The role of negative maternal affective states and infant temperament in early interactions between infants with cleft lip and their mothers

OBJECTIVES: The study examined the early interaction between mothers and their infants with cleft lip, assessing the role of maternal affective state and expressiveness and differences in infant temperament. METHODS: Mother-infant interactions were assessed in 25 2-month-old infants with cleft lip and 25 age-matched healthy infants. Self-report and behavioral observations were used to assess maternal depressive symptoms and expressions. Mothers rated infant temperament. RESULTS: Infants with cleft lip were less engaged and their mothers showed more difficulty in interaction than control group dyads. Mothers of infants with cleft lip displayed more negative affectivity, but did not report more self-rated depressive symptoms than control group mothers. No group differences were found in infant temperament. CONCLUSIONS: In order to support the mother's experience and facilitate her ongoing parental role, findings highlight the importance of identifying maternal negative affectivity during early interactions, even when they seem have little awareness of their depressive symptoms

Centrality in valued graphs: A measure of betweenness based on network flow

A new measure of centrality, C,, is introduced. It is based on the concept of network flows. While conceptually similar to Freeman’s original measure, Ca, the new measure differs from the original in two important ways. First, C, is defined for both valued and non-valued graphs. This makes C, applicable to a wider variety of network datasets. Second, the computation of C, is not based on geodesic paths as is C, but on all the independent paths between all pairs of points in the network

Early brain damage affects body schema and person perception abilities in children and adolescents with spastic diplegia

Early brain damage leading to cerebral palsy is associated to core motor impairments and also affects cognitive and social abilities. In particular, previous studies have documented specific alterations of perceptual body processing and motor cognition that are associated to unilateral motor deficits in hemiplegic patients. However, little is known about spastic diplegia (SpD), which is characterized by motorial deficits involving both sides of the body and is often associated to visuospatial, attentional, and social perception impairments. Here, we compared the performance of a sample of 30 children and adolescents with SpD (aged 7-18 years) and of a group of age-matched controls with typical development (TD) at two different tasks tapping on body representations. In the first task, we tested visual and motor imagery abilities as assessed, respectively, by the object-based mental rotation of letters and by the first-person transformations for whole-body stimuli. In the second task, we administered an inversion effect/composite illusion task to evaluate the use of configural/holistic processing of others' body. Additionally, we assessed social perception abilities in the SpD sample using the NEPSY-II battery. In line with previously reported visuospatial deficits, a general mental imagery impairment was found in SpD patients when they were engaged in both object-centered and first-person mental transformations. Nevertheless, a specific deficit in operating an own-body transformation emerged. As concerns body perception, while more basic configural processing (i.e., inversion effect) was spared, no evidence for holistic (i.e., composite illusion) body processing was found in the SpD group. NEPSY-II assessment revealed that SpD children were impaired in both the theory of mind and affect recognition subtests. Overall, these findings suggested that early brain lesions and biased embodied experience could affect higher-level motor cognition and perceptual body processing, thus pointing to a strict link between motor deficits, body schema alterations, and person processing difficulties

Characterizing Distances of Networks on the Tensor Manifold

At the core of understanding dynamical systems is the ability to maintain and control the systems behavior that includes notions of robustness, heterogeneity, or regime-shift detection. Recently, to explore such functional properties, a convenient representation has been to model such dynamical systems as a weighted graph consisting of a finite, but very large number of interacting agents. This said, there exists very limited relevant statistical theory that is able cope with real-life data, i.e., how does perform analysis and/or statistics over a family of networks as opposed to a specific network or network-to-network variation. Here, we are interested in the analysis of network families whereby each network represents a point on an underlying statistical manifold. To do so, we explore the Riemannian structure of the tensor manifold developed by Pennec previously applied to Diffusion Tensor Imaging (DTI) towards the problem of network analysis. In particular, while this note focuses on Pennec definition of geodesics amongst a family of networks, we show how it lays the foundation for future work for developing measures of network robustness for regime-shift detection. We conclude with experiments highlighting the proposed distance on synthetic networks and an application towards biological (stem-cell) systems.Comment: This paper is accepted at 8th International Conference on Complex Networks 201

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

Home-based cognitive training in pediatric patients with acquired brain injury: preliminary results on efficacy of a randomized clinical trial

Cognitive rehabilitation may compensate for cognitive deficits of children with acquired brain injury (ABI), capitalizing on the use-dependent plasticity of a developing brain. Remote computerized cognitive training (CCT) may be delivered to patients in ecological settings, ensuring rehabilitation continuity. This work evaluated cognitive and psychological adjustment outcomes of an 8-week multi-domain, home-based CCT (Lumosity Cognitive Training) in a sample of patients with ABI aged 11–16 years. Two groups of patients were engaged in five CCT sessions per week for eight weeks (40 sessions). According to a stepped-wedge research design, one group (Training-first Group) started the CCT immediately, whereas the other group (Waiting-first Group) started the CCT after a comparable time of waiting list. Changes after the training and after the waiting period were compared in the two groups. Both groups improved in visual-spatial working memory more after the training than after the waiting-list period. The Training-first group improved also in arithmetic calculation speed. Findings indicate that a multi-domain CCT can produce benefits in visual-spatial working memory, probably because, in accordance with previous research, computer games heavily tax visuo-spatial abilities. This suggests that the prolonged stimulation of the same cognitive ability may generate the greatest benefits in children with ABI

Gene Modulation by Peptide Nucleic Acids (PNAs) Targeting microRNAs (miRs)

