Segmentation of center brains and optic lobes in 3D confocal images of adult fruit fly brains

Automatic alignment (registration) of 3D images of adult fruit fly brains is often influenced by the significant displacement of the relative locations of the two optic lobes (OLs) and the center brain (CB). In one of our ongoing efforts to produce a better image alignment pipeline of adult fruit fly brains, we consider separating CB and OLs and align them independently. This paper reports our automatic method to segregate CB and OLs, in particular under conditions where the signal to noise ratio (SNR) is low, the variation of the image intensity is big, and the relative displacement of OLs and CB is substantial.We design an algorithm to find a minimum-cost 3D surface in a 3D image stack to best separate an OL (of one side, either left or right) from CB. This surface is defined as an aggregation of the respective minimum-cost curves detected in each individual 2D image slice. Each curve is defined by a list of control points that best segregate OL and CB. To obtain the locations of these control points, we derive an energy function that includes an image energy term defined by local pixel intensities and two internal energy terms that constrain the curve’s smoothness and length. Gradient descent method is used to optimize this energy function. To improve both the speed and robustness of the method, for each stack, the locations of optimized control points in a slice are taken as the initialization prior for the next slice. We have tested this approach on simulated and real 3D fly brain image stacks and demonstrated that this method can reasonably segregate OLs from CBs despite the aforementioned difficulties.     

Crystal structure of a truncated urease accessory protein UreF from Helicobacter pylori

Urease plays a central role in the pathogenesis of Helicobacter pylori in humans. Maturation of this nickel metalloenzyme in bacteria requires the participation of the accessory proteins UreD (termed UreH in H. pylori), UreF, and UreG, which form sequential complexes with the urease apoprotein as well as UreE, a metallochaperone. Here, we describe the crystal structure of C‐terminal truncated UreF from H. pylori (residues 1–233), the first UreF structure to be determined, at 1.55 Å resolution using SAD methods. UreF forms a dimer in vitro and adopts an all‐helical fold congruent with secondary structure prediction. On the basis of evolutionary conservation analysis, the structure reveals a probable binding surface for interaction with other urease components as well as key conserved residues of potential functional relevance. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Diamino-1,2,4-triazole derivatives are selective inhibitors of TYK2 and JAK1 over JAK2 and JAK3

Tyrosine kinase 2 (TYK2) is required for signaling of interleukin-23 (IL-23), which plays a key role in rheumatoid arthritis. Presented is the design and synthesis of 1,2,4-triazoles, and the evaluation of their inhibitory activity against the Janus associated kinases TYK2 and JAKs 1-3.     

Synthesis,characterization and preliminary analysis of in vivo biological activity of chitosan/celecoxib microcapsules

The use of chitosan as the wall of microcapsule designed for delivery of encapsulated celecoxib is reported. Microcapsules were characterised with respect to size and encapsulation efficiency of celecoxib. In vivo animals demonstrated that both free celecoxib administration and chitosan/celecoxib microcapsules administration lead to a significant inhibition of cyclooxygenase-2 protein expression in the hepatocytes when compared with vehicle control mice. Interestingly, microcapsule containing celecoxib showed a better inhibition of cyclooxygenase-2 protein expression when compared with a simple oral administration of free celecoxib. Gas-chromatography–mass-spectrometry analysis showed that in mice treated with free celecoxib or chitosan/celecoxib microcapsules, their plasma concentration of celecoxib was similar. Microcapsules-based biomaterials as oral drug delivery vehicles may help to improve the absorption efficiency of therapeutic drugs.     

Quantitative analysis of anandamide and related acylethanolamides in human seminal plasma by ultra performance liquid chromatography tandem mass spectrometry

The endocannabinoids anandamide, palmitoylethanolamide and oleoylethanolamide have been detected in human seminal plasma and are bioactive lipids implicated in regulation of sperm motility, capacitation and acrosome reaction. Several methods exist for endocannabinoid quantification but none have been validated for measurement in human seminal plasma. We describe sensitive, robust, reproducible solid phase and isotope-dilution UHPLC-ESI-MS/MS methods for the extraction and quantification of anandamide, palmitoylethanolamide and oleoylethanolamide in human seminal plasma. Precision and accuracy were evaluated using pooled seminal plasma over a 4 day period. For all analytes, the inter- and intraday precision (CV%) was between 6.6-17.7% and 6.3-12.5%, respectively. Analyses were linear over the range 0.237-19nM for anandamide and oleoylethanolamide and 0.9-76nM for PEA. Limits of detection (signal-to-noise >3) were 50, 100 and 100fmol/mL and limits of quantification (signal-to-noise >10) were 100, 200 and 200fmol/mL, respectively for anandamide, palmitoylethanolamide and oleoylethanolamide. Anandamide and oleoylethanolamide were stable at -80°C for up to 4 weeks, but palmitoylethanolamide declined significantly. We assessed seminal plasma from 40 human donors with normozoospermia and found mean (inter-quartile range) concentrations of 0.21nM (0.09-0.27), 1.785nM (0.48-2.32) and 15.54nM (7.05-16.31) for anandamide, oleoylethanolamide and palmitoylethanolamide, respectively. Consequently, this UHPLC-ESI-MS/MS method represents a rapid, reliable and reproducible technique for the analysis of these endocannabinoids in fresh seminal plasma.     

