Thioglycosides Are efficient metabolic decoys of glycosylation that reduce selectin dependent leukocyte adhesion

Metabolic decoys are synthetic analogs of naturally occurring biosynthetic acceptors. These compounds divert cellular biosynthetic pathways by acting as artificial substrates that usurp the activity of natural enzymes. While O-linked glycosides are common, they are only partially effective even at millimolar concentrations. In contrast, we report that N-acetylglucosamine (GlcNAc) incorporated into various thioglycosides robustly truncate cell surface N- and O-linked glycan biosynthesis at 10-100 μM concentrations. The >10-fold greater inhibition is in part due to the resistance of thioglycosides to hydrolysis by intracellular hexosaminidases. The thioglycosides reduce β-galactose incorporation into lactosamine chains, cell surface sialyl Lewis-X expression, and leukocyte rolling on selectin substrates including inflamed endothelial cells under fluid shear. Treatment of granulocytes with thioglycosides prior to infusion into mouse inhibited neutrophil homing to sites of acute inflammation and bone marrow by ∼80%-90%. Overall, thioglycosides represent an easy to synthesize class of efficient metabolic inhibitors or decoys. They reduce N-/O-linked glycan biosynthesis and inflammatory leukocyte accumulation

Structural Basis and Kinetics of Force-Induced Conformational Changes of an αA Domain-Containing Integrin

Integrin α(L)β₂ (lymphocyte function-associated antigen, LFA-1) bears force upon binding to its ligand intercellular adhesion molecule 1 (ICAM-1) when a leukocyte adheres to vascular endothelium or an antigen presenting cell (APC) during immune responses. The ligand binding propensity of LFA-1 is related to its conformations, which can be regulated by force. Three conformations of the LFA-1 αA domain, determined by the position of its α₇-helix, have been suggested to correspond to three different affinity states for ligand binding.The kinetics of the force-driven transitions between these conformations has not been defined and dynamically coupled to the force-dependent dissociation from ligand. Here we show, by steered molecular dynamics (SMD) simulations, that the αA domain was successively transitioned through three distinct conformations upon pulling the C-terminus of its α₇-helix. Based on these sequential transitions, we have constructed a mathematical model to describe the coupling between the αA domain conformational changes of LFA-1 and its dissociation from ICAM-1 under force. Using this model to analyze the published data on the force-induced dissociation of single LFA-1/ICAM-1 bonds, we estimated the force-dependent kinetic rates of interstate transition from the short-lived to intermediate-lived and from intermediate-lived to long-lived states. Interestingly, force increased these transition rates; hence activation of LFA-1 was accelerated by pulling it via an engaged ICAM-1.Our study defines the structural basis for mechanical regulation of the kinetics of LFA-1 αA domain conformational changes and relates these simulation results to experimental data of force-induced dissociation of single LFA-1/ICAM-1 bonds by a new mathematical model, thus provided detailed structural and kinetic characterizations for force-stabilization of LFA-1/ICAM-1 interaction

Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved 'high-coverage' and 'high-accuracy' glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics

The impact of diabetes on the pathogenesis of sepsis

Diabetes is associated with an increased susceptibility to infection and sepsis. Conflicting data exist on whether the mortality of patients with sepsis is influenced by the presence of diabetes, fuelling the ongoing debate on the benefit of tight glucose regulation in patients with sepsis. The main reason for which diabetes predisposes to infection appears to be abnormalities of the host response, particularly in neutrophil chemotaxis, adhesion and intracellular killing, defects that have been attributed to the effect of hyperglycaemia. There is also evidence for defects in humoral immunity, and this may play a larger role than previously recognised. We review the literature on the immune response in diabetes and its potential contribution to the pathogenesis of sepsis. In addition, the effect of diabetes treatment on the immune response is discussed, with specific reference to insulin, metformin, sulphonylureas and thiazolidinediones

A model for the kinetics of homotypic cellular aggregation under static conditions.

We present the formulation and testing of a mathematical model for the kinetics of homotypic cellular aggregation. The model considers cellular aggregation under no-flow conditions as a two-step process. Individual cells and cell aggregates 1) move on the tissue culture surface and 2) collide with other cells (or aggregates). These collisions lead to the formation of intercellular bonds. The aggregation kinetics are described by a system of coupled, nonlinear ordinary differential equations, and the collision frequency kernel is derived by extending Smoluchowski's colloidal flocculation theory to cell migration and aggregation on a two-dimensional surface. Our results indicate that aggregation rates strongly depend upon the motility of cells and cell aggregates, the frequency of cell-cell collisions, and the strength of intercellular bonds. Model predictions agree well with data from homotypic lymphocyte aggregation experiments using Jurkat cells activated by 33B6, an antibody to the beta 1 integrin. Since cell migration speeds and all the other model parameters can be independently measured, the aggregation model provides a quantitative methodology by which we can accurately evaluate the adhesivity and aggregation behavior of cells

Effects of Brand Preference, Product Attributes, and Marketing Mix Variables in Technology Product Markets

We develop a demand model for technology products that captures the effect of changes in the portfolio of models offered by a brand as well as the influence of the dynamics in its intrinsic preference on that brand's performance. To account for the potential correlation in the preferences of models offered by a particular brand, we use a nested logit model with the brand (e.g., Sony) at the upper level and its various models (e.g., Mavica, FD, DSC, etc.) at the lower level of the nest. Relative model preferences are captured via their attributes and prices. We allow for heterogeneity across consumers in their preferences for these attributes and in their price sensitivities in addition to heterogeneity in consumers' intrinsic brand preferences. Together with the nested logit assumption, this allows for a flexible substitution pattern across models at the aggregate level. The attractiveness of a brand's product line changes over time with entry and exit of new models and with changes in attribute and price levels. To allow for time-varying intrinsic brand preferences, we use a state-space model based on the Kalman filter, which captures the influence of marketing actions such as brand-level advertising on the dynamics of intrinsic brand preferences. Hence, the proposed model accounts for the effects of brand preferences, model attributes and marketing mix variables on consumer choice. First, we carry out a simulation study to ensure that our estimation procedure is able to recover the true parameters generating the data. Then, we estimate our model parameters on data for the U.S. digital camera market. Overall, we find that the effect of dynamics in the intrinsic brand preference is greater than the corresponding effect of the dynamics in the brand's product line attractiveness. Assuming plausible profit margins, we evaluate the effect of increasing the advertising expenditures for the largest and the smallest brands in this category and find that these brands can increase their profitability by increasing their advertising expenditures. We also analyze the impact of modifying a camera model's attributes on its profits. Such an analysis could potentially be used to evaluate if product development efforts would be profitable.econometric models, hi-tech marketing, advertising, product line attractiveness, product development, nested logit models, Kalman filter