Calcineurin expression and activity is regulated by the intracellular redox status and under hypertension in human neutrophils

Calcineurin (protein phosphatase 2B) (CN) comprises a family of serine/threonine phosphatases that play a pivotal role in signal transduction cascades in a variety of cells, including neutrophils. Angiotensin II (Ang II) increases both activity and de novo synthesis of CN in human neutrophils. This study focuses on the role that intracellular redox status plays in the induction of CN activity by Ang II. Both de novo synthesis of CN and activity increase promoted by Ang II were downregulated when cells were treated with l-buthionine-(S,R)-sulfoximine, an inhibitor of synthesis of the antioxidant glutathione. We have also investigated the effect of pyrrolidine dithiocarbamate and phenazine methosulfate, which are antioxidant and oxidant compounds, respectively, and concluded that the intracellular redox status of neutrophils is highly critical for Ang II-induced increase of CN expression and activity. Results obtained in neutrophils from hypertensive patients were very similar to those obtained in these cells on treatment with Ang II. We have also addressed the possible functional implication of CN activation in the development of hypertension. Present findings indicate that downregulation of hemoxygenase-1 expression in neutrophils from hypertensive subjects is likely mediated by CN, which acts by hindering translocation to the nucleus of the transcription factor NRF2. These data support and extend our previous results and those from other authors on modulation of CN expression and activity levels by the intracellular redox status.

The Conservation of our Built Heritage, in Particular Statues in Aberdeen, Evaluated Through a Social and Historical Context and Their Impact, Through the Use of 3D Scanning

Cultural heritage sites all over the world are at risk due to aggressive urban expansion, development, wars and general obsolescence. Not all objects are recorded in detail although they may have social and historical significance. For example more emphasis is placed on the recording of castles and palaces than on crofters’ cottages or tenement blocks, although their history can be just as rich. This paper will investigate the historic fabric of Aberdeen through the use of digital scanning, supported by a range of media including old photographs and paintings. Dissemination of social heritage through visualisations will be explored and how this can aid the understanding of space within the city or specific area. Focus will be given to the major statues/monuments within the context of the city centre, exploring their importance in their environment. In addition studying why many have been re-located away from their original site, the reasons why, and how we have perhaps lost some of the social and historical importance of why that monument was first located there. It will be argued that Digital Media could be utilised for much more than re-creation and re-presentation of physical entities. Digital scanning, in association with visualisation tools, is used to capture the essence of both the cultural heritage and the society that created or used the sites in association with visualisation tools and in some way re-enacting the original importance placed upon the monument in its original location, through adoption of BIM Heritage.

A Novel Prediction Method for Early Recognition of Global Human Behaviour in Image Sequences

Human behaviour recognition has been, and still remains, a challenging problem that involves different areas of computational intelligence. The automated understanding of people activities from video sequences is an open research topic in which the computer vision and pattern recognition areas have made big efforts. In this paper, the problem is studied from a prediction point of view. We propose a novel method able to early detect behaviour using a small portion of the input, in addition to the capabilities of it to predict behaviour from new inputs. Specifically, we propose a predictive method based on a simple representation of trajectories of a person in the scene which allows a high level understanding of the global human behaviour. The representation of the trajectory is used as a descriptor of the activity of the individual. The descriptors are used as a cue of a classification stage for pattern recognition purposes. Classifiers are trained using the trajectory representation of the complete sequence. However, partial sequences are processed to evaluate the early prediction capabilities having a specific observation time of the scene. The experiments have been carried out using the three different dataset of the CAVIAR database taken into account the behaviour of an individual. Additionally, different classic classifiers have been used for experimentation in order to evaluate the robustness of the proposal. Results confirm the high accuracy of the proposal on the early recognition of people behaviours.

Football Video Annotation Based on Player Motion Recognition Using Enhanced Entropy

This paper presents a semi-parametric Algorithm for parsing football video structures. The approach works on a two interleaved based process that closely collaborate towards a common goal. The core part of the proposed method focus perform a fast automatic football video annotation by looking at the enhance entropy variance within a series of shot frames. The entropy is extracted on the Hue parameter from the HSV color system, not as a global feature but in spatial domain to identify regions within a shot that will characterize a certain activity within the shot period. The second part of the algorithm works towards the identification of dominant color regions that could represent players and playfield for further activity recognition. Experimental Results shows that the proposed football video segmentation algorithm performs with high accuracy.