Inhibition of de novo ceramide biosynthesis affects aging phenotype in an in vitro model of neuronal senescence.

Although aging is considered to be an unavoidable event, recent experimental evidence suggests that the process can be counteracted. Intracellular calcium (Ca2+i) dyshomeostasis, mitochondrial dysfunction, oxidative stress, and lipid dysregulation are critical factors that contribute to senescence-related processes. Ceramides, a pleiotropic class of sphingolipids, are important mediators of cellular senescence, but their role in neuronal aging is still largely unexplored. In this study, we investigated the effects of L-cycloserine (L-CS), an inhibitor of thede novoceramide biosynthesis, on the aging phenotype of cortical neurons cultured for 22 days, a setting employed as anin vitromodel of senescence. Our findings indicate that, compared to control cultures, 'aged' neurons display dysregulation of [Ca2+]ilevels, mitochondrial dysfunction, increased generation of reactive oxygen species (ROS), altered synaptic activity as well as the activation of neuronal death-related molecules. Treatment with L-CS positively affected the senescent phenotype, a result associated with recovery of neuronal [Ca2+]isignaling and reduction of mitochondrial dysfunction and ROS generation. The results suggest that thede novoceramide biosynthesis represents a critical intermediate in the molecular and functional cascade leading to neuronal senescence and identify ceramide biosynthesis inhibitors as promising pharmacological tools to decrease age-related neuronal dysfunctions

The pharmacological perturbation of brain zinc impairs BDNF-related signaling and the cognitive performances of young mice.

Zinc (Zn2+) is a pleiotropic modulator of the neuronal and brain activity. The disruption of intraneuronal Zn2+ levels triggers neurotoxic processes and affects neuronal functioning. In this study, we investigated how the pharmacological modulation of brain Zn2+ affects synaptic plasticity and cognition in wild-type mice. To manipulate brain Zn2+ levels, we employed the Zn2+ (and copper) chelator 5-chloro-7-iodo-8-hydroxyquinoline (clioquinol, CQ). CQ was administered for two weeks to 2.5-month-old (m.o.) mice, and effects studied on BDNF-related signaling, metalloproteinase activity as well as learning and memory performances. CQ treatment was found to negatively affect short- and long-term memory performances. The CQ-driven perturbation of brain Zn2+ was found to reduce levels of BDNF, synaptic plasticity-related proteins and dendritic spine density in vivo. Our study highlights the importance of choosing "when", "where", and "how much" in the modulation of brain Zn2+ levels. Our findings confirm the importance of targeting Zn2+ as a therapeutic approach against neurodegenerative conditions but, at the same time, underscore the potential drawbacks of reducing brain Zn2+ availability upon the early stages of development

Food habits, Life style, Genetic background in tumour initiation and progression of Reproductive system

The relationship between diet and health is really engaging, it has been showed that modifications in dietary intake and the benefits of the Mediterranean diet, can importantly increase life expectancy, reducing the risk of chronic disease and improve quality of life. In this way, several studies assigned a highest reduction in tumor incidence to monosaturated and saturated lipids present in vegetables, such olive oil. On these basis, this study will be focused on the comprehension and understanding of initiation and progression phases linked to environmental stressors and food habits in the tumours of the reproductive system (breast and ovarian cancer). Recently it has been described the potential effect of the olive tree (Olea europaea) leaves, oil and fruits to inhibit proliferation and to induce apoptosis in different cancer cell lines. The phenolic fraction of Olive extract becomes specially interesting, including a polyphenol called Oleuropein (OL) present at higher levels in olives and leaves- as well as its hydrolysis metabolite, Hydroxytyrosol (HT). Taking this background into account, we have focused our research in the analysis of Olive leaf extracts with a high content in OL (48%) as a potential cell viability reducing agent on a malignant triple negative breast cancer cell line, MDA-MB- 231, which is highly aggressive. On this model, cell viability was measured with a MTS assay 24 and 48 h after the treatment with the Olive extract. The preliminary results seem to indicate that this extract at high concentrations (200-400µg/mL) determines a reduction in the MDA- MB-231 cell viability

Cognitive Developmental Differences in Source Monitoring

PsychologyMaster of Arts (M.A.

A time-domain control signal detection technique for OFDM

Transmission of system-critical control information plays a key role in efficient management of limited wireless network resources and successful reception of payload data information. This paper uses an orthogonal frequency division multiplexing (OFDM) architecture to investigate the detection performance of a time-domain approach used to detect deterministic control signalling information. It considers a type of control information chosen from a finite set of information, which is known at both transmitting and receiving wireless terminals. Unlike the maximum likelihood (ML) estimation method, which is often used, the time-domain detection technique requires no channel estimation and no pilots as it uses a form of time-domain correlation as the means of detection. Results show that when compared with the ML method, the time-domain approach improves detection performance even in the presence of synchronisation error caused by carrier frequency offset

Emergence of scale-free leadership structure in social recommender systems

The study of the organization of social networks is important for understanding of opinion formation, rumor spreading, and the emergence of trends and fashion. This paper reports empirical analysis of networks extracted from four leading sites with social functionality (Delicious, Flickr, Twitter and YouTube) and shows that they all display a scale-free leadership structure. To reproduce this feature, we propose an adaptive network model driven by social recommending. Artificial agent-based simulations of this model highlight a "good get richer" mechanism where users with broad interests and good judgments are likely to become popular leaders for the others. Simulations also indicate that the studied social recommendation mechanism can gradually improve the user experience by adapting to tastes of its users. Finally we outline implications for real online resource-sharing systems

Tag-Aware Recommender Systems: A State-of-the-art Survey

In the past decade, Social Tagging Systems have attracted increasing attention from both physical and computer science communities. Besides the underlying structure and dynamics of tagging systems, many efforts have been addressed to unify tagging information to reveal user behaviors and preferences, extract the latent semantic relations among items, make recommendations, and so on. Specifically, this article summarizes recent progress about tag-aware recommender systems, emphasizing on the contributions from three mainstream perspectives and approaches: network-based methods, tensor-based methods, and the topic-based methods. Finally, we outline some other tag-related works and future challenges of tag-aware recommendation algorithms.Comment: 19 pages, 3 figure

Meta-validation of bipartite network projections

Monopartite projections of bipartite networks are useful tools for modeling indirect interactions in complex systems. The standard approach to identify significant links is statistical validation using a suitable null network model, such as the popular configuration model (CM) that constrains node degrees and randomizes everything else. However different CM formulations exist, depending on how the constraints are imposed and for which sets of nodes. Here we systematically investigate the application of these formulations in validating the same network, showing that they lead to different results even when the same significance threshold is used. Instead a much better agreement is obtained for the same density of validated links. We thus propose a meta-validation approach that allows to identify model-specific significance thresholds for which the signal is strongest, and at the same time to obtain results independent of the way in which the null hypothesis is formulated. We illustrate this procedure using data on scientific production of world countries.The configuration model, in its various formulations, is a widely used null model for statistical validation of bipartite network projections. Here, the authors show that different formulations might bring to very different results, and propose a meta-validation approach that allows to identify model-specific significance thresholds while remaining null-model independent