Long-term neurodevelopmental and cardiovascular outcome after intrauterine transfusions for fetal anaemia: a review

Perinatal survival rates after intrauterine transfusions (IUT) for red cell alloimmunisation now exceed 90%, which demonstrates the safety and efficacy of one of the most successful procedures in fetal therapy. However, improved perinatal survival could lead to an increased number of children with long-term disabilities. The importance of long-term follow-up studies in fetal therapy lies in both the necessity of evaluation of antenatal management as well as in evidence-based preconceptional and prenatal counselling. This review describes the possible long-term cardiovascular and neurodevelopmental sequelae after IUT treatment for different indications including red cell alloimmunisation, parvovirus B19 infection, fetomaternal haemorrhage and twin anaemia-polycythaemia sequence. © 2013 John Wiley & Sons, Ltd.     

A revised calculation of the econometric factors α- and β for the Extended Exergy Accounting method

Extended Exergy Accounting (“EEA”) is a method to compute the space- and time integral of the primary exergy required to produce a good or a service: the extended exergy of a commodity measures its “embodied exergy”, including externalities (Labour, Capital and Environmental Costa). A crucial point of the method is the calculation of two econometric coefficients, commonly referred to as “α” and “β”,used to calculate the extended exergy equivalents of Labour and Capital respectively. In previous applications of the EEA method, these coefficients have been assigned approximate values estimated on the basis of global system considerations. In this paper, a novel procedure is described that leads to the calculation of “exact” values of both econometric coefficients, based on detailed exergy- and monetary balances of the Society to which the EEA is applied. It is shown that both α and β depend in a non-trivial way from the consumption patterns, the technological level and the life- and socio-economic standards of each Country. It is also shown that the values are substantially different for developed (OECD) and underdeveloped Countries, and representative samples of values are calculated and critically analysed. On the basis of these new model coefficients, the specific exergy equivalents of Labour (ee_L) and of Capital (ee_K) are calculated, and shown to differ from the values used in previous EEA calculations.     

An integrated air quality forecast system for a metropolitan area

Air quality forecasting is an important issue in environmental research, due to the effects that air pollutants have on population health. To deal with this topic, in this work an integrated modelling system has been developed to forecast daily maximum eight hours ozone concentrations and daily mean PM10 concentrations, up to two days in advance, over an urban area. The presented approach involves two steps. In the first step, artificial neural networks are identified and applied to get point-wise forecasting. In the second step, the forecasts obtained at the monitoring station locations are spatially interpolated all over the domain using the cokriging technique, which allows to improve the spatial interpolation in the absence of densely sampled data. The integrated modelling system has been then applied to a case study over Northern Italy, performing a validation over space and time for the year 2004 and analyzing if the limit values for the protection of human health set by the European Commission are respected. The presented approach represents a fast and reliable way to provide decision makers and the general public with air quality forecasting, and to support prevention and precautionary measures.     

Comparison of topological,empirical and optimization-based approaches for locating quality detection points in water distribution networks

Environmental Science and Pollution Research - The positioning of quality detection points as well as the frequency of sampling is a crucial aspect for the implementation of Water Safety Plans...     

A correlation study between multiple sclerosis and type 1 diabetes incidences and geochemical data in Europe

Complex multifactorial disorders usually arise in individuals genetically at risk in the presence of permissive environmental factors. For many of these diseases, predisposing gene variants are partly known while the identification of the environmental component is much more difficult. This study aims to investigate whether there are correlations between the incidence of two complex traits, multiple sclerosis and type 1 diabetes, and some chemical elements and compounds present in soils and stream sediments in Europe. Data were obtained from the published literature and analyzed by calculating the mean values of each element and of disease incidence for each Country, respectively, 17 for multiple sclerosis and 21 for type 1 diabetes. Correlation matrices and regression analyses were used in order to compare incidence data and geochemical data. R correlation index and significance were evaluated. The analyses performed in this study have revealed significant positive correlations between barium and sodium oxide on one hand and multiple sclerosis and diabetes incidences on the other hand that may suggest interactions to be evaluated between silicon-rich lithologies and/or marine environments. The negative correlations shown by cobalt, chromium and nickel (typical of silicon-poor environment), which in this case can be interpreted as protective effects against the two diseases onset, make the split between favorable and protective environments even more obvious. In conclusion, if other studies will confirm the involvement of the above elements and compounds in the etiology of these pathologies, then it will be possible to plan strategies to reduce the spread of these serious pandemics.     

Maternal effects on begging behaviour: an experimental demonstration of the effects of laying sequence, hatch order, nestling sex and brood size

Differential resource allocation by females across the laying sequence has been hypothesised as a mechanism through which females could either compensate nestlings that hatch last in asynchronous broods or promote brood reduction. In this study we artificially incubated eggs and cross-fostered offspring to manipulate nestlings’ position in the hatching order, to identify whether the competitive ability of nestlings is dependent on position in the laying sequence. In both control and experimentally reversed broods, first hatched chicks had a higher survival than last hatched siblings. Yet, nestlings that hatched from eggs laid in the second half of a clutch begged with a greater intensity than nestlings hatched from eggs laid in the first half of a clutch. In natural broods, the greater begging competitiveness of nestlings from later-laid eggs led to a moderation of sibling competition and these nestlings achieved the same body size and weight as nestlings from eggs laid in the first half of the clutch. The lack of a substantial difference in the size and condition of surviving nestlings in respect to laying order suggests that differential resource allocation across the egg-laying sequence partially compensates for hatching last in asynchronous broods and reduces the negative effects of the nestling size hierarchy. The effect of laying order, brood size and experimental treatment also differed for male and female nestlings. Our study highlights the need to be aware of the complex and subtle effects of nestling sex and laying sequence when investigating genetic and environmental influences on individual fitness.     

How to address data privacy concerns when using social media data in conservation science

Social media data are being increasingly used in conservation science to study human–nature interactions. User-generated content, such as images, video, text, and audio, and the associated metadata can be used to assess such interactions. A number of social media platforms provide free access to user-generated social media content. However, similar to any research involving people, scientific investigations based on social media data require compliance with highest standards of data privacy and data protection, even when data are publicly available. Should social media data be misused, the risks to individual users' privacy and well-being can be substantial. We investigated the legal basis for using social media data while ensuring data subjects’ rights through a case study based on the European Union's General Data Protection Regulation. The risks associated with using social media data in research include accidental and purposeful misidentification that has the potential to cause psychological or physical harm to an identified person. To collect, store, protect, share, and manage social media data in a way that prevents potential risks to users involved, one should minimize data, anonymize data, and follow strict data management procedure. Risk-based approaches, such as a data privacy impact assessment, can be used to identify and minimize privacy risks to social media users, to demonstrate accountability and to comply with data protection legislation. We recommend that conservation scientists carefully consider our recommendations in devising their research objectives so as to facilitate responsible use of social media data in conservation science research, for example, in conservation culturomics and investigations of illegal wildlife trade online.