Crime, Institutions and Sector-Specific FDI in Latin America

In this article, we explore how crime and institutions affect the flow of capital in the form of foreign direct investment (FDI) to Latin American and Caribbean countries in the primary, secondary and tertiary sectors during the 1996-2010 period. We use three different variables related to violent crime: homicides, crime victimization, and an index of organized crime. We find that there is a correlation between the institutional and crime variables, where the significance of institutional variables tends to disappear when the crime variables are added to the model. We find that higher crime victimization and organized crime are associated with lower FDI in the tertiary sector. We do not find that crime affects FDI inflows to Latin America in the primary and secondary sector

A transcriptomics-based in vitro assay for predicting chemical genotoxicity in vivo

The lack of accurate in vitro assays for predicting in vivo toxicity of chemicals together with new legislations demanding replacement and reduction of animal testing has triggered the development of alternative methods. This study aimed at developing a transcriptomics-based in vitro prediction assay for in vivo genotoxicity. Transcriptomics changes induced in the human liver cell line HepG2 by 34 compounds after treatment for 12, 24, and 48h were used for the selection of gene-sets that are capable of discriminating between in vivo genotoxins (GTX) and in vivo nongenotoxins (NGTX). By combining transcriptomics with publicly available results for these chemicals from standard in vitro genotoxicity studies, we developed several prediction models. These models were validated by using an additional set of 28 chemicals. The best prediction was achieved after stratification of chemicals according to results from the Ames bacterial gene mutation assay prior to transcriptomics evaluation after 24h of treatment. A total of 33 genes were selected for discriminating GTX from NGTX for Ames-positive chemicals and 22 for Ames-negative chemicals. Overall, this method resulted in 89% accuracy and 91% specificity, thereby clearly outperforming the standard in vitro test battery. Transcription factor network analysis revealed HNF3a, HNF4a, HNF6, androgen receptor, and SP1 as main factors regulating the expression of classifiers for Ames-positive chemicals. Thus, the classical bacterial gene mutation assay in combination with in vitro transcriptomics in HepG2 is proposed as an upgraded in vitro approach for predicting in vivo genotoxicity of chemicals holding a great promise for reducing animal experimentations on genotoxicity