JC virus-induced Progressive Multifocal Leukoencephalopathy

Progressive multifocal encephalopathy (PML) is a fatal demyelinating disease of the central nervous system (CNS), caused by the lytic infection of oligodendrocytes by a human polyomavirus, JC virus (JCV). PML is rare disease but mostly develops in patients with underlying immunosuppressive conditions, including Hodgkin's lymphoma, lymphoproliferative diseases, in those undergoing antineoplastic therapy and AIDS. However, consistent with the occurrence of PML under immunocompromised conditions, this disease seems to be also steadily increasing among autoimmune disease patients (multiple sclerosis and Crohn's disease), who are treated with antibody-based regimens (natalizumab, efalizumab and rituximab). This unexpected occurrence of the disease among such a patient population reconfirms the existence of a strong link between the underlying immunosuppressive conditions and development of PML. These recent observations have generated a new interest among investigators to further examine the unique biology of JCV.     

Unusual stilbenoids and a stilbenolignan from seeds of Syagrus romanzoffiana

Stilbenoids, syagrusins A-B (1-2), and a stilbenolignan, 5-hydroxyaiphanol (3), along with three known phenylpropanoids (4-6), were isolated from seeds of Syagrus romanzoffiana. Compounds 1 and 2 possess unusual 1,4,4a,9a-tetrahydrofluoren-9-one and bicyclo[3.3.0]octanedione skeletons, respectively, whereas compound 3 is a stilbenolignan belonging to a very rare structural class of plant secondary metabolites. Their structures were elucidated by spectroscopic analyses. Compounds 1-3 exhibited moderate inhibitory activity against α-glucosidase with IC₅₀ values of 16.9 μM (1), 23.7 μM (2) and 12.8 μM (3), respectively.     

Biochemical Characterization of the Cell-Biomaterial Interface by Quantitative Proteomics

