A structural analysis of heparin-like glycosaminoglycans using MALDI-TOF mass spectrometry

Abstract. Mass spectrometry (MS) techniques have spear-headed the field of proteomics. Recently, MS has been used to structurally analyse carbohydrates. The heparin/heparan sulfate-like glycosaminoglycans (HLGAGs) present a special set of difficulties for structural analysis because they are highly sulfated and heterogeneous. We have used a matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-MS) technique in which heparin fragments are non-covalently bound to basic peptides of a known mass, so as to limit in-source desulfation and hence afford an accurate mass. We examined a range of different sized fragments with varying degrees of sulfation. The potential of combining the MALDI-MS technique with enzymatic digestion to obtain saccharide sequence information on heparin fragments was explored. A disaccharide analysis greatly assists in determining a sequence from MALDI-MS data. Enzymatic digestion followed by MALDI-MS allows structural data on heparin fragments too large for direct MALDI-MS to be obtained. We demonstrate that synthetic sulfated oligosaccharides can also be analysed by MALDI-MS. There are advantages and limitations with this methodology, but until superior MS techniques become readily accessible to biomedical scientists the MALDI-MS method provides a means to structurally analyse HLGAG fragments that have therapeutic potential because of their ability to bind to and functionally regulate a host of clinically important proteins

The reaction of acetylacetone with amino sugars: implications for the formation of glycosylpyrazole derivatives

Glycosylpyrazoles are efficiently formed by reaction of saccharide hydrazones with pentan-2,4-dione (acetylacetone), but in aqueous buffer, pyrazole derivatives of amino sugars couple with a further equivalent of acetylacetone affording high yields of ketoenamines. These ketoenamines were considerably more stable than the ketoenamines formed from 2-amino-2-deoxy aldoses that have been described as intermediates in the classical Elson-Morgan reaction. Moreover, high yields of perketoenamine derivatives were achieved with oligosaccharides derived from hydrolysis of chitosan. The removal of the ketoenamine moieties to regenerate the free amine was readily accomplished with aqueous hydrazine.8 page(s

Heterocyclic derivatives of sugars: the formation of 1-glycosyl-3-methylpyrazol-5-ones from hydrazones

9 page(s

Is it true? (When) does it matter? The roles of likelihood and desirability in argument judgments and attitudes

Several theoretical perspectives either directly or indirectly specify roles for likelihood and desirability information in argument judgments and attitude formation. Some perspectives assume that argument judgments and attitudes are a function of the likelihood of the consequences or conclusions, others contend that the desirability of the consequences or conclusions underlie judgments and attitudes, and expectancy-value perspectives, (e.g., Fishbein, 1963) propose that judgments and attitudes should depend on the likelihood × desirability interaction. Construal level theory (CLT; Trope & Liberman, 2003) also suggests that both likelihood and desirability information impact argument judgments and attitudes, but the roles of each are moderated by when the outcomes are to occur. Three studies examined the sometimes-competing predictions regarding the roles of these variables by orthogonally manipulating levels of likelihood and desirability. Although likelihood and desirability both emerged as components of argument strength, and contributed to attitudes, all 3 studies showed that desirability information was more closely associated with argument strength and attitudes than was likelihood information. In Study 1a, argument strength was shown to mediate the desirability-attitude relation. The likelihood × desirability interaction did not predict attitudes in a manner consistent with expectancy-value predictions, though in some instances likelihood and desirability judgments interacted to predict attitudes and attitude change in the predicted expectancy-value pattern. Studies 1b and 2 showed that the desirability-attitude relation was best described as a cubic trend consistent with prospect theory. CLT predictions examined in Study 2 were largely unsupported. Theoretical and methodological implications are discussed.

