From early stress to 12-month development in very preterm infants: Preliminary findings on epigenetic mechanisms and brain growth

Very preterm (VPT) infants admitted to Neonatal Intensive Care Unit (NICU) are at risk for altered brain growth and less-than-optimal socio-emotional development. Recent research suggests that early NICU-related stress contributes to socio-emotional impairments in VPT infants at 3 months through epigenetic regulation (i.e., DNA methylation) of the serotonin transporter gene (SLC6A4). In the present longitudinal study we assessed: (a) the effects of NICU-related stress and SLC6A4 methylation variations from birth to discharge on brain development at term equivalent age (TEA); (b) the association between brain volume at TEA and socio-emotional development (i.e., Personal-Social scale of Griffith Mental Development Scales, GMDS) at 12 months corrected age (CA). Twenty-four infants had complete data at 12-month-age. SLC6A4 methylation was measured at a specific CpG previously associated with NICU-related stress and socio-emotional stress. Findings confirmed that higher NICU-related stress associated with greater increase of SLC6A4 methylation at NICU discharge. Moreover, higher SLC6A4 discharge methylation was associated with reduced anterior temporal lobe (ATL) volume at TEA, which in turn was significantly associated with less-than-optimal GMDS Personal-Social scale score at 12 months CA. The reduced ATL volume at TEA mediated the pathway linking stress-related increase in SLC6A4 methylation at NICU discharge and socio-emotional development at 12 months CA. These findings suggest that early adversity-related epigenetic changes might contribute to the long-lasting programming of socio-emotional development in VPT infants through epigenetic regulation and structural modifications of the developing brain

The Assertive Brain : Anterior Cingulate Phosphocreatine plus Creatine Levels Correlate With Self-Directedness in Healthy Adolescents

Despite various advances in the study of the neurobiological underpinnings of personality traits, the specific neural correlates associated with character and temperament traits are not yet fully understood. Therefore, this study aims to fill this gap by exploring the biochemical basis of personality, which is explored with the temperament and character inventory (TCI), during brain development in a sample of adolescents. Twenty-six healthy adolescents (aged between 13 and 21 years; 9 males and 18 females) with behavioral and emotional problems underwent a TCI evaluation and a 3T single-voxel proton magnetic resonance spectroscopy (1H MRS) acquisition of the anterior cingulate cortex (ACC). Absolute metabolite levels were estimated using LCModel: significant correlations between metabolite levels and selective TCI scales were identified. Specifically, phosphocreatine plus creatine (PCr+Cre) significantly correlated with self-directedness, positively, and with a self-transcendence (ST), negatively, while glycerophosphocholine plus phosphocholine (GPC+PC) and myo-inositol negatively correlated with ST. To the best of our knowledge, this is the first study reporting associations of brain metabolites with personality traits in adolescents. Therefore, our results represent a step forward for personality neuroscience within the study of biochemical systems and brain structures

The future of Cybersecurity in Italy: Strategic focus area

This volume has been created as a continuation of the previous one, with the aim of outlining a set of focus areas and actions that the Italian Nation research community considers essential. The book touches many aspects of cyber security, ranging from the definition of the infrastructure and controls needed to organize cyberdefence to the actions and technologies to be developed to be better protected, from the identification of the main technologies to be defended to the proposal of a set of horizontal actions for training, awareness raising, and risk management

Deep learning for the prediction of treatment response in depression

Background: Mood disorders are characterized by heterogeneity in severity, symptoms and treatment response. The possibility of selecting the correct therapy on the basis of patient-specific biomarker may be a considerable step towards personalized psychiatry. Machine learning methods are gaining increasing popularity in the medical field. Once trained, the possibility to consider single patients in the analyses instead of whole groups makes them particularly appealing to investigate treatment response. Deep learning, a branch of machine learning, lately gained attention, due to its effectiveness in dealing with large neuroimaging data and to integrate them with clinical, molecular or -omics biomarkers. Methods: In this mini-review, we summarize studies that use deep learning methods to predict response to treatment in depression. We performed a bibliographic search on PUBMED, Google Scholar and Web of Science using the terms “psychiatry”, “mood disorder”, “depression”, “treatment”, “deep learning”, “neural networks”. Only studies considering patients’ datasets are considered. Results: Eight studies met the inclusion criteria. Accuracies in prediction of response to therapy were considerably high in all studies, but results may be not easy to interpret. Limitations: The major limitation for the current studies is the small sample size, which constitutes an issue for machine learning methods. Conclusions: Deep learning shows promising results in terms of prediction of treatment response, often outperforming regression methods and reaching accuracies of around 80%. This could be of great help towards personalized medicine. However, more efforts are needed in terms of increasing datasets size and improved interpretability of result

Twin MRI studies on genetic and environmental determinants of brain morphology and function in the early lifespan