Since non-viral gene therapy was developed and employed in different in vitro and in vivo experimental systems as an effective way to control and modify gene expression, RNA has been considered as a molecular target of great relevance (Li &Huang, 2008, López-Fraga et al., 2008). In combination with standard chemotherapy, the siRNA therapy can reduce the chemoresistance of certain cancers, demonstrating its potential for treating many malignant diseases. Examples of RNA sequences to be targeted for therapeutic applications are mRNAs coding oncoproteins or RNA coding anti-apoptotic proteins for the development of anti-cancer therapy. In the last years, progresses in molecular biology have allowed to identify many genes Coding for small non coding RNA molecules, microRNA (miRNAs or miRs), able to regulate gene expression at the translation level (Huang et al., 2008, Shrivastava & Shrivastava, 2008, Sahu et al. 2007, Orlacchio et al., 2007, Williams et al., 2008, Papagiannakopoulos & Kosik, 2008). Accordingly, an increasing number of reports associate the changed expression with specific phenotypes and even with pathological conditions (Garzon & Croce, 2008, Mascellani et al., 2008, Sontheimer & Carthew, 2005, Filipowicz et al., 2005, Alvarez-Garcia & Miska, 2005). Interestingly, microRNAs play a double role in cancer, behaving both as oncogenes or tumor suppressor genes. In general, miRs promoting cancer targets mRNA coding for tumor-suppression proteins, while microRNAs exhibiting tumor-suppression properties usually target mRNAs coding oncoproteins. MicroRNAs which have been demonstrated to play a crucial role in the initiation and progression of human cancer are defined as oncogenic miRNAs (oncomiRs) (Cho, 2007). The oncomiR expression profiling of human malignancies has also identified a number of diagnostic and prognostic cancer signals (Cho, 2007, Lowery et al., 2008). Moreover, microRNAs have been firmly demonstrated to be involved in cancer metastasis (metastamiRs). Examples of metastasis-promoting microRNAs are, miR-10b (Calin et al., 2006), miR-373 and - 520c (Woods et al., 2007), miR-21, -143 and -182 (Hayashita et al., 2005; Si et al., 2007; Zhu et al.,2007). Reviews on metastamiR has been recently published Hurst et al. (Hurst et al. 2009, Edmonds et al. 2009). Reviews on metastamiRs has been recently published by Hurst et al

Network analysis of a stakeholder community combatting illegal wildlife trade

The illegal wildlife trade has emerged as a growing and urgent environmental issue. Stakeholders involved in the efforts to curb wildlife trafficking include non- governmental organizations (NGOs), academia, and state government/enforcement bodies. The extent to which these stakeholders work and communicate amongst each other is fundamental to effectively combatting illicit trade. Using the United Kingdom as a case study, we conducted a mixed methods study using a social network analysis and stakeholder interviews to assess communication relationships in the counter wildlife trafficking community. NGOs consistently occupied 4 of the 5 most central positions in the generated networks, while academic institutions were routinely the converse, filling 4 of the 5 most peripheral positions. However, NGOs were also shown to be the least diverse in their communication practices, compared to the other stakeholder groups. Through semi- structured interviews, personal relationships were identified as the biggest key to functioning communication. Participant insights also showed that stakeholder-specific variables (e.g. ethical/confidentiality concerns), and competition and fundraising, can have a confounding effect on inter-communication. Evaluating communication networks and intra- stakeholder communication trends is essential to facilitate a more cohesive, productive, and efficient response to the challenges of combatting illegal wildlife trade

Multitask Learning on Graph Neural Networks: Learning Multiple Graph Centrality Measures with a Unified Network

The application of deep learning to symbolic domains remains an active research endeavour. Graph neural networks (GNN), consisting of trained neural modules which can be arranged in different topologies at run time, are sound alternatives to tackle relational problems which lend themselves to graph representations. In this paper, we show that GNNs are capable of multitask learning, which can be naturally enforced by training the model to refine a single set of multidimensional embeddings $\in \mathbb{R}^d$ and decode them into multiple outputs by connecting MLPs at the end of the pipeline. We demonstrate the multitask learning capability of the model in the relevant relational problem of estimating network centrality measures, focusing primarily on producing rankings based on these measures, i.e. is vertex $v_1$ more central than vertex $v_2$ given centrality $c$?. We then show that a GNN can be trained to develop a \emph{lingua franca} of vertex embeddings from which all relevant information about any of the trained centrality measures can be decoded. The proposed model achieves $89\%$ accuracy on a test dataset of random instances with up to 128 vertices and is shown to generalise to larger problem sizes. The model is also shown to obtain reasonable accuracy on a dataset of real world instances with up to 4k vertices, vastly surpassing the sizes of the largest instances with which the model was trained ($n=128$). Finally, we believe that our contributions attest to the potential of GNNs in symbolic domains in general and in relational learning in particular.Comment: Published at ICANN2019. 10 pages, 3 Figure

Omnivorousness in sport: The importance of social capital and networks

There has been for some time a significant and growing body of research around the relationship between sport and social capital. Similarly, within sociology there has been a corpus of work that has acknowledged the emergence of the omnivore–univore relationship. Surprisingly, relatively few studies examining sport and social capital have taken the omnivore–univore framework as a basis for understanding the relationship between sport and social capital. This gap in the sociology of sport literature and knowledge is rectified by this study that takes not Putnam, Coleman or Bourdieu, but Lin’s social network approach to social capital. The implications of this article are that researchers investigating sport and social capital need to understand more about how social networks and places for sport work to create social capital and, in particular, influence participating in sporting activities. The results indicate that social networks both facilitate and constrain sports participation; whilst family and friendship networks are central in active lifestyles, those who are less active have limited networks