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Hereditary angioedema (HAE) is a genetic disorder that manifests as recurrent angioedema attacks, most frequently due to absent or reduced C1 inhibitor (C1INH) activity. C1INH is a crucial regulator of enzymatic cascades in the complement, fibrinolytic, and contact systems. Inter-α-trypsin inhibitor heavy chain 4 (ITIH4) is an abundant plasma protease inhibitor that can inhibit enzymes in the proteolytic pathways associated with HAE. Nothing is known about its role in HAE. We investigated ITIH4 activation in HAE, establishing it as a potential biomarker, and explored its involvement in HAE-associated proteolytic pathways. Specific immunoassays for noncleaved ITIH4 (intact ITIH4) and an assay detecting both intact and cleaved ITIH4 (total ITIH4) were developed. We initially tested serum samples from HAE patients (n = 20), angiotensin-converting enzyme inhibitor–induced edema patients (ACEI) (n = 20), and patients with HAE of unknown cause (HAE-UNK) (n = 20). Validation involved an extended cohort of 80 HAE patients (60 with HAE-C1INH type 1, 20 with HAE-C1INH type 2), including samples taken during attack and quiescent disease periods, as well as samples from 100 healthy controls. In 63% of HAE patients, intact ITIH4 assay showed lower signals than total ITIH4 assay. This difference was not observed in ACEI and HAE-UNK patients. Western blot analysis confirmed cleaved ITIH4 with low intact ITIH4 samples. In serum samples lacking intact endogenous ITIH4, we observed immediate cleavage of added recombinant ITIH4, suggesting continuous enzymatic activity in the serum. Confirmatory HAE cohort analysis revealed significantly lower intact ITIH4 levels in both type 1 and type 2 HAE patients compared to controls, with consistently low intact/total ITIH4 ratios during clinical HAE attacks. The disease-specific low intact ITIH4 levels highlight its unique nature in HAE. ITIH4 may exhibit compensatory mechanisms in HAE, suggesting its utility as a diagnostic and prognostic biomarker. The variations during quiescent and active disease periods raise intriguing questions about the dynamics of proteolytic pathways in HAE. [ABSTRACT FROM AUTHOR]

• There is a pressing need for water reuse where scarcity is not forcing the issue. • Stronger foundations for reuse in water rich contexts are urgently needed. • Environmental sustainability arguments are key to expanding reuse everywhere. The wealth of water reuse research in scarcity and/or rapid urbanisation contexts has underpinned significant change in many relatively water scarce contexts. Less progress has been achieved in water rich contexts; a fact illustrated by the lack of change on the ground. The Climate Emergency demands that all municipalities urgently contribute to more efficient resource management of water. Consequently, to advance municipal scale reuse projects in locations where scarcity is not forcing the issue, for example Scotland, there is a need to predicate water reuse on different drivers, specifically climate change and the circular economy. Moreover, greater contextual sensitivity needs to be applied when exploring barriers to reuse to more critically exploit opportunities, for example avenues to reform complex regulatory frameworks, different contingencies around trust, and different potential degrees of the yuck factor. To achieve this, new initiatives need to be urgently undertaken to consider the barriers to reuse that will not be swept aside by the imperative of scarcity. The notion of a yum factor, whereby positive sentiments are nurtured to combat instinctive repugnance, coined as yuck by the bioethicist Arthur Caplan, is advanced as a strategic objective to promote more rapid expansion of municipal scale reuse. [Display omitted] [ABSTRACT FROM AUTHOR]

