Stimulation of cholesteryl ester synthesis in human monocyte-derived macrophages by low-density lipoproteins from type 1 (insulin-dependent) diabetic patients:the influence of non-enzymatic glycosylation of low-density lipoproteins

Diabetes mellitus is an independent risk factor in the development of atherosclerosis. In this study we aimed to demonstrate whether there is an abnormal interaction between low-density lipoproteins from diabetic patients and human macrophages. We measured cholesteryl ester synthesis and cholesteryl ester accumulation in human monocyte-derived macrophages (obtained from non-diabetic donors) incubated with low density lipoproteins from Type 1 (insulin-dependent) diabetic patients in good or fair glycaemic control. Low density lipoproteins from the diabetic patients stimulated more cholesteryl ester synthesis than low density lipoproteins from non-diabetic control subjects (7.19 +/- 1.19 vs 6.11 +/- 0.94 nmol/mg cell protein/20 h, mean +/- SEM, p less than 0.05). The stimulation of cholesteryl ester synthesis by low density lipoproteins isolated from diabetic patients was paralleled by a significant increase in intracellular cholesteryl ester accumulation (p less than 0.02). There were no significant differences in the lipid composition of low density lipoproteins between the diabetic and control groups. Non-enzymatic glycosylation of low density lipoproteins was higher in the diabetic group (p less than 0.01) and correlated significantly with cholesteryl ester synthesis (r = 0.58). Similarly, low-density lipoproteins obtained from non-diabetic subjects and glycosylated in vitro stimulated more cholesteryl ester synthesis in macrophages than control low density lipoproteins. The increase in cholesteryl ester synthesis and accumulation by cells exposed to low density lipoproteins from diabetic patients seems to be mediated by an increased uptake of these lipoproteins by macrophages.(ABSTRACT TRUNCATED AT 250 WORDS)

Effect of in vitro non-enzymatic glycosylation of human skin collagen on susceptibility to collagenase digestion

The effect of glycosylation on susceptibility of skin collagen to collagenase digestion was studied in a skin sample obtained at autopsy from the interscapular region of a 24 year old white male who had died of an acute illness and who had no history of diabetes. Homogeneous suspensions of insoluble collagen were prepared, and were incubated in 50 mmol l-1 dextrose at pH 7.35 and 37 degrees C for 7 days. Non-enzymatic glycosylation measured by the weak acid hydrolysis/thiobarbituric acid method increased from 13.1 +/- 1.0 (n = 5) to 45.2 +/- 5.5 (n = 8) nmol fructose per 10 mg collagen (P less than 0.001). Digestion of collagen using clostridial collagenase was monitored by measuring (a) hydroxyproline content and (b) absorption at 206 nm of the supernatant after centrifugation to remove substrate. The rate of digestion was similar in glycosylated and control collagen. We conclude that the ketoamine link formed in non-enzymatic glycosylation does not increase the resistance of collagen to enzymatic digestion. The possibility remains that subsequent rearrangement of this link could be important in this respect.

Non-enzymatic glycosylation of skin collagen in patients with type 1 (insulin-dependent) diabetes mellitus and limited joint mobility

Forearm skin biopsies were obtained from diabetic subjects with and without limited joint mobility, and from non-diabetic control subjects. Collagen purified from these samples was assayed for non-enzymatic glycosylation. The level in all diabetic patients was significantly greater than that in control subjects (p less than 0.001), but those diabetic patients with limited joint mobility had a level of collagen glycosylation similar to that in those with normal joints (15.3 +/- 1.3 and 16.5 +/- 1.3 nmol fructose/10 mg protein, respectively; mean +/- SEM). Glycosylation of collagen in the diabetic patients correlated with glycosylated haemoglobin measured at the time of skin biopsy (r = 0.60). These results do not support the hypothesis that non-enzymatic glycosylation of collagen, as reflected by the ketoamine link, plays an important role in the development of limited joint mobility in diabetes.

Detection of Protein-Protein Interactions Using Protein-Fragment Complementation Assays (PCA)

Protein-protein interactions play a central role in many cellular processes. Their characterisation is necessary in order to analyse these processes and for the functional identification of unknown proteins. Existing detection methods such as the yeast two-hybrid (Y2H) and tandem affinity purification (TAP) method provide a means to answer rapidly questions regarding protein-protein interactions, but have limitations which restrict their use to certain interaction networks; furthermore they provide little information regarding interaction localisation at the subcellular level. The development of protein-fragment complementation assays (PCA) employing a fluorescent reporter such as a member of the green fluorescent protein (GFP) family has led to a new method of interaction detection termed Bimolecular Fluorescent Complementation (BiFC). These assays have become important tools for understanding protein interactions and the development of whole genome interaction maps. BiFC assays have the advantages of very low background signal coupled with rapid detection of protein-protein interactions in vivo while also providing information regarding interaction compartmentalisation. Modified forms of the assay such as the use of combinations of spectral variants of GFP have allowed simultaneous visualisation of multiple competing interactions in vivo. Advantages and disadvantages of the method are discussed in the context of other fluorescence-based interaction monitoring techniques.

