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The widespread use of video games among adolescents has raised concerns about their impact on psychological and social development. This study aimed to assess the effects of different types of parental mediation on adolescents' tendency to use video games to avoid negative emotions and determine the relationship between adolescents' interpersonal skills and their reliance on online video games for escapism. Participants were 452 adolescents from 15 middle and high schools. Data on sociodemographic information, gaming habits, parental control of online gaming, interpersonal skills, and reasons for playing online games were also collected. Hierarchical multiple regression was used to analyze the data, with online video game escapism as the dependent variable. Results supported the study's hypothesis that both parental mediation and adolescent interpersonal skills significantly predict the use of online video games for escapism. Higher levels of parental monitoring were associated with a lower tendency of adolescents to use video games to escape negative emotions, while parental mediation supporting autonomy showed a similar but weaker protective effect. At the same time, parental monitoring was also found to be associated with lower interpersonal skills, notably higher impulsivity, narcissism, and stress in social situations. In addition, adolescents with higher levels of impulsivity were more likely to use video games for escapism. These findings highlight the importance of balanced parental involvement and the development of adolescents' social skills to mitigate the risks of problematic online gaming. Interventions should promote effective parental mediation strategies and enhance adolescents' interpersonal skills to reduce their tendency to use video games as a coping mechanism for real‐life challenges. Effective parental mediation and improved interpersonal skills are critical for promoting healthier gaming habits and reducing adolescent escapism. [ABSTRACT FROM AUTHOR]

Background: In previous investigations of combined miRNAs/mRNAs expressions in neurodegenerative diseases like Multiple Sclerosis (MS) and Amyotrophic Lateral Sclerosis (ALS) we have targeted some interesting genes and molecular pathways that needed further confirmation. Methods: By nanofluidic qPCR analysis, we aimed to verify the expression of genes that resulted differentially expressed in the previous analyses. Data from MS patients -- either the pediatric and the adult occurrence of the disease (adMS and pedMS, respectively) -- was compared to age-matched healthy groups. As neurological controls we recruited a cohort of ALS subjects, considering published searches of possible genetic similarities between the two diseases. Results: The main results confirmed the involvement of most of the investigated genes in pedMS and adMS, like BACH2 and MICAL3. On the other hand, suggestive MS candidate genes like TNFSF13B showed an interesting trend possibly influenced by interfering factors, such as concomitant disease-modifying treatments; it is worth noting that TNFSF13B was one of the genes upregulated in ALS compared to age-matched adMS patients, together with the transcription factor TFDP1. Conclusions: Although with caution due to the small sample size, this study confirms the interest in transcriptomic analysis supported by integrated and educated bioinformatics evaluations, to shed further light in complex neurological diseases. [ABSTRACT FROM AUTHOR]

Abstract Background It is known from recent studies that more than 90% of human multi-exon genes are subject to Alternative Splicing (AS), a key molecular mechanism in which multiple transcripts may be generated from a single gene. It is widely recognized that a breakdown in AS mechanisms plays an important role in cellular differentiation and pathologies. Polymerase Chain Reactions, microarrays and sequencing technologies have been applied to the study of transcript diversity arising from alternative expression. Last generation Affymetrix GeneChip Human Exon 1.0 ST Arrays offer a more detailed view of the gene expression profile providing information on the AS patterns. The exon array technology, with more than five million data points, can detect approximately one million exons, and it allows performing analyses at both gene and exon level. In this paper we describe BEAT, an integrated user-friendly bioinformatics framework to store, analyze and visualize exon arrays datasets. It combines a data warehouse approach with some rigorous statistical methods for assessing the AS of genes involved in diseases. Meta statistics are proposed as a novel approach to explore the analysis results. BEAT is available at http://beat.ba.itb.cnr.it. Results BEAT is a web tool which allows uploading and analyzing exon array datasets using standard statistical methods and an easy-to-use graphical web front-end. BEAT has been tested on a dataset with 173 samples and tuned using new datasets of exon array experiments from 28 colorectal cancer and 26 renal cell cancer samples produced at the Medical Genetics Unit of IRCCS Casa Sollievo della Sofferenza. To highlight all possible AS events, alternative names, accession Ids, Gene Ontology terms and biochemical pathways annotations are integrated with exon and gene level expression plots. The user can customize the results choosing custom thresholds for the statistical parameters and exploiting the available clinical data of the samples for a multivariate AS analysis. Conclusions Despite exon array chips being widely used for transcriptomics studies, there is a lack of analysis tools offering advanced statistical features and requiring no programming knowledge. BEAT provides a user-friendly platform for a comprehensive study of AS events in human diseases, displaying the analysis results with easily interpretable and interactive tables and graphics.