Kinetics of chemokine-glycosaminoglycan interactions control neutrophil migration into the airspaces of the lungs

Chemokine–glycosaminoglycan (GAG) interactions are thought to result in the formation of tissue-bound chemokine gradients. We hypothesized that the binding of chemokines to GAGs would increase neutrophil migration toward CXC chemokines instilled into lungs of mice. To test this hypothesis we compared neutrophil migration toward recombinant human CXCL8 (rhCXCL8) and two mutant forms of CXCL8, which do not bind to heparin immobilized on a sensor chip. Unexpectedly, when instilled into the lungs of mice the CXCL8 mutants recruited more neutrophils than rhCXCL8. The CXCL8 mutants appeared in plasma at significantly higher concentrations and diffused more rapidly across an extracellular matrix in vitro. A comparison of the murine CXC chemokines, KC and MIP-2, revealed that KC was more effective in recruiting neutrophils into the lungs than MIP-2. KC appeared in plasma at significantly higher concentrations and diffused more rapidly across an extracellular matrix in vitro than MIP-2. In kinetic binding studies, KC, MIP-2, and rhCXCL8 bound heparin differently, with KC associating and dissociating more rapidly from immobilized heparin than the other chemokines. These data suggest that the kinetics of chemokine–GAG interactions contributes to chemokine function in tissues. In the lungs, it appears that chemokines, such as CXCL8 or MIP-2, which associate and disassociate slowly from GAGs, form gradients relatively slowly compared with chemokines that either bind GAGs poorly or interact with rapid kinetics. Thus, different types of chemokine gradients may form during an inflammatory response. This suggests a new model, whereby GAGs control the spatiotemporal formation of chemokine gradients and neutrophil migration in tissue

TEM imaging of subcellular localization following <i>in vitro</i> binding of IONP-Tfab to HER2+ breast cancer cells.

<p>(<b>A</b>) At 20,000X magnification in SKBR3 cells, 30 nm IONP-Tfab localize primary to intracellular vesicles with a smaller proportion remaining bound to the cell surface (arrows). (<b>B</b>) At 20,000X magnification in BT-474 cells, 30 nm IONP-Tfab exhibit similar localization. (<b>C</b>) At 10,000X magnification in SKBR3 cells, 100 nm IONP-Tfab are mainly found in intracellular vesicles (arrows). (<b>D</b>) At 20,000X magnification in BT-474 cells, 100 nm IONP-Tfab exhibit similar localization. Scale bars are 100 nm (A, B, D) and 500 nm (C).</p

<i>In vitro</i> binding affinity of Tfab and Tmab.

<p>*IC₅₀ values reflect concentration of Tfab required to compete 50% of saturating Tmab IgG.</p><p>Errors are standard deviations from technical triplicates.</p><p><i>In vitro</i> binding affinity of Tfab and Tmab.</p

<i>In vivo</i> biodistribution of IONP.

<p>Nanoparticles (80 μg/g body mass) were systemically administered by tail vein injection in NSG mice bearing BT-474 xenograft tumors. Iron content of various tissue compartments was quantified 24 hours post injection by ICP-MS. (<b>A</b>) Tumor, (<b>B</b>) Blood, (<b>C</b>) Heart, (<b>D</b>) Lung, (<b>E</b>) Liver, (<b>F</b>) Spleen, (<b>G</b>) Kidney. Statistical significance (P<0.05) was analyzed by one way ANOVA with a Tukey multiple comparison posttest. Solid brackets with asterisk indicate groups of mice that were not significantly different from each other but were significantly different from other groups outside the bracket. Significant differences between individual groups, including exceptions to the solid brackets, are indicated by solid arrows marked with an asterisk. For the heart, non-significance between individual groups (i.e. exceptions to the solid bracket) is indicated by hatched arrows marked with “ns”. For the heart, the 100 nm maleimide IONP group was not significantly different from any other group in the panel. N = 4 to 7 per group. Statistical analyses were completed using GraphPad Prism 5 (GraphPad Software, Inc., San Diego, CA).</p

<i>In vitro</i> binding studies of IONP.

<p>(<b>A</b>) Dose response rHER2 binding curves for 30 nm IONP-Tfab (closed circles) and 30 nm IONP-Mal (open squares). (<b>B</b>) Dose response rHER2 binding curves for 100 nm IONP-Tfab (closed circles) and 100 nm IONP-Mal (open squares). (<b>C</b>) Binding of HER2+ breast cancer cells for 30 nm IONP-Tfab and 30 nm IONP-Mal, both dosed at 100 μg/ml. (<b>D</b>) Binding of HER2+ breast cancer cells for 100 nm IONP-Tfab and 100 nm IONP-Mal, both dosed at70 μg/ml. Error bars represent standard deviation.</p