Duplex quantitative real-time PCR assay for the detection and discrimination of the eggs of Toxocara canis and Toxocara cati (Nematoda, Ascaridoidea) in soil and fecal samples.

BACKGROUND: Toxocarosis is a zoonotic disease caused by Toxocara canis (T. canis) and/or Toxocara cati (T. cati), two worldwide distributed roundworms which are parasites of canids and felids, respectively. Infections of humans occur through ingestion of embryonated eggs of T. canis or T. cati, when playing with soils contaminated with dogs or cats feces. Accordingly, the assessment of potential contamination of these areas with these roundworms eggs is paramount. METHODS: A duplex quantitative real-time PCR (2qPCR) targeting the ribosomal RNA gene internal transcribed spacer (ITS2) has been developed and used for rapid and specific identification of T. canis and T. cati eggs in fecal and soil samples. The assay was set up on DNA samples extracted from 53 adult worms including T. canis, T. cati, T. leonina, Ascaris suum (A. suum) and Parascaris equorum (P. equorum). The assay was used to assess the presence of T. cati eggs in several samples, including 12 clean soil samples spiked with eggs of either T. cati or A. suum, 10 actual soil samples randomly collected from playgrounds in Brussels, and fecal samples from cats, dogs, and other animals. 2qPCR results on dogs and cats fecal samples were compared with results from microscopic examination. RESULTS: 2qPCR assay allowed specific detection of T. canis and T. cati, whether adult worms, eggs spiked in soil or fecal samples. The 2qPCR limit of detection (LOD) in spiked soil samples was 2 eggs per g of soil for a turnaround time of 3 hours. A perfect concordance was observed between 2qPCR assay and microscopic examination on dogs and cats feces. CONCLUSION: The newly developed 2qPCR assay can be useful for high throughput prospective or retrospective detection of T.canis and/or T. cati eggs in fecal samples as well as in soil samples from playgrounds, parks and sandpits.

QSAR models for 2-amino-6-arylsulfonylbenzonitriles and congeners HIV-1 reverse transcriptase inhibitors based on linear and nonlinear regression methods.

A quantitative structure-activity relationship study of a series of HIV-1 reverse transcriptase inhibitors (2-amino-6-arylsulfonylbenzonitriles and their thio and sulfinyl congeners) was performed. Topological and geometrical, as well as quantum mechanical energy-related and charge distribution-related descriptors generated from CODESSA, were selected to describe the molecules. Principal component analysis (PCA) was used to select the training set. Six techniques: multiple linear regression (MLR), multivariate adaptive regression splines (MARS), radial basis function neural networks (RBFNN), general regression neural networks (GRNN), projection pursuit regression (PPR) and support vector machine (SVM) were used to establish QSAR models for two data sets: anti-HIV-1 activity and HIV-1 reverse transcriptase binding affinity. Results showed that PPR and SVM models provided powerful capacity of prediction.

MolDiA: a novel molecular diversity analysis tool. 1. Principles and architecture.

We introduce the principles and the architecture of a user-friendly software named MOLDIA (Molecular Diversity Analysis) which aims to the comparison of diverse molecular data sets through an XML structured database of predefined fragments. The MOLDIA descriptors are composed of complex fingerprint-like structures, which enclose not only structural information but also physicochemical property data. The system architecture includes the use of customizable weights on molecular descriptors and different choices of similarity/diversity measures to analyze the given data sets. Intermolecular comparisons using Ullmann's algorithm were optimized by the use of fuzzy logic, generic atoms, and a whole system of chemical graph analysis. We have found that customizing the similarity/diversity computation using structural and/or properties weights and choosing the level of fuzziness of the molecular comparison allow the user to adapt the tool to particular needs and increases the possibilities of MolDiA applications. The implementation of XML Web technologies has proven to improve and ease the extraction, processing, and analysis of chemical information.

Benchmarking of linear and nonlinear approaches for quantitative structure-property relationship studies of metal complexation with ionophores.

A benchmark of several popular methods, Associative Neural Networks (ANN), Support Vector Machines (SVM), k Nearest Neighbors (kNN), Maximal Margin Linear Programming (MMLP), Radial Basis Function Neural Network (RBFNN), and Multiple Linear Regression (MLR), is reported for quantitative-structure property relationships (QSPR) of stability constants logK1 for the 1:1 (M:L) and logbeta2 for 1:2 complexes of metal cations Ag+ and Eu3+ with diverse sets of organic molecules in water at 298 K and ionic strength 0.1 M. The methods were tested on three types of descriptors: molecular descriptors including E-state values, counts of atoms determined for E-state atom types, and substructural molecular fragments (SMF). Comparison of the models was performed using a 5-fold external cross-validation procedure. Robust statistical tests (bootstrap and Kolmogorov-Smirnov statistics) were employed to evaluate the significance of calculated models. The Wilcoxon signed-rank test was used to compare the performance of methods. Individual structure-complexation property models obtained with nonlinear methods demonstrated a significantly better performance than the models built using multilinear regression analysis (MLRA). However, the averaging of several MLRA models based on SMF descriptors provided as good of a prediction as the most efficient nonlinear techniques. Support Vector Machines and Associative Neural Networks contributed in the largest number of significant models. Models based on fragments (SMF descriptors and E-state counts) had higher prediction ability than those based on E-state indices. The use of SMF descriptors and E-state counts provided similar results, whereas E-state indices lead to less significant models. The current study illustrates the difficulties of quantitative comparison of different methods: conclusions based only on one data set without appropriate statistical tests could be wrong.