Background Lectin pathway proteases activate coagulation and may theoretically play a role in the increased thrombosis risk in cancer, which is especially high during surgery. Aims To investigate lectin pathway proteins during lung cancer surgery, the influence of low molecular weight heparin (LMWH) on lectin pathway proteins, and correlations between lectin pathway proteins and coagulation. Methods Fifty lung cancer patients undergoing video-assisted thoracoscopic surgery lobectomy were randomised to LMWH, n  = 26, or no anticoagulant (control), n  = 24. Pre-, intra- and postoperative lectin pathway protein concentrations (mannose-binding lectin (MBL), H– and M-ficolin, collectin liver-1, MBL-associated serine protease (MASP)-1, -2 and -3, MBL-associated proteins MAp44 and MAp19) were assessed using a time-resolved immunofluorometric assay, and fibrinogen, fibrin d-dimer, and thrombin generation were analysed. Results For all proteins except MASP-1, concentrations decreased during surgery in both groups; most markedly M-ficolin which decreased 49% (median: 2836 [quartiles:2297–3505] to 1424 [1187–2199] ng/ml) (LMWH group) and 43% (2974 [2539–3510] to 1685 [1391–2076] ng/ml) (control group), while MBL decreased 12% (1936 [823–2801] to 1702 [676–2830] ng/ml) (LMWH) and 23% (1526 [250–2412] to 1175 [229–1947]) (controls). No differences in postoperative change were observed between groups except for MAp19 ( p  = 0.03) which decreased 9% (401 [337–467] to 364 [288–416] ng/ml) (LMWH) vs 28% (370 [272–468] to 268 [212–379] ng/ml) (controls). No correlation was found between lectin pathway proteins and coagulation ( r  = −0.23–0.28, p  > 0.06) except for M-ficolin and fibrinogen ( r  = 0.29–0.36, p  = 0.01–0.04). Conclusion Lectin pathway proteins were influenced by surgery but not by LMWH. No consistent correlation was found between lectin pathway proteins and coagulation. [ABSTRACT FROM AUTHOR]

A generalised quantitative risk assessment (QRA) is developed to assess the potential harm to human health resulting from irrigation with reclaimed water. The QRA is conducted as a backward calculation starting from a pre-defined acceptable risk level at the receptor point (defined as an annual infection risk of 10 −4 for pathogens and by reference doses (RfD) for chemical hazards) and results in an estimate of the corresponding acceptable concentration levels of the given hazards in the effluent. In this way the QRA is designed to inform the level of water treatment required to achieve an acceptable risk level and help establish reclaimed water quality standards. The QRA considers the exposure of human receptors to microbial and chemical hazards in the effluent through various exposure pathways and routes depending on the specific irrigation scenario. By considering multiple pathways and routes, a number of key aspects relevant to estimating human exposure to recycled water can be accounted for, including irrigation and crop handling practices (e.g., non-edible vs edible, spray vs. drip, withholding time) and volumes consumed (directly vs indirectly). The QRA relies on a large number of inputs, many of which were found to be highly uncertain. A possibilistic approach, based on fuzzy set theory, was used to propagate the uncertain input values through the QRA model to estimate the possible range of hazard concentrations that are deemed acceptable/safe for reclaimed water irrigation. Two scenarios were considered: amenity irrigation and irrigation of ready-to-eat food crops, and calculations were carried out for six example hazards (norovirus, Cryptosporidium , cadmium, lead, PCB118 and naphthalene) and using UK-specific input values. The human health risks associated with using reclaimed water for amenity irrigation were overall deemed low, i.e. the calculated acceptable concentration levels for most of the selected hazards were generally far greater than levels typically measured in effluent from wastewater treatment plants; however the predicted acceptable concentration levels for norovirus and Cryptosporidium suggested that disinfection by UV may be required before use. It was found that stricter concentration standards were required for hazards that are more strongly bound to soil and/or are more toxic/infectious. It was also found that measures that reduce the amount of effluent directly ingested by the receptor would significantly reduce the risks (by up to 2 orders of magnitude for the two pathogens). The results for the food crop irrigation scenario showed that stricter concentration standards are required to ensure the effluent is safe to use. For pathogens, the dominant exposure route was found to be ingestion of effluent captured on the surface of the crops indicating that risks could be significantly reduced by restricting irrigation to the non-edible parts of the crop. The results also showed that the exposure to some organic compounds and heavy metals through plant uptake and attached soil particles could be high and possibly pose unacceptable risk to human health. For both scenarios, we show that the predicted acceptable concentration levels are associated with large uncertainty and discuss the implications this has for defining quality standards and how the uncertainty can be reduced. [ABSTRACT FROM AUTHOR]

