Measles virus and classical Hodgkin lymphoma: no evidence for a direct association.

A proportion of Hodgkin lymphoma (HL) cases are causally associated with the Epstein-Barr virus (EBV) but the aetiology of the remaining cases remains obscure. Over the last 3 decades several studies have found an association between HL and measles virus (MV) including a recent cohort study describing the detection of MV antigens in Hodgkin and Reed-Sternberg cells, the tumour cells in HL. In the present study we looked at the relationship between history of MV infection and risk of developing HL in a population-based, case/control study of HL. In addition we used immunohistochemistry and RT-PCR to look for direct evidence of MV in HL biopsies. There was no significant difference in the proportion of cases reporting previous measles compared to controls in the entire data set or when young adults were considered separately. Using a robust immunohistochemical assay for MV infection, we failed to find evidence of MV in biopsies from 97 cases of HL and RT-PCR studies similarly gave negative results. This study therefore provides no evidence that MV is directly involved in the development of HL. However, when age at first reported MV infection was investigated, significant differences emerged with children infected before school-age having higher risk, especially of EBV-ve HL, when compared with children infected at older ages; the interpretation of these latter results is unclear.

Modelling the correlation between processing parameters and properties of maraging steels using artificial neural network

An artificial neural network (ANN) model is developed for the analysis and simulation of the correlation between the properties of maraging steels and composition, processing and working conditions. The input parameters of the model consist of alloy composition, processing parameters (including cold deformation degree, ageing temperature, and ageing time), and working temperature. The outputs of the ANN model include property parameters namely: ultimate tensile strength, yield strength, elongation, reduction in area, hardness, notched tensile strength, Charpy impact energy, fracture toughness, and martensitic transformation start temperature. Good performance of the ANN model is achieved. The model can be used to calculate properties of maraging steels as functions of alloy composition, processing parameters, and working condition. The combined influence of Co and Mo on the properties of maraging steels is simulated using the model. The results are in agreement with experimental data. Explanation of the calculated results from the metallurgical point of view is attempted. The model can be used as a guide for further alloy development.

Applying a QSPR correlation to the prediction of surface tensions of ionic liquids

Ionic liquids (ILs) have attracted large amount of interest due to their unique properties. Although large effort has been focused on the investigation of their potential application, characterization of ILs properties and structure–property relationships of ILs are poorly understood. Computer aided molecular design (CAMD) of ionic liquids (ILs) can only be carried if predictive computational methods for the ILs properties are available. The limited availability of experimental data and their quality have been preventing the development of such tools. Based on experimental surface tension data collected from the literature and measured at our laboratory, it is here shown how a quantitative structure–property relationship (QSPR) correlation for parachors can be used along with an estimation method for the densities to predict the surface tensions of ILs. It is shown that a good agreement with literature data is obtained. For circa 40 ionic liquids studied a mean percent deviation (MPD) of 5.75% with a maximum deviation inferior to 16% was observed. A correlation of the surface tensions with the molecular volumes of the ILs was developed for estimation of the surface tensions at room temperature. It is shown that it can describe the experimental data available within a 4.5% deviation. The correlations here developed can thus be used to evaluate the surface tension of ILs for use in process design or in the CAMD of new ionic liquids.