Establishing optimal quantitative-polymerase chain reaction assays for routine diagnosis and tracking of minimal residual disease in JAK2-V617F-associated myeloproliferative neoplasms:a joint European LeukemiaNet/MPN&MPNr-EuroNet (COST action BM0902) study

Reliable detection of JAK2-V617F is critical for accurate diagnosis of myeloproliferative neoplasms (MPNs); in addition, sensitive mutation-specific assays can be applied to monitor disease response. However, there has been no consistent approach to JAK2-V617F detection, with assays varying markedly in performance, affecting clinical utility. Therefore, we established a network of 12 laboratories from seven countries to systematically evaluate nine different DNA-based quantitative PCR (qPCR) assays, including those in widespread clinical use. Seven quality control rounds involving over 21,500 qPCR reactions were undertaken using centrally distributed cell line dilutions and plasmid controls. The two best-performing assays were tested on normal blood samples (n=100) to evaluate assay specificity, followed by analysis of serial samples from 28 patients transplanted for JAK2-V617F-positive disease. The most sensitive assay, which performed consistently across a range of qPCR platforms, predicted outcome following transplant, with the mutant allele detected a median of 22 weeks (range 6-85 weeks) before relapse. Four of seven patients achieved molecular remission following donor lymphocyte infusion, indicative of a graft vs MPN effect. This study has established a robust, reliable assay for sensitive JAK2-V617F detection, suitable for assessing response in clinical trials, predicting outcome and guiding management of patients undergoing allogeneic transplant.

Comparative evaluation of 2,3-bis [2-methyloxy-4-nitro-5-sulfophenyl]-2H-tetrazolium-5-carboxanilide (XTT) and 2-(2-methoxy-4-nitrophenyl)-3-(4-nitrophenyl)-5-(2, 4-disulfophenyl)-2H-tetrazolium, monosodium salt (WST-8) rapid colorimetric assays for antimicrobial susceptibility testing of staphylococci and ESBL-producing clinical isolates

A new generation of water soluble tetrazolium salts have recently become available and in this study we compared a colorimetric assay developed using one of these salts, 2-(2-methoxy-4-nitrophenyl)-3-(4-nitrophenyl)-5-(2, 4-disulfophenyl)-2H-tetrazolium, monosodium salt (WST-8), with a previously developed 2,3-bis [2-methyloxy-4-nitro-5-sulfophenyl]-2H-tetrazolium-5-carboxanilide (XTT) colorimetric assay to determine which agent is most suitable for use as a colorimetric indicator in susceptibility testing. The MICs of 6 antibiotics were determined for 33 staphylococci using both colorimetric assays and compared with those obtained using the British Society for Antimicrobial Chemotherapy reference broth microdilution method. Absolute categorical agreement between the reference and test methods ranged from 79% (cefuroxime) to 100% (vancomycin) for both assays. No minor or major errors occurred using either assay with very major errors ranging from zero (vancomycin) to seven (cefuroxime). Analysis of the distribution of differences in the log2 dilution MIC results revealed overall agreement, within the accuracy limits of the standard test (± 1 log2 dilution), using the XTT and WST-8 assays of 98% and 88%, respectively. Further studies on 31 ESBL-producing isolates were performed using the XTT method with absolute categorical agreement ranging from 87% (nitrofurantoin) to 100% (ofloxacin and meropenem). No errors were noted for either ofloxacin or meropenem with overall agreement of 91%. The data suggests that XTT is more reliable and accurate than WST-8 for use in a rapid antimicrobial susceptibility test.

Novel comparison of kinetic models for the adsorption-coupled reduction of Cr(VI) using untreated date pit biomaterial

Biosorption of Cr(VI) onto date pit biomass has been investigated via kinetic studies as functions of initial Cr(VI) concentration, solution temperature and date pit particle size. Kinetic experiments indicated that chromate ions accumulate onto the date pits and then reduce to less toxic Cr(III) compounds. The López-García, Escudero and Park Cr(VI) biosorption kinetic models, which take into consideration the direct reduction, the passivation process and the follow-on decrease of the active surface area of reaction, were applied to the kinetic data. The models represented the experimental data accurately at low Cr(VI) concentration (0.480 mM) and small particle size (0.11–0.22 mm) at which the Cr(VI) was completely removed from the aqueous solution and completely reduced to Cr(III) after 420 min. Date pit biomass thus offers a green chemical process for the remediation of chromium from wastewater. This investigation will help researchers employ the adsorption-coupled reduction of Cr(VI) models and simplify their application to kinetic experimental data.

