Air entrapment in sheet molding compounds (SMC)

Entrapped air can commonly lead to large delaminations in thick walled sheet molding compound (SMC) products. In this work different sources of air entrapment in SMC are investigated. The critical process is shown to be the impregnation of the fibers. If no surface active additives are used, large volumes of air may be entrapped in this process, unless the viscosity of the compound is very low. In this situation of poor wetting, the viscosity of the compound during fiber impregnation will critically determine the interlaminar, tensile strength of the product. However, if surface active additives are used, the air escapes entrapment even at relatively high viscosities. The lowering of the viscosity, which is a side effect of the additives, has practically no importance under these conditions of good wetting. Large numbers of small air bubbles are also entrapped during the mixing of the components, but it is shown that these bubbles have very little effect on the mechanical properties of the finished part.     

In situ studies of the decomposition of ammonium uranyl carbonate in an electron microscope

An electron microscope has been used to study the reduction of ammonium uranyl carbonate (AUC) to UO₂. The reactions could be followed both in the diffraction and the lattice image mode. The first intermediate obtained was amorphous UO₃. Depending on the experimental conditions, either crystalline UO₂ was formed directly from this phase, or several other intermediates were indicated.Properties like crystallinity and crystallite size of final UO₂ were found to be a function of experimental conditions. Comparisons with properties of UO₂ from the industrial process have been made.     

Catalytic Encounters at the Molecular Level: Gabor A. Somorjai Award Symposium for Creative Research in Catalysis in Honor of Professor Manos Mavrikakis

Topics in Catalysis -     

Classification of Amyloidosis by Model-Assisted Mass Spectrometry-Based Proteomics

Amyloidosis is a rare disease caused by the misfolding and extracellular aggregation of proteins as insoluble fibrillary deposits localized either in specific organs or systemically throughout the body. The organ targeted and the disease progression and outcome is highly dependent on the specific fibril-forming protein, and its accurate identification is essential to the choice of treatment. Mass spectrometry-based proteomics has become the method of choice for the identification of the amyloidogenic protein. Regrettably, this identification relies on manual and subjective interpretation of mass spectrometry data by an expert, which is undesirable and may bias diagnosis. To circumvent this, we developed a statistical model-assisted method for the unbiased identification of amyloid-containing biopsies and amyloidosis subtyping. Based on data from mass spectrometric analysis of amyloid-containing biopsies and corresponding controls. A Boruta method applied on a random forest classifier was applied to proteomics data obtained from the mass spectrometric analysis of 75 laser dissected Congo Red positive amyloid-containing biopsies and 78 Congo Red negative biopsies to identify novel “amyloid signature” proteins that included clusterin, fibulin-1, vitronectin complement component C9 and also three collagen proteins, as well as the well-known amyloid signature proteins apolipoprotein E, apolipoprotein A4, and serum amyloid P. A SVM learning algorithm were trained on the mass spectrometry data from the analysis of the 75 amyloid-containing biopsies and 78 amyloid-negative control biopsies. The trained algorithm performed superior in the discrimination of amyloid-containing biopsies from controls, with an accuracy of 1.0 when applied to a blinded mass spectrometry validation data set of 103 prospectively collected amyloid-containing biopsies. Moreover, our method successfully classified amyloidosis patients according to the subtype in 102 out of 103 blinded cases. Collectively, our model-assisted approach identified novel amyloid-associated proteins and demonstrated the use of mass spectrometry-based data in clinical diagnostics of disease by the unbiased and reliable model-assisted classification of amyloid deposits and of the specific amyloid subtype.     

Interactions between immunoglobulin-like and catalytic modules in Clostridium thermocellum cellulosomal cellobiohydrolase CbhA

Cellobiohydrolase CbhA from Clostridium thermocellum cellulosome is a multi-modular protein composed starting from the N-terminus of a carbohydrate-binding module (CBM) of family 4, an immunoglobulin(Ig)-like module, a catalytic module of family 9 glycoside hydrolases (GH9), X1(1) and X1(2) modules, a CBM of family 3 and a dockerin module. Deletion of the Ig-like module from the Ig-GH9 construct results in complete inactivation of the GH9 module. The crystal structure of the Ig-GH9 module pair reveals the existence of an extensive module interface composed of over 40 amino acid residues of both modules and maintained through a large number of hydrophilic and hydrophobic interactions. To investigate the importance of these interactions between the two modules, we compared the secondary and tertiary structures and thermostabilities of the individual Ig-like and GH9 modules and the Ig-GH9 module pair using both circular dichroism (CD) spectroscopy and differential scanning calorimetry (DSC). Thr230, Asp262 and Asp264 of the Ig-like module are located in the module interface of the Ig-GH9 module pair and are suggested to be important in 'communication' between the modules. These residues were mutated to alanyl residues. The structure, stability and catalytic properties of the native Ig-GH9 and its D264A and T230A/D262A mutants were compared. The results indicate that despite being able to fold relatively independently, the Ig-like and GH9 modules interact and these interactions affect the final fold and stability of each module. Mutations of one or two amino acid residues lead to destabilization and change of the mechanism of thermal unfolding of the polypeptides. The enzymatic properties of native Ig-GH9, D264A and T230A/D262A mutants are similar. The results indicate that inactivation of the GH9 module occurs as a result of multiple structural disturbances finally affecting the topology of the catalytic center.     

Bacterial Dehydrogenases Facilitate Oxidative Inactivation and Bioremediation of Chloramphenicol

Antimicrobial resistance represents a major threat to human health and knowledge of the underlying mechanisms is therefore vital. Here, we report the discovery and characterization of oxidoreductases that inactivate the broad-spectrum antibiotic chloramphenicol via dual oxidation of the C3-hydroxyl group. Accordingly, chloramphenicol oxidation either depends on standalone glucose-methanol-choline (GMC)-type flavoenzymes, or on additional aldehyde dehydrogenases that boost overall turnover. These enzymes also enable the inactivation of the chloramphenicol analogues thiamphenicol and azidamfenicol, but not of the C3-fluorinated florfenicol. Notably, distinct isofunctional enzymes can be found in Gram-positive (e. g., Streptomyces sp.) and Gram-negative (e. g., Sphingobium sp.) bacteria, which presumably evolved their selectivity for chloramphenicol independently based on phylogenetic analyses. Mechanistic and structural studies provide further insights into the catalytic mechanisms of these biotechnologically interesting enzymes, which, in sum, are both a curse and a blessing by contributing to the spread of antibiotic resistance as well as to the bioremediation of chloramphenicol.