The multinational corporation: a study in the political economy of power Neil Gordon McDonald Renwick

This study focuses on the question of how far multinational corporations lie beyond the regulatory control of nation-states. In what sense are these corporations autonomous organisations whose rules Ana practice exist independent of State control? This is a political rather than economic question, for concepts such as power, control or independence are fundamentally political in nature,. The thesis analyses four leading interpretations or the multinationals and their relations with States, the actual characteristics of both 'actors' and the role of oil multinationals in the international oil industry in relation to 'host' and 'home' governments. Much of the debate over multinationals centres upon their unique character. Organised on the basis of productive capital in a number of countries, that is, subsidiaries linked to centralised managerial; technical and financial resources, it is argued that these companies exercise global flexibility with which the States tied to their borders- cannot compete. 'Global Reach' is therefore claimed to allow multinationals to ignore national regulations and interests. This analysis, however, suggests that the multinational-State relationship takes place within the framework of national regulations and international supervisory bodies that effectively form the 'rules' for the multinationals and the boundaries for bargaining. The multinational forms an important and integral part of the prevailing system that is largely reflective of State-interests, rather than a major challenge to the authority of the States

MicroRNAs MiR-17, MiR-20a, and MiR-106b Act in Concert to Modulate E2F Activity on Cell Cycle Arrest during Neuronal Lineage Differentiation of USSC

MicroRNAs are short (∼22 nt) non-coding regulatory RNAs that control gene expression at the post-transcriptional level. Here the functional impact of microRNAs on cell cycle arrest during neuronal lineage differentiation of unrestricted somatic stem cells from human cord blood (USSC) was analyzed./M transition. Most strikingly, miR-17, -20a, and -106b were found to promote cell proliferation by increasing the intracellular activity of E2F transcription factors, despite the fact that miR-17, -20a, and -106b directly target the transcripts that encode for this protein family./S transition

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers

Control of foliar diseases in barley:towards an integrated approach

Barley is one of the world's most important crops providing food and related products for millions of people. Diseases continue to pose a serious threat to barley production, despite the use of fungicides and resistant varieties, highlighting the impact of fungicide resistance and the breakdown of host plant resistance on the efficacy of control measures. This paper reviews progress towards an integrated approach for disease management in barley in which new methods may be combined with existing measures to improve the efficacy of control in the long-term. Advances have been made in genetic mapping of resistance (R) genes and in identifying novel sources of genes in wild barley populations and land races. Marker assisted selection techniques are being used to pyramid R genes to increase the durability of resistance. Elicitors to induce host resistance used in combination with fungicides can provide effective disease control in the field and could delay the evolution of fungicide insensitivity. Traits that may contribute to disease tolerance and escape have been identified and the extent of genetic variation within barley germplasm is being determined. Tools are being developed to integrate the above methods via an assessment of the risk of economic injury occurring from disease to guide decisions on the requirement for fungicide treatment. Barriers exist to the adoption of integrated management approaches from growers and end-users further down the supply chain (e. g. acceptance of variety mixtures) and policy incentives from government may be required for it to be taken up in practice. © 2012 KNPV