Prohibiting Restriction of Free Trade within the Community: Articles 30-36 of the EEC Treaty

The problem of accommodating the tensions of power between the European Economic Community and individual Member States is particularly acute in the area of prohibitions on restriction on free trade within the Community. Professor van Themaat and Mr. Gormley analyze key aspects of this problem in select decisions of the Court of Justice concerning Articles 30-36 of the EEC Treaty. The areas of discussion include the extent to which Articles 30-36 affect internal economic regulations of Member States, the difference between trading within an established Community organization and trade in an area where no organization exists, and the relation of Articles 30-36 to other provisions of the Treaty. The authors conclude with a consideration of the prospects for federalization within the Common Market in light of the cases discussed earlier

Prohibiting Restriction of Free Trade within the Community: Articles 30-36 of the EEC Treaty

The problem of accommodating the tensions of power between the European Economic Community and individual Member States is particularly acute in the area of prohibitions on restriction on free trade within the Community. Professor van Themaat and Mr. Gormley analyze key aspects of this problem in select decisions of the Court of Justice concerning Articles 30-36 of the EEC Treaty. The areas of discussion include the extent to which Articles 30-36 affect internal economic regulations of Member States, the difference between trading within an established Community organization and trade in an area where no organization exists, and the relation of Articles 30-36 to other provisions of the Treaty. The authors conclude with a consideration of the prospects for federalization within the Common Market in light of the cases discussed earlier

Studies on the susceptibility of ultraviolet irradiated BHK21 C13 cells to transformation by polyoma virus and some aspects of their radiobiology

The role played by virused end radiation in the etiology of cancer is reviewed. The isolation and properties of one tumour causing virus, polyoma virus, are described. When BHK21 C13 cells were irradiated with low does of ultraviolet light before infection with polyoma virus and enhancement of the transformation rate was observed. A two-fold rise in the proportion of transformed colonics to normal colonies was found was found after a radiation dose of 100 ergs/mm2. This irradiation dose was sufficient to lower the plating efficiency of the cells by approximately 45%. A method was developed by which the rise in the proportion of transformed cells could be more adequately observed. This method involved the delayed plating of irradiated, infected cells in agar suspension medium. BHK21 C13 cells which were irradiated up to 24 hour before infection with polyoma virus did not show loss of the transformation enhacement. No enhacement was observed, however, when the cells were irradiated four or more hours after infection. The irradiation doses used did not significantly affect the transforming ability of the virus particles. The results obtained when experiments were performed to test the effect ultraviolet radiation on the interferon synthesising capacity of the cells suggested that reduced synthesis of interferon was not the mechanism by which transformation enhancement occurred. Survival curves were determined for BHK21 C13 cells and two lined of polyoma virus transformed BHK21 C13 cells. The curved obtained were of the normal "C" form. The transformed cells were found to be more resistant to ultraviolet irradiation than the untransformed cells. All cell lines tested showed a greater resistance to ultraviolet irradiation when plated out for colony formation in the presence of mouse embryo feeder cells. Cycloheximide, and inhibitor of protein synthesis, did not significantly affect the survival curves. Photoreactivation of ultraviolet radiation induced damage could not be demonstrated in BHK21 C13 cells. Repair of ultraviolet radiation induced sublethal damage in BHK21 C13 cells was demonstrated by a split dose technique, although the expression of this repair was not observed until 8 hours after the initial irradiation. Transformation of BHK21 C13 cells by ultraviolet irradiation alone could not be demonstrated. The results are discussed with regard to a possible mechanism for the observed enhacement of transformation