This work describes a non-invasive, automated software framework to discriminate between individuals with a genetic disorder, Pitt–Hopkins syndrome (PTHS), and healthy individuals through the identification of morphological facial features. The input data consist of frontal facial photographs in which faces are located using histograms of oriented gradients feature descriptors. Pre-processing steps include color normalization and enhancement, scaling down, rotation, and cropping of pictures to produce a series of images of faces with consistent dimensions. Sixty-eight facial landmarks are automatically located on each face through a cascade of regression functions learnt via gradient boosting to estimate the shape from an initial approximation. The intensities of a sparse set of pixels indexed relative to this initial estimate are used to determine the landmarks. A set of carefully selected geometric features, for example, the relative width of the mouth or angle of the nose, is extracted from the landmarks. The features are used to investigate the statistical differences between the two populations of PTHS and healthy controls. The methodology was tested on 71 individuals with PTHS and 55 healthy controls. The software was able to classify individuals with an accuracy rate of 91%, while pediatricians achieved a recognition rate of 74%. Two geometric features related to the nose and mouth showed significant statistical difference between the two populations. [ABSTRACT FROM AUTHOR]

Summary: Viral infections are accompanied by a massive production of small interfering RNAs (siRNAs) of plant origin, such as virus‐activated (va)siRNAs, which drive the widespread silencing of host gene expression, and whose effects in plant pathogen interactions remain unknown.By combining phenotyping and molecular analyses, we characterized vasiRNAs that are associated with typical mosaic symptoms of cauliflower mosaic virus infection in two crops, turnip (Brassica rapa) and oilseed rape (Brassica napus), and the reference plant Arabidopsis thaliana.We identified 15 loci in the three infected plant species, whose transcripts originate vasiRNAs. These loci appear to be generally affected by virus infections in Brassicaceae and encode factors that are centrally involved in photosynthesis and stress response, such as Rubisco activase (RCA), senescence‐associated protein, heat shock protein HSP70, light harvesting complex, and membrane‐related protein CP5. During infection, the expression of these factors is significantly downregulated, suggesting that their silencing is a central component of the plant's response to virus infections. Further findings indicate an important role for 22 nt long vasiRNAs in the plant's endogenous RNA silencing response.Our study considerably enhances knowledge about the new class of vasiRNAs that are triggered in virus‐infected plants and will help to advance strategies for the engineering of gene clusters involved in the development of crop diseases. [ABSTRACT FROM AUTHOR]

A handheld laser-induced breakdown spectroscopy (LIBS) instrument is proposed as a novel tool that is able to provide information on the nature of meteorites and discriminate among iron, stone, stony-iron meteorites and meteor-wrongs. Further, a novel fuzzy logic-based inference algorithm is applied to broadband LIBS spectra for the identification of meteorites and their classification according to their origin and nature. The identification of meteorites is a decision-making problem based on a compromise among human experience, visual evidence and analytical data, which fuzzy logic is proved to be able to solve. The final model is able to correctly classify 25 out of 26 samples and provides a set of IF-THEN rules that describe how some selected wavelengths are involved in the classification task. [ABSTRACT FROM AUTHOR]