in sentinel species