Cardiac Progenitor Cells from Stem Cells: Learning from Genetics and Biomaterials

Cardiac Progenitor Cells (CPCs) show great potential as a cell resource for restoring cardiac function in patients affected by heart disease or heart failure. CPCs are proliferative and committed to cardiac fate, capable of generating cells of all the cardiac lineages. These cells offer a significant shift in paradigm over the use of human induced pluripotent stem cell (iPSC)-derived cardiomyocytes owing to the latter's inability to recapitulate mature features of a native myocardium, limiting their translational applications. The iPSCs and direct reprogramming of somatic cells have been attempted to produce CPCs and, in this process, a variety of chemical and/or genetic factors have been evaluated for their ability to generate, expand, and maintain CPCs in vitro. However, the precise stoichiometry and spatiotemporal activity of these factors and the genetic interplay during embryonic CPC development remain challenging to reproduce in culture, in terms of efficiency, numbers, and translational potential. Recent advances in biomaterials to mimic the native cardiac microenvironment have shown promise to influence CPC regenerative functions, while being capable of integrating with host tissue. This review highlights recent developments and limitations in the generation and use of CPCs from stem cells, and the trends that influence the direction of research to promote better application of CPCs

Extended Granger causality: a new tool to identify the structure of physiological networks

Granger causality (GC) is a very popular tool for assessing the presence of directional interactions between two time series of a multivariate data set. In its original formulation, GC does not account for zero-lag correlations possibly existing between the observed time series. In the present study we compare the GC with a novel measure, termed extended GC (eGC), able to capture instantaneous causal relationships. We present a two-step procedure for the practical estimation of eGC based on first detecting the existence of zero-lag correlations, and then assigning them to one of the two possible causal directions using pairwise measures of non-Gaussianity. The proposed method was validated in a simulation study, showing that the estimation procedure based on the extended representation overcomes the limits of the classic computation of GC, correctly detecting the presence and direction of zero-lag interactions and providing a meaningful causal interpretation based on the eGC. Then, GC and eGC were computed on the physiological variability series of heart period (HP), mean arterial pressure (AP) and cerebral blood flow velocity (FV) in ten subjects with postural related syncope (PRS), during different epochs of an head-up tilt test protocol. We found that both measures reflect the baroreflex impairment and the loss of cerebral autoregulation during pre-syncope. Furthermore, eGC analysis suggests that fast, within-beat effects between AP and FV variability contribute substantially to the mutual regulation of these physiological variables, and may play an important role in the impairment of cerebrovascular regulation associated with PRS

Mutual information-based feature selection for low-cost BCIs based on motor imagery

In the present study a feature selection algorithm based on mutual information (MI) was applied to electro-encephalographic (EEG) data acquired during three different motor imagery tasks from two dataset: Dataset I from BCI Competition IV including full scalp recordings from four subjects, and new data recorded from three subjects using the popular low-cost Emotiv EPOC EEG headset. The aim was to evaluate optimal channels and band-power (BP) features for motor imagery tasks discrimination, in order to assess the feasibility of a portable low-cost motor imagery based Brain-Computer Interface (BCI) system. The minimal sub set of features most relevant to task description and less redundant to each other was determined, and the corresponding classification accuracy was assessed offline employing linear support vector machine (SVM) in a 10-fold cross validation scheme. The analysis was performed: (a) on the original full Dataset I from BCI competition IV, (b) on a restricted channels set from Dataset I corresponding to available Emotiv EPOC electrodes locations, and (c) on data recorded with the EPOC system. Results from (a) showed that an offline classification accuracy above 80% can be reached using only 5 features. Limiting the analysis to EPOC channels caused a decrease of classification accuracy, although it still remained above chance level, both for data from (b) and (c). A top accuracy of 70% was achieved using 2 optimal features. These results encourage further research towards the development of portable low cost motor imagery-based BCI systems

Computer Aided Rehabilitation of Water Networks (CARE-W), EU 5 Framework Program (contract EVK1-CT-2000-00053)

The challenges for urban water distribution have a huge financial dimension. Although they do what they can, many cities and countries do not have the economic capability cope with their problems. They are therefore chasing international funds such as EU structural funds, World Bank etc. This situation is a challenge regarding the fulfilment of the UN Millennium goals for water. Also in the highest developed countries in financial terms the network ageing is considered as a major challenge into 21 century, and sustainable levels of renovation and corresponding decision criteria is under discussion. Also in these countries the willingness to invest in networks is probably less than the actual need. A minimum ambition should be not to expel the financial burden of water network management to our children and grandchildren generations, and it is the responsibility of researchers to demonstrate consequences of to-days practises. The contribution of research community can be very important to cope with the problems, by demonstrating the best ways to approach the situation, new technologies and optimization techniques. These approaches can optimise the necessary expenditure of resources to improve the urban water situation for the less favorized regions. This is the background for the extensive joint efforts that has been carried out by 16 research centres and 20 cities Europe-wide and also including Australia, namely the CARE-W project. Intermediate results have been presented in several international conferences, including the IWA World Congresses in Paris, Hamburg, Melbourne and Marrakech. CARE-W is now finished as EU research projects, but it continue swith application and implementation world-wide. The main goals for CARE-W have been to support cities in achieving the right urban water rehabilitation project using the right technology at the right time. The research team had as its vision to support a move from re-active approach to the networks to a pro-active approach. This means leaving the strategy of repairing damages to avoid the damages by preventive rehabilitation, in other words to move from crisis handling to risk based network management. Avoiding damages means saving money. On the other side and there will be a risk of wrong selection of projects and waste of investment capital. To avoid this, better knowledge about the network performance is needed. This can be obtained by a systematic analysis of the relevant factors of network performance based on a systematic collection and processing of urban network information. The information may need to be more extensive than practise in cities, but the main idea is to make the data collection and processing more intelligent. The network manager of CARE-W acts as the operating system and connect tools to GIS platform and databases. It is also managing the data flow (input and results) between the tools. The tools of the system are summarized as follows: Objective 1: Status, trends, investments, customer related performance: PI tool on investment and condition for drinking water systems; Objective 2: Failure forecasting: Tool based on failure history (breaks, leaks) analyzed by stochastic method (Proportional Hazard model); Objective 3: Hydraulic network and hydraulic reliability model (consequences when pipe stop working); Objective 4: Socio-economic impact (impact to customer) : Integrated in ranking methodology Objective 5: Long-term investment strategies: Based on life distribution statistics and service life expectation; Objective 6: Selection and ranking of projects: Multi-criteria analysis technique based on weighting (Electre tri). CARE-W is now being implemented in many cities in Europe and abroad; it is used for validating existing or developing new master plans and in the daily management of the urban water