Neurodevelopment represents a period of increased opportunity and vulnerability, during which a complex confluence of genetic and environmental factors influences brain growth trajectories, cognitive and mental health outcomes. Recently, magnetic resonance imaging (MRI) studies on twins have increased our knowledge of the extent to which genes, the environment and their interactions shape inter-individual brain variability. The present review draws from highly salient MRI studies in young twin samples to provide a robust assessment of the heritability of structural and functional brain changes during development. The available studies suggest that (as with many other traits), global brain morphology and network organization are highly heritable from early childhood to young adulthood. Conversely, genetic correlations among brain regions exhibit heterogeneous trajectories, and this heterogeneity reflects the progressive, experience-related increase in brain network complexity. Studies also support the key role of environment in mediating brain network differentiation via changes of genetic expression and hormonal levels. Thus, rest- and task-related functional brain circuits seem to result from a contextual and dynamic expression of heritability

Association of increased genotypes risk for bipolar disorder with brain white matter integrity investigated with tract-based spatial statistics : Special Section on “Translational and Neuroscience Studies in Affective Disorders”. Section Editor, Maria Nobile MD, PhD. This Section of JAD focuses on the relevance of translational and neuroscience studies in providing a better understanding of the neural basis of affective disorders. The main aim is to briefly summarise relevant research findings in clinical neuroscience with particular regards to specific innovative topics in mood and anxiety disorders

Background Diffusion tensor imaging (DTI) studies, which allow the in-vivo investigation of brain tissue integrity, have shown that bipolar disorder (BD) patients present signs of white matter dysconnectivity. In parallel, genome-wide association studies (GWAS) identified several risk genetic variants for BD. I Methods In this mini-review, we summarized DTI studies coupling tract-based spatial statistics (TBSS), a reliable technique exploring white matter axon bundles, and genetics in BD. We performed a bibliographic search on PUBMED, using the search terms \u201cTBSS\u201d, \u201cgenetics\u201d, \u201cgenome\u201d, \u201cgenes\u201d, \u201cpolymorphism\u201d, \u201cbipolar disorder\u201d. Results Ten studies met these inclusion criteria. ANK3 and ZNF804A polymorphisms have shown the most consistent results, with the risk alleles showing abnormal white matter integrity in patients with BD. Limitations Current studies are limited by the investigation of single SNPs in small and chronically treated samples. Conclusions Most considered TBSS-DTI studies found associations between decreased white matter integrity and genetic risk variants. These results suggest an involvement of dysmyelination in the pathogenesis of BD. The combination of TBSS with genotyping can be powerful to unveil the role of white matter in BD, in conjunction with risk genes. Future DTI studies should combine TBSS and GWAS in large populations of drug-free or minimally treated patients with BD at the onset of the disease

Key factors in psychotherapy training: an analysis of trainers', trainees' and psychotherapists' points of view

The literature on clinical training lacks identifications of the factors that are most relevant in training programs; accordingly, the main aim of this work is to fill this research gap by assessing which factors that trainers, trainees and psychotherapists consider most relevant in psychotherapy training programs. A secondary aim is to identify whether these factors differ among trainers, trainees and psychotherapists. An ad hoc questionnaire was created and administered at 24 psychotherapy schools from 14 institutions; the sample included 641 trainees, 172 trainers and 218 psychotherapists of various theoretical orientations. The questionnaire included 63 items and used a 5-point Likert scale. An exploratory factor analysis was completed to identify the latent structure. The reliability of the dimensions was then checked. Finally, an analysis of variance and a multivariate analysis of variance were completed to achieve the study's aims. Four factors emerged from the study's results: trainers' relational characteristics, supervision, transmission of clinical know-how, and theoretical background and technical support. All these factors displayed acceptable reliability and internal consistency. Moreover, their relative rankings varied based on the participants' roles and theoretical backgrounds. This study's results indicate that the new instrument's psychometric qualities are acceptable. It thus could be used to develop a new approach to psychotherapy training, as this study's results regarding trainees' needs underline the differences between trainees' perceptions of those needs, as compared to trainers' and psychotherapists' perceptions

Twin MRI studies on genetic and environmental determinants of brain morphology and function in the early lifespan

Neurodevelopment represents a period of increased opportunity and vulnerability, during which a complex confluence of genetic and environmental factors influences brain growth trajectories, cognitive and mental health outcomes. Recently, magnetic resonance imaging (MRI) studies on twins have increased our knowledge of the extent to which genes, the environment and their interactions shape inter-individual brain variability. The present review draws from highly salient MRI studies in young twin samples to provide a robust assessment of the heritability of structural and functional brain changes during development. The available studies suggest that (as with many other traits), global brain morphology and network organization are highly heritable from early childhood to young adulthood. Conversely, genetic correlations among brain regions exhibit heterogeneous trajectories, and this heterogeneity reflects the progressive, experience-related increase in brain network complexity. Studies also support the key role of environment in mediating brain network differentiation via changes of genetic expression and hormonal levels. Thus, rest- and task-related functional brain circuits seem to result from a contextual and dynamic expression of heritability