Classification of tissues and disease subtypes using whole-genome signatures

Development and application of microarray technology in biological research has led to compilation of expression and sequence data on a genome-wide scale. Given the volume of data produced and the complexity of gene regulatory mechanisms, it can be difficult to extract meaningful biological information. Classification can be used to reduce the complexity through the detection of genes, genetic loci or conditions that share common attributes and the identification of gene expression patterns or genotypes associated with phenotype. In the study of cancer, supervised classification has been applied to identify gene expression biomarkers of different disease states. Clinically validated biomarkers are valuable indicators for diagnosis and guiding therapeutic strategy. We developed an iterative machine learning algorithm to compare the predictive value of biomarker sets chosen by supervised classification against sets selected randomly from known disease-related genes. Both supervised classification and feature selection based on prior knowledge resulted in discriminative classification of molecular phenotypes in breast cancer and lymphoma. Compilation of gene expression data has led to the identification of genes with bimodal, or switch-like, expression patterns. We used unsupervised, supervised and model-based classification methods to investigate the biological relevance of bimodal expression patterns and to evaluate their potential for class discovery and prediction. Both model-based and supervised classification resulted in the accurate classification of samples by tissue phenotype or infectious disease. Functional enrichment analysis indicates switch-like genes are involved in tissue-specific or immune response functions. Taken together, this evidence supports the assertion that bimodal expression patterns are biologically relevant. Clinical relevance of bimodal expression patterns was investigated in an association study of genotypes of families affected by autism. A subset of neural-specific switch-like genes was used to identify candidate gene regions which may contain genetic variants associated with autism risk. A two-stage family-based association test detected an autism susceptibility locus in the q26 region of chromosome 10. The coding region of the fibroblast growth factor receptor 2 (FGFR2) gene is 80 kilobases downstream from the identified locus. Altered expression of FGFR2 may be a contributing genetic factor in development of autism. Identification of the susceptibility locus provides motivation for novel hypotheses concerning the molecular basis of autism. In addition, we provide a method for integration of gene expression and genotype data that may lead to the identification of disease-related polymorphisms in other disorders.Ph.D., Biomedical Engineering -- Drexel University, 200

Usefulness of mid-infrared spectroscopy as a tool to estimate body condition score change from milk samples in intensively-fed dairy cows.

Directly measuring individual cow energy balance is not trivial. Other traits, like body condition score (BCS) and BCS change (ΔBCS) can, however, be used as an indicator of cow energy status. Body condition score is a metric used world-wide to estimate cow body reserves and the estimation of ΔBCS was, until now, conditional on the availability of multiple BCS assessments. The aim of the present study was to estimate ΔBCS from milk mid-infrared (MIR) spectra and days in milk (DIM) in intensively-fed dairy cows using statistical prediction methods. Daily BCS was interpolated from cubic splines fitted through the BCS records and daily ΔBCS was calculated from these splines. Body condition score change records were merged with milk MIR spectra recorded on the same week. The data set comprised 37,077 ΔBCS phenotypes across 9,403 lactations from 6,988 cows in 151 herds based in Quebec (Canada). Partial least squares regression (PLSR) and a neural network (NN) were then used to estimate ΔBCS from 1) MIR spectra only, 2) DIM only, or 3) MIR spectra and DIM together. ΔBCS data in both the first 120 DIM and 305 DIM of lactation were used to develop the estimates. Daily ΔBCS had a standard deviation of 4.40*10-3 BCS units in the 120-d data set and of 3.63*10-3 BCS units in the 305-d data set. 4-fold cross-validation was used to calibrate and test the prediction equations. External validation was also conducted using more recent years of data. Irrespective of whether based on the first 120 or 305 DIM, or when MIR spectra only, DIM only or MIR spectra and DIM were jointly used as prediction variables, NN produced the lowest root mean square error (RMSE) of cross-validation (1.81*10-3 BCS units and 1.51*10-3 BCS units, respectively, using the 120-d and 305-d data set). Relative to predictions for the entire 305 DIM, the RMSE of cross-validation was 15.4% and 1.5% lower in the first 120 DIM when using PLSR and NN, respectively. Predictions from DIM only were more accurate than those using just MIR spectra data but, irrespective of the data set and of the prediction model used, the combining DIM information with MIR spectral data as prediction variables reduced the RMSE compared with inclusion of DIM alone, albeit the benefit was small (the RMSE from cross-validation was reduced up to 5.5% when DIM and spectral data were jointly used as model features instead of DIM only). However, when predicting extreme ΔBCS records, the MIR spectral data was more informative than DIM. Model performance when predicting ΔBCS records in future years was similar to that from cross-validation demonstrating the ability of MIR spectra of milk and DIM combined to estimate ΔBCS, particularly in early lactation. This can be used to routinely generate estimates of ΔBCS to aid in day-to-day individual cow management