Integrating intrinsic and global kinetics as a dual kinetic model for automotive catalysis

The majority of the kinetic models employed in catalytic after-treatment of exhaust emissions use a global kinetic approach owing to the simplicity because one expression can account for all the steps in a reaction. The major drawback of this approach is the limited predictive capabilities of the models. The intrinsic kinetic approach offers much more information about the processes occurring within the catalytic converter; however, it is significantly more complex and time consuming to develop. In the present work, a methodology which allows accessing a model that combines the simplicity of the global kinetic approach and the accuracy of the intrinsic kinetic approach is reported. To assess the performance of this new approach, the oxidation of carbon monoxide in the presence of nitric oxide as well as a driving cycle was investigated. The modelling of carbon monoxide oxidation with oxygen which utilised the intrinsic kinetic approach with the global kinetic approach was used for the carbon monoxide + nitric oxide reaction (and all remaining reactions for the driving cycle). The comparison of the model results for the dual intrinsic + global kinetic approach with the experimental data obtained for both the reactor and the driving cycle indicate that the dual approach is promising with results significantly better than those obtained with only the global kinetics approach.

Optimisation of Kinetic Parameters for an After-treatment Catalyst

Mathematical modelling has become an essential tool in the design of modern catalytic systems. Emissions legislation is becoming increasingly stringent, and so mathematical models of aftertreatment systems must become more accurate in order to provide confidence that a catalyst will convert pollutants over the required range of conditions. 
Automotive catalytic converter models contain several sub-models that represent processes such as mass and heat transfer, and the rates at which the reactions proceed on the surface of the precious metal. Of these sub-models, the prediction of the surface reaction rates is by far the most challenging due to the complexity of the reaction system and the large number of gas species involved. The reaction rate sub-model uses global reaction kinetics to describe the surface reaction rate of the gas species and is based on the Langmuir Hinshelwood equation further developed by Voltz et al. [1] The reactions can be modelled using the pre-exponential and activation energies of the Arrhenius equations and the inhibition terms. 
The reaction kinetic parameters of aftertreatment models are found from experimental data, where a measured light-off curve is compared against a predicted curve produced by a mathematical model. The kinetic parameters are usually manually tuned to minimize the error between the measured and predicted data. This process is most commonly long, laborious and prone to misinterpretation due to the large number of parameters and the risk of multiple sets of parameters giving acceptable fits. Moreover, the number of coefficients increases greatly with the number of reactions. Therefore, with the growing number of reactions, the task of manually tuning the coefficients is becoming increasingly challenging. 
In the presented work, the authors have developed and implemented a multi-objective genetic algorithm to automatically optimize reaction parameters in AxiSuite®, [2] a commercial aftertreatment model. The genetic algorithm was developed and expanded from the code presented by Michalewicz et al. [3] and was linked to AxiSuite using the Simulink add-on for Matlab. 
The default kinetic values stored within the AxiSuite model were used to generate a series of light-off curves under rich conditions for a number of gas species, including CO, NO, C_{3H8 and C3H6. These light-off curves were used to generate an objective function.} 
This objective function was used to generate a measure of fit for the kinetic parameters. The multi-objective genetic algorithm was subsequently used to search between specified limits to attempt to match the objective function. In total the pre-exponential factors and activation energies of ten reactions were simultaneously optimized. 
The results reported here demonstrate that, given accurate experimental data, the optimization algorithm is successful and robust in defining the correct kinetic parameters of a global kinetic model describing aftertreatment processes.

Evaluation of an in situ spatial resolution instrument for fixed beds through the assessment of the invasiveness of probes and a comparison with a micro-kinetic model

This paper reports the detailed description and validation of a fully automated, computer controlled analytical method to spatially probe the gas composition and thermal characteristics in packed bed systems. This method has been designed to limit the invasiveness of the probe, a characteristic assessed using CFD. The thermocouple is aligned with the sampling holes to enable simultaneous recording of the gas composition and temperature profiles. This analysis technique has been validated by studying CO oxidation over a 1% Pt/Al2O3 catalyst. The resultant profiles have been compared with a micro-kinetic model, to further assess the strength of the technique. 

Chemistry and Mechanism of Alizarin Red S and Methylene Blue Biosorption onto Olive Stone: Equilibrium and Kinetic

The biosorption process of anionic dye Alizarin Red S (ARS) and cationic dye methylene blue (MB) as a function of solution pH, initial concentration and contact time onto olive stone (OS) biomass has been investigated. The main objectives of the current study are to: (i) study the chemistry and the mechanism of ARS and MB biosorption onto olive stone and the type of OS–ARS, MB interactions occurring, (ii) study the biosorption equilibrium and kinetic experimental data required for the design and operation of column reactors. Equilibrium biosorption isotherms and kinetics were also examined. Experimental equilibrium data were fitted to four different isotherms by non-linear regression method, however, the biosorption experimental data for ARS and MB dyes were well interpreted by the Temkin and Langmuir isotherms, respectively. The maximum monolayer adsorption capacity for ARS and MB dyes were 109.0 and 102.6 mg/g, respectively. The kinetic data of the two dyes could be better described by the pseudo second-order model. The data showed that olive stone can be effectively used for removing dyes from wastewater.