Software tools for micro-analysis of programs

The paper proposes and describes several tools enabling their user to estimate the efficiency of Pascal or C-like programs. The approach consists of generating symbolic formulas expressing the efficiency of the programs being analyzed. The formulas are applicable to a variety of compiler-machine configurations. The actual numeric values of the variables in the symbolic formula are determined using linear programming techniques. The proposed approach reduces considerably the amount of benchmarking needed to analyze programs. Several examples are presented showing the applicability of the tools. The effort necessary to implement them is considerably reduced by the combined usage of Prolog and a symbolic formula manipulation package (Maple).     

Interaction of H2,n-butane and cis-2-butene with Pt and Pt In in NaY: a microcalorimetric study

Pt NaY and Pt In NaY adsorption properties have been compared by using probes like H₂, C₄H₁₀, 2-C₄H₈ and microcalorimetry. It appears that the addition of In to Pt does not change the initial heat of H₂ chemisorption but decreases the initial heat of butane and butene chemisorption.     

Engineering of protein epitopes: a single deletion in a snake toxin generates full binding capacity to a previously unrecognized antibody

Structural features associated with the ability of a monoclonalantibody (mAb) to discriminate between protein variants areidentified and engineered. The variants are the curaremimetictoxin from Naja nigricollis and erabutoxin a or b from Laticaudasemifasciata which differ from each other by 16 substitutionsand one insertion. The neutralizing mAb M1 recognizes with highaffinity a topographical epitope on the surface of toxin , butfails to recognize the erabutoxins although they possess mostof the residues forming the presumed epitope. Examinations ofthe toxin and erabutoxin 3-D structures and molecular dynamicssimulations reveal several differences between the variants.In particular, the region involving the ß-turn 17–24is organized differently. Analysis of the differences foundin this region suggests that the insertion (or deletion) atposition 18 of the variant amino add sequences is particularlyimportant in determining the differential cross-reactivity.To test this proposal, residue 18 was deleted in one erabutoxinusing sitedirected mutagenesis, and the biological propertiesof the resulting mutant were examined. We found that full antigenicitywas restored in the previously unrecognized variant. The implicationsof this finding are discussed.     

Optimal parameters identification and sensitivity study for abrasive waterjet milling model

In this paper we present the work related to the parameters identification for abrasive waterjet milling (AWJM) model that appears as an ill-posed inverse problem. The necessity of studying this problem comes from the industrial milling applications where the possibility to predict and model the final surface with high accuracy is one of the primary tasks in the absence of any knowledge of the model parameters that should be used. The adjoint approach based on corresponding Lagrangian gives the opportunity to find out the unknowns of the AWJM model and their optimal values that could be used to reproduce the required trench profile. Due to the complexity of the nonlinear problem and the large number of the model parameters, we use an automatic differentiation software tool. This approach also gives us the ability to distribute the research on more complex cases and consider different types of model errors and 3D time dependent model with variations of the jet feed speed. This approach gives us a good opportunity to identify the optimal model parameters and predict the surface profile both with self-generated data and measurements obtained from the real production. Considering different types of model errors allows us to receive the results acceptable in manufacturing and to expect the proper identification of unknowns.     

Differential Plasma Metabolites between High- and Low-Grade Meningioma Cases

Meningiomas (MGMs) are currently classified into grades I, II, and III. High-grade tumors are correlated with decreased survival rates and increased recurrence rates. The current grading classification is based on histological criteria and determined only after surgical tumor sampling. This study aimed to identify plasma metabolic alterations in meningiomas of different grades, which would aid surgeons in predefining the ideal surgical strategy. Plasma samples were collected from 51 patients with meningioma and classified into low-grade (LG) (grade I; n = 43), and high-grade (HG) samples (grade II, n = 5; grade III, n = 3). An untargeted metabolomic approach was used to analyze plasma metabolites. Statistical analyses were performed to select differential biomarkers among HG and LG groups. Metabolites were identified using tandem mass spectrometry along with database verification. Five and four differential biomarkers were identified for HG and LG meningiomas, respectively. To evaluate the potential of HG MGM metabolites to differentiate between HG and LG tumors, a receiving operating characteristic curve was constructed, which revealed an area under the curve of 95.7%. This indicates that the five HG MGM metabolites represent metabolic alterations that can differentiate between LG and HG meningiomas. These metabolites may indicate tumor grade even before the appearance of histological features.     

Optimization of the Alizarin Red S Assay by Enhancing Mineralization of Osteoblasts

The alizarin red S assay is considered the gold standard for quantification of osteoblast mineralization and is thus widely used among scientists. However, there are several restrictions to this method, e.g., moderate sensitivity makes it difficult to uncover slight but significant effects of potentially clinically relevant substances. Therefore, an adaptation of the staining method is appropriate and might be obtained by increasing the mineralization ability of osteoblasts. In this study, cell culture experiments with human (SaOs-2) and murine (MC3T3-E1) osteoblasts were performed under the addition of increasing concentrations of calcium chloride (1, 2.5, 5, and 10 mM) or calcitonin (1, 2.5, 5, and 10 nM). After three or four weeks, the mineralization matrix was stained with alizarin red S and the concentration was quantified photometrically. Only calcium chloride was able to significantly increase mineralization, and therefore enhanced the sensitivity of the alizarin red S staining in a dose-dependent manner in both osteoblastic cell lines as well as independent of the cell culture well surface area. This cost- and time-efficient optimization enables a more sensitive analysis of potentially clinically relevant substances in future bone research.