Differences in the expression of apoptotic proteins in Burkitt's lymphoma cell lines: potential models for screening apoptosis-inducing agents.

Mammalian cells undergo programmed cell death by orchestrated interactions involving multiple independent pathways. At least one of them, the p53-dependent pathway is commonly compromised in Burkitt's lymphoma (BL) cell lines. Differences in the integrity of this pathway in various BL cell lines have made them useful experimental models in understanding response to standard or novel antitumor drugs vis-a-vis the p53 pathway. Non-p53-dependent loss of apoptotic regulation also contributes to the genesis and/or progression of lymphomas and it is possible that BL cell lines also represent these models. We have characterized the expression of multiple apoptotic proteins in a panel of BL cell lines and describe cell lines with loss of cIAP1, cIAP2, Bax, Bak, Bcl-Xs and p38 MAP-kinase. This data should make this panel of cell lines a useful screening system for testing novel apoptotic inducers.

Spectral code index (SPECOIND): a general infrared spectral database search method.

A new spectral code that can be used by Relational Database Management Systems (RDBMS) as an index for infrared (IR) spectra searches in Relational Database (RDB) is presented and its suitability is evaluated. Spectral codes are constructed for all spectra in the database as the spectral indexes and three query strings are created with the same theory used for the creation of the index code for the query spectrum. Some effects of parameters used to create index strings and query strings are discussed. All spectral searches are accomplished in structured query language (SQL) approach and the utilization examples of SQL have been shown. The sequential application of this procedure can reduce the original library of about 18000 spectra to a few spectra that can be used as references for subsequent detailed comparison. The software developed for the proposed system is particularly suitable for spectral search and structure interpretation.

MASSIS: a mass spectrum simulation system. 2: Procedures and performance.

The use of the mass spectral simulation system, MASSIS, is reported and its performance has been evaluated. The search for substructures matching with fragments stored in four pivot databases was realised using the Ullmann algorithm. Special cleavage rules, such as the McLafferty rearrangement, the retro-Diels-Alder reaction, elimination of a neutral small molecule and oxygen migration, are processed through shortest path and depth-first search algorithms. For a search in the database of small fragments, the key step is to determine the tautomeric fragments; then a match can be obtained using a subgraph isomorphism algorithm. A string match is used to determine peak intensity. If the limited environment of an atom is the same as that found in the database of relationships between fragment and intensity, this intensity value is assigned to the query atom. Performance in a set of tests is very important in evaluating the system performance. A comparison of peaks with an intensity greater than 5% (relative) shows that our system has a very high performance figure (> 90% ) for routine organic compounds.

MASSIS: a mass spectrum simulation system 1. Principle and method.

A mass spectrum simulation system was developed. The simulated spectrum for a given target structure is computed based on the cleavage knowledge and statistical rules established and stocked in pivot databases: cleavage rule knowledge, function groups, small fragments and fragment-intensity relationships. These databases were constructed from correlation charts and statistical analysis of large population of organic mass spectra using data mining techniques. Since 1980, several systems were proposed for mass spectrum simulation, but in present there is no any commercial software available. This shows the complexity and difficulties in the development of a such system. The reported mass spectral simulation system in this paper could be the first general software for organic chemistry use

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and Fas apoptosis in Burkitt's lymphomas with loss of multiple pro-apoptotic proteins.

BACKGROUND AND OBJECTIVES: Normal B-cells in the germinal center (GC) may be exposed to both tumor necrosis factor-related apoptosis inducing ligand (TRAIL) and Fas-L. Whether abrogation of TRAIL apoptosis is a feature in the genesis of B cell lymphomas of GC-phenotype is not known. We assessed the integrity of the TRAIL pathway in Fas-resistant and Fas-sensitive Burkitt s lymphomas (BLs). DESIGN AND METHODS: Expression of TRAIL receptors was determined by flow cytometry and Western blots. The extent of apoptosis following exposure to TRAIL was measured by annexin-V/propidium iodide dual staining. The integrity of the Fas and TRAIL apoptotic pathways was determined by Western blotting to assess cleavage of downstream caspases. Western blot analyses were used to determine the expression of pro- and anti-apoptotic proteins and the profile of expression was correlated with response to TRAIL and CH11. RESULTS: Our results demonstrate that BL expresses both functional and decoy TRAIL receptors. BLs with a functional Fas pathway retained sensitivity to TRAIL: Frequent and compound loss of expression of pro-apoptotic proteins can be identified in BLs resistant to Fas. However, loss of Bax, Bak and Bcl-Xs did not compromise sensitivity to TRAIL: INTERPRETATION AND CONCLUSIONS: Our results indicate that BLs frequently retain sensitivity to the TRAIL pathway. These results underscore the utility of TRAIL-based therapeutic strategies in the treatment of those B-cell lymphomas that may have compromised expression of several pro-apoptotic proteins.

SIRS-SS: a system for simulating IR/Raman spectra. 2. Procedures and performance.

This paper is devoted to the description of procedures used in our IR/RAMAN spectrum simulation system, based on substructure/subspectrum correlations established between linked databases. The search is performed in the following order: small molecules/specific fragments/atom centered FRELs (FREL: FRagment centered on an Environment which is Limited)/bond focused FRELs. Comparative study with several reported methods has been carried out to show good performance of this software both for IR and RAMAN spectrum simulation.