Importing Corruption Culture from Overseas: Evidence from Corporate Tax Evasion in the United States

This paper studies how cultural norms and enforcement policies influence illicit corporate activities. Using confidential IRS audit data, we show that corporations with owners from countries with higher corruption norms engage in higher amounts of tax evasion in the U.S. This effect is strong for small corporations and decreases as the size of the corporation increases. In the mid-2000s, the United States implemented several enforcement measures which significantly increased tax compliance. However, we find that these enforcement efforts were less effective in reducing tax evasion by corporations whose owners are from countries with higher corruption norms. This suggests that cultural norms can be a challenge to legal enforcement.

Meta-analysis of diffusion tensor imaging studies shows altered fractional anisotropy occurring in distinct brain areas in association with depression

Fractional anisotropy anomalies occurring in the white matter tracts in the brains of depressed patients may reflect microstructural changes underlying the pathophysiology of this disorder. We conducted a meta-analysis of fractional anisotropy abnormalities occurring in major depressive disorder using voxel-based diffusion tensor imaging studies. Using the Embase, PubMed and Google Scholar databases, 89 relevant data sets were identified, of which 7 (including 188 patients with major depressive disorder and 221 healthy controls) met our inclusion criteria. Authors were contacted to retrieve any additional data required. Coordinates were extracted from clusters of significant white matter fractional anisotropy differences between patients and controls. Relevant demographic, clinical and methodological variables were extracted from each study or obtained directly from authors. The meta-analysis was carried out using Signed Differential Mapping. Patients with depression showed decreased white matter fractional anisotropy values in the superior longitudinal fasciculus and increased fractional anisotropy values in the fronto-occipital fasciculus compared to controls. Using quartile and jackknife sensitivity analysis, we found that reduced fractional anisotropy in the left superior longitudinal fasciculus was very stable, with increases in the right fronto-occipital fasciculus driven by just one study. In conclusion, our meta-analysis revealed a significant reduction in fractional anisotropy values in the left superior longitudinal fasciculus, which may ultimately play an important role in the pathology of depression

TMFoldRec: a statistical potential-based transmembrane protein fold recognition tool.

BACKGROUND: Transmembrane proteins (TMPs) are the key components of signal transduction, cell-cell adhesion and energy and material transport into and out from the cells. For the deep understanding of these processes, structure determination of transmembrane proteins is indispensable. However, due to technical difficulties, only a few transmembrane protein structures have been determined experimentally. Large-scale genomic sequencing provides increasing amounts of sequence information on the proteins and whole proteomes of living organisms resulting in the challenge of bioinformatics; how the structural information should be gained from a sequence. RESULTS: Here, we present a novel method, TMFoldRec, for fold prediction of membrane segments in transmembrane proteins. TMFoldRec based on statistical potentials was tested on a benchmark set containing 124 TMP chains from the PDBTM database. Using a 10-fold jackknife method, the native folds were correctly identified in 77 % of the cases. This accuracy overcomes the state-of-the-art methods. In addition, a key feature of TMFoldRec algorithm is the ability to estimate the reliability of the prediction and to decide with an accuracy of 70 %, whether the obtained, lowest energy structure is the native one. CONCLUSION: These results imply that the membrane embedded parts of TMPs dictate the TM structures rather than the soluble parts. Moreover, predictions with reliability scores make in this way our algorithm applicable for proteome-wide analyses. AVAILABILITY: The program is available upon request for academic use

Preference Change

International audienceMost models of rational action assume that all possible states and actions are pre-defined and that preferences change only when beliefs do. But several decision and game problems lack these features, calling for a dynamic model of preferences: preferences can change when unforeseen possibilities come to light or when there is no specifiable or measurable change in belief. We propose a formally precise dynamic model of preferences that extends an existing static model (Boutilier et al. in J Artif Intell Res 21:135-191, 2004). Our axioms for updating preferences preserve consistency while minimising change, like Hansson's (Theory Decis 38(1):1-28, 1995). But unlike prior models of preference change, ours supports default reasoning with partial preference information, which is essential to handle decision problems where the decision tree isn't surveyable. We also show that our model avoids problems for other models of preference change discussed in Spohn (Preference change: approaches from philosophy. Economics and Psychology: Springer, pp 109-121, 2009)

Long-Term Effects of the Periconception Period on Embryo Epigenetic Profile and Phenotype: The Role of Stress and How This Effect Is Mediated

Stress represents an unavoidable aspect of human life, and pathologies associated with dysregulation of stress mechanisms - particularly psychiatric disorders - represent a significant global health problem. While it has long been observed that levels of stress experienced in the periconception period may greatly affect the offspring's risk of psychiatric disorders, the mechanisms underlying these associations are not yet comprehensively understood. In order to address this question, this chapter will take a 'top-down' approach, by first defining stress and associated concepts, before exploring the mechanistic basis of the stress response in the form of the hypothalamic-pituitary-adrenal (HPA) axis, and how dysregulation of the HPA axis can impede our mental and physical health, primarily via imbalances in glucocorticoids (GCs) and their corresponding receptors (GRs) in the brain. The current extent of knowledge pertaining to the impact of stress on developmental programming and epigenetic inheritance is then extensively discussed, including the role of chromatin remodelling associated with specific HPA axis-related genes and the possible role of regulatory RNAs as messengers of environmental stress both in the intrauterine environment and across the germ line. Furthering our understanding of the role of stress on embryonic development is crucial if we are to increase our predictive power of disease risk and devise-effective treatments and intervention strategies

FoxO1, A2M, and TGF-beta 1 : three novel genes predicting depression in gene X environment interactions are identified using cross-species and cross-tissues transcriptomic and miRNomic analyses

To date, gene-environment (GxE) interaction studies in depression have been limited to hypothesis-based candidate genes, since genome-wide (GWAS)-based GxE interaction studies would require enormous datasets with genetics, environmental, and clinical variables. We used a novel, cross-species and cross-tissues "omics" approach to identify genes predicting depression in response to stress in GxE interactions. We integrated the transcriptome and miRNome profiles from the hippocampus of adult rats exposed to prenatal stress (PNS) with transcriptome data obtained from blood mRNA of adult humans exposed to early life trauma, using a stringent statistical analyses pathway. Network analysis of the integrated gene lists identified the Forkhead box protein O1 (FoxO1), Alpha-2-Macroglobulin (A2M), and Transforming Growth Factor Beta 1 (TGF-beta 1) as candidates to be tested for GxE interactions, in two GWAS samples of adults either with a range of childhood traumatic experiences (Grady Study Project, Atlanta, USA) or with separation from parents in childhood only (Helsinki Birth Cohort Study, Finland). After correction for multiple testing, a meta-analysis across both samples confirmed six FoxO1 SNPs showing significant GxE interactions with early life emotional stress in predicting depressive symptoms. Moreover, in vitro experiments in a human hippocampal progenitor cell line confirmed a functional role of FoxO1 in stress responsivity. In secondary analyses, A2M and TGF-beta 1 showed significant GxE interactions with emotional, physical, and sexual abuse in the Grady Study. We therefore provide a successful 'hypothesis-free' approach for the identification and prioritization of candidate genes for GxE interaction studies that can be investigated in GWAS datasets.Peer reviewe