Surface topography and texture of cell culture substrata can affect the differentiation and growth of adherent cells. The biochemical basis of the transduction of the physical and mechanical signals to cellular responses is not well understood. The lack of a systematic characterization of cell-biomaterial interaction is the major bottleneck. This study demonstrated the use of a novel subcellular fractionation method combined with quantitative MS-based proteomics to enable the robust and high-throughput analysis of proteins at the adherence interface of Madin-Darby canine kidney cells. This method revealed the enrichment of extracellular matrix proteins and membrane and stress fibers proteins at the adherence surface, whereas it shows depletion of extracellular matrix belonging to the cytoplasmic, nucleus, and lateral and apical membranes. The asymmetric distribution of proteins between apical and adherence sides was also profiled. Apart from classical proteins with clear involvement in cell-material interactions, proteins previously not known to be involved in cell attachment were also discovered.The growth and differentiation of cells in multicellular organisms are regulated by the complex interplay of biochemical and mechanical signals. In the past decades, a plethora of data on the roles of mechanical and structural cues in modulating cellular behaviors has emerged (1–5). It is increasingly evident that cell fates can be changed by engineering the physical properties of the microenvironment to which the cells are exposed (6–8). These observations have inspired the development of functionalized biomaterials that can directly and specifically interact with tissue components, and support or even direct the appropriate cellular activities (9, 10). Although promising progress has been observed in the past few years, several gaps in knowledge in this field have hindered the development of such ”intelligent” biomaterials. In particular, the understanding of the mechanism in which the cell orchestrates physiological and morphological changes by translating mechanical and structural information into biochemical signals is still very limited.As a standard experimental model, cell lines cultured in vitro as a monolayer over solid substrata are usually used to study the effects of biomaterial surfaces on cellular phenotypes. With this simple model system, ingenious experiments have shown that physical forces applied through the extracellular matrix (ECM)1 can induce changes in cell adhesion molecules and stress-induced ion channels, which then lead to changes in the cytoskeleton and gene expressions (11–13). We term the biochemical structure present at the interface between the substratum and the cellular interior the adherence surface (AS), which is composed of the basal plasma membrane with associated structures such as the ECM on one side and the focal adherence complexes on the other. In monolayer cell culture systems, the AS is the only part of the cells in direct contact with the substratum, and is therefore responsible for the first line of communication between the cells and the biomaterial. It is likely that the AS is the organelle that mediates the communication of mechanical and tectonic signals from the substratum to biochemical transducers in the cells. Given the complexity of this process, it is clear that the understanding of this phenomenon cannot be achieved merely by studying individual biological parts in isolation. It is necessary, therefore, to systematically characterize the biochemical factors that mediate the interactions between cells and materials to yield insights into intracellular signaling processes that are responsible for such cellular responses. Toward this goal, we seek to investigate the biochemical basis of how different biomaterials may impose changes in the composition of the AS of adherent cells.MS-based proteomics have recently emerged as a standard technique in modern cell biology. Various techniques based on the chemical conjugation of isotopically labeled reporters to proteins or peptides, such as the isobaric tag for relative and absolute quantitation (iTRAQ) and the isotope-coded affinity tags, enable MS-based proteomics to quantify and compare proteome changes between biological samples. As an attractive alternative, stable isotope labeling with amino acids in cell culture (SILAC) is a metabolic labeling technique that enables isotopically encoded cells to be mixed before lysis and fractionation, thus eliminating inherent quantification biases in these steps, and also enables a simpler procedure and more accurate quantitation (14). SILAC MS-based proteomics have recently contributed to organellar proteomes (15, 16), accurate measurement of protein-protein interactions (17), and the characterization of proteome dynamics during cell differentiation (18). The use of MS-based proteomics has enabled the systematic evaluation of proteome changes on the adhesion of cells to substrata of interest. Kantawong et al. (19) applied DIGE and LC-MS/MS to identify proteome changes in cells on surface with nanotopography. Xu et al. (20) investigated proteome differences of human osteoblasts on various nano-sized hydroxyapatite powders with different shapes and chemical compositions using iTRAQ-based two-dimensional LC-MS/MS.One advantage of proteomics is that it can effectively be combined with subcellular fractionation and allow the comprehensive characterization of the proteins enriched in targeted cellular structures. To yield new insight in molecular interactions in cell-biomaterial interfaces, we aimed to develop a robust protocol for the proteomic characterization of the AS of adherent cells on a biomaterial surface and use it for discovering new cell-biomaterial interface specific biomarkers. Our approach was to develop an isolation technique for AS with high yields and purity for proteomic analysis. The isolated AS on substratum was analyzed by confocal microscopy and Western blotting. SILAC was then used to characterize the fold-enrichment of proteins in the purified AS compared with whole cells and to discover new biomolecules in the cell-biomaterial interface. This study introduces a novel cell-biomaterial interface proteomic procedure, which can be used to identify the AS specific proteome in a high throughput manner and provide a simple and robust method to systematically analyze cell-biomaterial interactions at a molecular level.     

Merits of Modelling Multivariate Survival Data Using Random Effects Proportional Odds Model

Recently, there has been a great deal of interest in the analysis of multivariate survival data. In most epidemiological studies, survival times of the same cluster are related because of some unobserved risk factors such as the environmental or genetic factors. Therefore, modelling of dependence between events of correlated individuals is required to ensure a correct inference on the effects of treatments or covariates on the survival times. In the past decades, extension of proportional hazards model has been widely considered for modelling multivariate survival data by incorporating a random effect which acts multiplicatively on the hazard function. In this article, we consider the proportional odds model, which is an alternative to the proportional hazards model at which the hazard ratio between individuals converges to unity eventually. This is a reasonable property particularly when the treatment effect fades out gradually and the homogeneity of the population increases over time. The objective of this paper is to assess the influence of the random effect on the within‐subject correlation and the population heterogeneity. We are particularly interested in the properties of the proportional odds model with univariate random effect and correlated random effect. The correlations between survival times are derived explicitly for both choices of mixing distributions and are shown to be independent of the covariates. The time path of the odds function among the survivors are also examined to study the effect of the choice of mixing distribution. Modelling multivariate survival data using a univariate mixing distribution may be inadequate as the random effect not only characterises the dependence of the survival times, but also the conditional heterogeneity among the survivors. A robust estimate for the correlation of the logarithm of the survival times within a cluster is obtained disregarding the choice of the mixing distributions. The sensitivity of the estimate of the regression parameter under a misspecification of the mixing distribution is studied through simulation. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)