The Neuropeptide Y Single-nucleotide Polymorphism rs16147 Moderates the Effect of Alcohol Dependence on Depression

Background: Previous studies suggest that alcohol dependence is associated with depression, however, the effect of alcohol dependence varies from individual to individual, which may be due to different genetic backgrounds. The interactions between alcohol dependence and different gene polymorphisms may finally shape the onset of depression. Neuropeptide Y (NPY), which can maintain homeostasis from high-stress stimulation, may protect individuals from the onset of depression. Here, we explored whether the NPY rs16147 regulates depression in individuals with alcohol dependence during the period of alcohol dependence withdrawal.Methods: A total of 455 males with alcohol dependence were recruited. The scale of MAST and SDS were respectively used to analyze the condition of alcohol dependence and depression. Genomic DNA was extracted from each blood sample and NPY polymorphisms were genotyped. The interaction between NPY rs16147 and alcohol dependence on depression was first analyzed. Then, region of significance analysis was used to confirm which model provided the best fit for the interaction (diathesis-stress or differential susceptibility). Finally, by using internal replication analyses, the accuracy and robustness of the interaction results were improved.Results: Alcohol dependence was positively correlated with depression. CC homozygotes of NPYrs16147 exhibited less depression when exposed to low alcohol dependence, but more depression when exposed to high alcohol dependence. Individuals with the T allele showed the opposite result.Conclusions: NPY rs16147 might be correlated with susceptibility for depression in males during alcohol dependence withdrawal. The findings support the differential susceptibility model.

Marketing Mix Modeling Using PLS-SEM, Bootstrapping the Model Coefficients

Partial least squares structural equations modeling (PLS-SEM) uses sampling bootstrapping to calculate the significance of the model parameter estimates (e.g., path coefficients and outer loadings). However, when data are time series, as in marketing mix modeling, sampling bootstrapping shows inconsistencies that arise because the series has an autocorrelation structure and contains seasonal events, such as Christmas or Black Friday, especially in multichannel retailing, making the significance analysis of the PLS-SEM model unreliable. The alternative proposed in this research uses maximum entropy bootstrapping (meboot), a technique specifically designed for time series, which maintains the autocorrelation structure and preserves the occurrence over time of seasonal events or structural changes that occurred in the original series in the bootstrapped series. The results showed that meboot had superior performance than sampling bootstrapping in terms of the coherence of the bootstrapped data and the quality of the significance analysis.

Features of the initial stage of investigating fraud with financial resources in cyberspace

The article aims to characterize the forensic features of the initial stage of investigating fraud with financial resources in cyberspace, its significance, analysis, and justification as a type of cybercrime that is dangerous for everyone, and prove the need for urgent measures to prevent and combat such criminal offenses. The authors used several methods of scientific cognition: logical-semantic, system-structural, analytical, formal-legal, forecasting, dialectical, interpretation, and hermeneutics. The article focuses on the general provisions of the forensic characteristics of Internet fraud with financial resources; analysis of the information model of the mechanism of committing fraud with financial resources in the field of computer information; coverage of the tactical features of individual investigative actions at the initial stage of the investigation of fraud with financial resources in cyberspace. It was concluded that the effectiveness of combating Internet fraud and the level of cybersecurity in Ukraine is very low. Therefore, the investigation of fraud with financial resources in cyberspace requires in-depth specific knowledge from the subjects of the investigation.