Adolescent Loneliness and Social Skills:Agreement and Discrepancies Between Self-, Meta-, and Peer-Evaluations

Contains fulltext : 160961.pdf (publisher's version ) (Open Access)Lonely adolescents report that they have poor social skills, but it is unknown whether this is due to an accurate perception of a social skills deficit, or a biased negative perception. This is an important distinction, as actual social skills deficits require different treatments than biased negative perceptions. In this study, we compared self-reported social skills evaluations with peer-reported social skills and meta-evaluations of social skills (i.e., adolescents' perceptions of how they believe their classmates evaluate them). Based on the social skills view, we expected negative relations between loneliness and these three forms of social skills evaluations. Based on the bias view, we expected lonely adolescents to have more negative self- and meta-evaluations compared to peer-evaluations of social skills. Participants were 1342 adolescents (48.64 % male, M age = 13.95, SD = .54). All classmates rated each other in a round-robin design to obtain peer-evaluations. Self- and meta-evaluations were obtained using self-reports. Data were analyzed using polynomial regression analyses and response surface modeling. The results indicated that, when self-, peer- and meta-evaluations were similar, a greater sense of loneliness was related to poorer social skills. Loneliness was also related to larger discrepancies between self- and peer-evaluations of loneliness, but not related to the direction of these discrepancies. Thus, for some lonely adolescents, loneliness may be related to an actual social skills deficit, whereas for others a biased negative perception of one's own social skills or a mismatch with the environment may be related to their loneliness. This implies that different mechanisms may underlie loneliness, which has implications for interventions.11 p

Multiview classification and dimensionality reduction of scalp and intracranial EEG data through tensor factorisation

Electroencephalography (EEG) signals arise as a mixture of various neural processes that occur in different spatial, frequency and temporal locations. In classification paradigms, algorithms are developed that can distinguish between these processes. In this work, we apply tensor factorisation to a set of EEG data from a group of epileptic patients and factorise the data into three modes; space, time and frequency with each mode containing a number of components or signatures. We train separate classifiers on various feature sets corresponding to complementary combinations of those modes and components and test the classification accuracy of each set. The relative influence on the classification accuracy of the respective spatial, temporal or frequency signatures can then be analysed and useful interpretations can be made. Additionaly, we show that through tensor factorisation we can perform dimensionality reduction by evaluating the classification performance with regards to the number mode components and by rejecting components with insignificant contribution to the classification accuracy

A new class of glycomimetic drugs to prevent free fatty acid-induced endothelial dysfunction

Background: Carbohydrates play a major role in cell signaling in many biological processes. We have developed a set of glycomimetic drugs that mimic the structure of carbohydrates and represent a novel source of therapeutics for endothelial dysfunction, a key initiating factor in cardiovascular complications. Purpose: Our objective was to determine the protective effects of small molecule glycomimetics against free fatty acid­induced endothelial dysfunction, focusing on nitric oxide (NO) and oxidative stress pathways. Methods: Four glycomimetics were synthesized by the stepwise transformation of 2,5­dihydroxybenzoic acid to a range of 2,5­substituted benzoic acid derivatives, incorporating the key sulfate groups to mimic the interactions of heparan sulfate. Endothelial function was assessed using acetylcholine­induced, endotheliumdependent relaxation in mouse thoracic aortic rings using wire myography. Human umbilical vein endothelial cell (HUVEC) behavior was evaluated in the presence or absence of the free fatty acid, palmitate, with or without glycomimetics (1µM). DAF­2 and H2DCF­DA assays were used to determine nitric oxide (NO) and reactive oxygen species (ROS) production, respectively. Lipid peroxidation colorimetric and antioxidant enzyme activity assays were also carried out. RT­PCR and western blotting were utilized to measure Akt, eNOS, Nrf­2, NQO­1 and HO­1 expression. Results: Ex vivo endothelium­dependent relaxation was significantly improved by the glycomimetics under palmitate­induced oxidative stress. In vitro studies showed that the glycomimetics protected HUVECs against the palmitate­induced oxidative stress and enhanced NO production. We demonstrate that the protective effects of pre­incubation with glycomimetics occurred via upregulation of Akt/eNOS signaling, activation of the Nrf2/ARE pathway, and suppression of ROS­induced lipid peroxidation. Conclusion: We have developed a novel set of small molecule glycomimetics that protect against free fatty acidinduced endothelial dysfunction and thus, represent a new category of therapeutic drugs to target endothelial damage, the first line of defense against cardiovascular disease