PDNAsite:identification of DNA-binding site from protein sequence by incorporating spatial and sequence context

Protein-DNA interactions are involved in many fundamental biological processes essential for cellular function. Most of the existing computational approaches employed only the sequence context of the target residue for its prediction. In the present study, for each target residue, we applied both the spatial context and the sequence context to construct the feature space. Subsequently, Latent Semantic Analysis (LSA) was applied to remove the redundancies in the feature space. Finally, a predictor (PDNAsite) was developed through the integration of the support vector machines (SVM) classifier and ensemble learning. Results on the PDNA-62 and the PDNA-224 datasets demonstrate that features extracted from spatial context provide more information than those from sequence context and the combination of them gives more performance gain. An analysis of the number of binding sites in the spatial context of the target site indicates that the interactions between binding sites next to each other are important for protein-DNA recognition and their binding ability. The comparison between our proposed PDNAsite method and the existing methods indicate that PDNAsite outperforms most of the existing methods and is a useful tool for DNA-binding site identification. A web-server of our predictor (http://hlt.hitsz.edu.cn:8080/PDNAsite/) is made available for free public accessible to the biological research community

The Immune System in Stroke

Stroke represents an unresolved challenge for both developed and developing countries and has a huge socio-economic impact. Although considerable effort has been made to limit stroke incidence and improve outcome, strategies aimed at protecting injured neurons in the brain have all failed. This failure is likely to be due to both the incompleteness of modelling the disease and its causes in experimental research, and also the lack of understanding of how systemic mechanisms lead to an acute cerebrovascular event or contribute to outcome. Inflammation has been implicated in all forms of brain injury and it is now clear that immune mechanisms profoundly influence (and are responsible for the development of) risk and causation of stroke, and the outcome following the onset of cerebral ischemia. Until very recently, systemic inflammatory mechanisms, with respect to common comorbidities in stroke, have largely been ignored in experimental studies. The main aim is therefore to understand interactions between the immune system and brain injury in order to develop novel therapeutic approaches. Recent data from clinical and experimental research clearly show that systemic inflammatory diseases -such as atherosclerosis, obesity, diabetes or infection - similar to stress and advanced age, are associated with dysregulated immune responses which can profoundly contribute to cerebrovascular inflammation and injury in the central nervous system. In this review, we summarize recent advances in the field of inflammation and stroke, focusing on the challenges of translation between pre-clinical and clinical studies, and potential anti-inflammatory/immunomodulatory therapeutic approaches

The role of Mediterranean mesoscale eddies on the climate of the Euro-Mediterranean region

Within the CIRCE (Climate Change and Impact Research: The Mediterranean Environment) EU Project, substantial efforts were devoted to enhance the representation of the oceanic system in the Mediterranean region. This was achieved by developing coupled general circulation models with ocean components which either explicitly resolve, or simply permit, mesoscale circulation features. The inclusion of the eddy variability tail in the spectrum of the processes resolved by the modelled system represents a particularly relevant step forward with respect to the previous CMIP3 generation of climate models , as these were systematically based on coarse resolution ocean components, leading in turn to an extremely rough representation of the Mediterranean Sea sub-system. In this study the role of mesoscale oceanic features on the air-sea interactions over the Mediterranean region was analysed, in the context of one of the CIRCE ensemble of climate models. To this aim, two different simulations of the 20th Century climate, performed with two distinct configurations of the CMCC coupled general circulation model featuring radically different horizontal resolutions in the Mediterranean Sea domain, were compared. This comparison highlights the implications deriving from the inclusion of energetic ocean mesoscale structures in the variability spectrum of the coupled ocean-atmosphere system and points to the need for high-resolution ocean components in the development of next generation climate model