Reaction of superoxide radicals with glycosaminoglycan chloramides: a kinetic study.

Hypochlorous acid and its acid-base counterpart, hypochlorite ions, produced under inflammatory conditions, may produce chloramides of glycosaminoglycans, perhaps through the binding of myeloperoxidase directly to the glycosaminoglycans. The N-Cl group in the chloramides is a potential target for reducing species such as Cu(I) and superoxide radicals. Laser flash photolysis has been used here to obtain, for the first time, the rate constants for the direct reaction of superoxide radicals with the chloramides of hyaluronan and heparin. The rate constants were in the range 2.2-2.7 × 103 M-1 s-1. The rate constant for the reaction with the amino acid taurine was found to be much lower, at 3.5-4.0 × 102 M-1 s-1. This demonstration that superoxide anion radicals react directly with hyaluronan and heparin chloramides may support the mechanism first proposed by M.D. Rees et al. (Biochem. J. 381, 175-184, 2004) for an efficient fragmentation of these glycosaminoglycans in the extracellular matrix under inflammatory conditions. © 2013 Elsevier Inc

Application of 3D MAPs pipeline identifies the morphological sequence chondrocytes undergo and the regulatory role of GDF5 in this process

The activity of epiphyseal growth plates, which drives long bone elongation, depends on extensive changes in chondrocyte size and shape during differentiation. Here, we develop a pipeline called 3D Morphometric Analysis for Phenotypic significance (3D MAPs), which combines light-sheet microscopy, segmentation algorithms and 3D morphometric analysis to characterize morphogenetic cellular behaviors while maintaining the spatial context of the growth plate. Using 3D MAPs, we create a 3D image database of hundreds of thousands of chondrocytes. Analysis reveals broad repertoire of morphological changes, growth strategies and cell organizations during differentiation. Moreover, identifying a reduction in Smad 1/5/9 activity together with multiple abnormalities in cell growth, shape and organization provides an explanation for the shortening of Gdf5 KO tibias. Overall, our findings provide insight into the morphological sequence that chondrocytes undergo during differentiation and highlight the ability of 3D MAPs to uncover cellular mechanisms that may regulate this process

PROMO: An interactive tool for analyzing clinically-labeled multi-omic cancer datasets

AbstractBackgroundAnalysis of large genomic datasets along with their accompanying clinical information has shown great promise in cancer research over the last decade. Such datasets typically include thousands of samples, each measured by one or several high-throughput technologies (‘omics’) and annotated with extensive clinical information. While instrumental for fulfilling the promise of personalized medicine, the analysis and visualization of such large datasets is challenging and necessitates programming skills and familiarity with a large array of software tools to be used for the various steps of the analysis.ResultsWe developed PROMO (Profiler of Multi-Omic data), a friendly, fully interactive stand-alone software for analyzing large genomic cancer datasets together with their associated clinical information. The tool provides an array of built-in methods and algorithms for importing, preprocessing, visualizing, clustering, clinical label enrichment testing and survival analysis that can be performed on a single or multi-omic dataset. The tool can be used for quick exploration and for stratification of tumor samples taken from patients into clinically significant molecular subtypes. Identification of prognostic biomarkers and generation of simple subtype classifiers are additional important features. We review PROMO’s main features and demonstrate its analysis capabilities on a breast cancer cohort from TCGA.ConclusionsPROMO provides a single integrated solution for swiftly performing a complete analysis of cancer genomic data for subtype discovery and biomarker identification without writing a single line of code, and can, therefore, make the analysis of these data much easier for cancer biologists and biomedical researchers. PROMO is freely available for download at http://acgt.cs.tau.ac.il/promo/.</jats:sec

PROMO: an interactive tool for analyzing clinically-labeled multi-omic cancer datasets

Abstract Background Analysis of large genomic datasets along with their accompanying clinical information has shown great promise in cancer research over the last decade. Such datasets typically include thousands of samples, each measured by one or several high-throughput technologies (‘omics’) and annotated with extensive clinical information. While instrumental for fulfilling the promise of personalized medicine, the analysis and visualization of such large datasets is challenging and necessitates programming skills and familiarity with a large array of software tools to be used for the various steps of the analysis. Results We developed PROMO (Profiler of Multi-Omic data), a friendly, fully interactive stand-alone software for analyzing large genomic cancer datasets together with their associated clinical information. The tool provides an array of built-in methods and algorithms for importing, preprocessing, visualizing, clustering, clinical label enrichment testing, and survival analysis that can be performed on a single or multi-omic dataset. The tool can be used for quick exploration and stratification of tumor samples taken from patients into clinically significant molecular subtypes. Identification of prognostic biomarkers and generation of simple subtype classifiers are additional important features. We review PROMO’s main features and demonstrate its analysis capabilities on a breast cancer cohort from TCGA. Conclusions PROMO provides a single integrated solution for swiftly performing a complete analysis of cancer genomic data for subtype discovery and biomarker identification without writing a single line of code, and can, therefore, make the analysis of these data much easier for cancer biologists and biomedical researchers. PROMO is freely available for download at http://acgt.cs.tau.ac.il/promo/. </jats:sec

MOESM1 of PROMO: an interactive tool for analyzing clinically-labeled multi-omic cancer datasets

Additional file 1: Figure S1. Clustering Panel. Figure S2. Biomarker Discovery. Table S1. List of differentially expressed genes. Figure S3. Label Management Panel. Figure S4. Multi-omic sample clustering

A symbiotic-like biologically-driven regenerating fabric

Living organisms constantly maintain their structural and biochemical integrity by the critical means of response, healing, and regeneration. Inanimate objects, on the other hand, are axiomatically considered incapable of responding to damage and healing it, leading to the profound negative environmental impact of their continuous manufacturing and trashing. Objects with such biological properties would be a significant step towards sustainable technology. In this work we present a feasible strategy for driving regeneration in fabric by means of integration with a bacterial biofilm to obtain a symbiotic-like hybrid - the fabric provides structural framework to the biofilm and supports its growth, whereas the biofilm responds to mechanical tear by synthesizing a silk protein engineered to self-assemble upon secretion from the cells. We propose the term crossbiosis to describe this and other hybrid systems combining organism and object. Our strategy could be implemented in other systems and drive sensing of integrity and response by regeneration in other materials as well

Development of migrating entheses involves replacement of progenitor populations

AbstractAttachment sites of tendons to bones, called entheses, are essential for proper musculoskeletal function. They are formed embryonically bySox9+ progenitors and undergo a developmental process that continues into the postnatal period and involvesGli1lineage cells. During bone elongation, some entheses maintain their relative positions by actively migrating along the bone shaft, while others, located at the bone’s extremities, remain stationary. Despite their importance, we lack information on the developmental transition from embryonic to mature enthesis and on the relation betweenSox9+ progenitors andGli1lineage cells. Here, by performing a series of lineage tracing experiments, we identify the onset ofGli1lineage contribution to different entheses during embryogenesis. We show thatGli1expression is regulated by SHH signaling during embryonic development, whereas postnatally it is maintained by IHH signaling. Interestingly, we found that unlike in stationary entheses, whereSox9+ cells differentiate into theGli1lineage, in migrating entheses theSox9lineage is replaced byGli1lineage and do not contribute to the mature enthesis. Moreover, we show that theseGli1+progenitors are pre-specified embryonically to form the different cellular domains of the mature enthesis.Overall, these findings demonstrate a developmental strategy whereby one progenitor population establishes a simple, embryonic tissue, whereas another population is responsible for its maturation into a complex structure during its migration. Moreover, they suggest that different cell populations may be considered for cell-based therapy of enthesis injuries.</jats:p