In many agricultural catchments of Europe and North America, pesticides occur at generally low concentrations with significant temporal variation. This poses several challenges for both monitoring and understanding ecological risks/impacts of these chemicals. This study aimed to compare the performance of passive and spot sampling strategies given the constraints of typical regulatory monitoring. Nine pesticides were investigated in a river currently undergoing regulatory monitoring (River Ugie, Scotland). Within this regulatory framework, spot and passive sampling were undertaken to understand spatiotemporal occurrence, mass loads and ecological risks. All the target pesticides were detected in water by both sampling strategies. Chlorotoluron was observed to be the dominant pesticide by both spot (maximum: 111.8 ng/l, mean: 9.35 ng/l) and passive sampling (maximum: 39.24 ng/l, mean: 4.76 ng/l). The annual pesticide loads were estimated to be 2735 g and 1837 g based on the spot and passive sampling data, respectively. The spatiotemporal trend suggested that agricultural activities were the primary source of the compounds with variability in loads explained in large by timing of pesticide applications and rainfall. The risk assessment showed chlorotoluron and chlorpyrifos posed the highest ecological risks with 23% of the chlorotoluron spot samples and 36% of the chlorpyrifos passive samples resulting in a Risk Quotient greater than 0.1. This suggests that mitigation measures might need to be taken to reduce the input of pesticides into the river. The overall comparison of the two sampling strategies supported the hypothesis that passive sampling tends to integrate the contaminants over a period of exposure and allows quantification of contamination at low concentration. The results suggested that within a regulatory monitoring context passive sampling was more suitable for flux estimation and risk assessment of trace contaminants which cannot be diagnosed by spot sampling and for determining if long-term average concentrations comply with specified standards. [ABSTRACT FROM AUTHOR]

Multi-criteria analyses (MCAs) are often applied to assess and compare the sustainability of different renewable energy technologies or energy plans with the aim to provide decision-support for choosing the most sustainable and suitable options either for a given location or more generically. MCAs are attractive given the multi-dimensional and complex nature of sustainability assessments, which typically involve a range of conflicting criteria featuring different forms of data and information. However, the input information on which the MCA is based is often associated with uncertainties. The aim of this study was to develop and apply a MCA for a national-scale sustainability assessment and ranking of eleven renewable energy technologies in Scotland and to critically investigate how the uncertainties in the applied input information influence the result. The developed MCA considers nine criteria comprising three technical, three environmental and three socio-economic criteria. Extensive literature reviews for each of the selected criteria were carried out and the information gathered was used with MCA to provide a ranking of the renewable energy alternatives. The reviewed criteria values were generally found to have wide ranges for each technology. To account for this uncertainty in the applied input information, each of the criteria values were defined by probability distributions and the MCA run using Monte Carlo simulation. Hereby a probabilistic ranking of the renewable energy technologies was provided. We show that the ranking provided by the MCA in our specific case is highly uncertain due to the uncertain input information. We conclude that it is important that future MCA studies address these uncertainties explicitly, when assessing the sustainability of different energy projects to obtain more robust results and ensure better informed decision-making. [ABSTRACT FROM AUTHOR]

Electricity and heat generation are key contributors to global emissions of greenhouse gases (GHG). In this paper, specific attention is paid to renewable energy technologies (RETs) for electricity and heat generation and reviews current understanding and estimates of life cycle GHG emissions from a range of renewable electricity and heat generation technologies. Comprehensive literature reviews for each RET were carried out. The 79 studies reviewed involved the life cycle assessment (LCA) of renewable electricity and heat generation based on onshore and offshore winds, hydropower, marine technologies (wave power and tidal energy), geothermal, photovoltaic (PV), solar thermal, biomass, waste, and heat pumps. The study demonstrates the variability of existing LCA studies (results) in tracking GHG emissions for electricity and heat generation from RETs. This review has shown that the lowest GHG emissions were associated with offshore wind technologies (mean life cycle GHG emissions could be 5.3–13 g CO 2 eq/kWh). Results compared with GHG estimates by fossil fuel heat and electricity indicated that life cycle GHG emissions are comparatively higher in conventional sources as compared to renewable sources with the exception of nuclear-based power electricity generation. In this present study, considering renewable energy sources, waste treatment and dedicated biomass technologies (DBTs) were found to potentially have high GHG emissions based on the feedstock, selected boundary and the inputs required for their production. The study identifies additional impacts associated with renewable electricity and heat technologies, points out the effectiveness of life cycle analysis (LCA) as a tool for assessing environmental impacts of renewable energy sources and concludes with opportunities for improvement in the future. [ABSTRACT FROM AUTHOR]

Abstract: It is generally acknowledged that water management must be based on an integrated approach, considering the entire freshwater cycle. This has in particularly been endorsed in Europe by the European Water Framework Directive (WFD) imposing integrated management considering all waters. Although not prescribed by the WFD, integrated hydrological modelling may be necessary to support the management according to the directive as also suggested by several research projects initiated by the EU commission. To ensure a coherent and consistent management across various institutions and authorities, having different responsibilities and operating at various scales, a common tool integrating all relevant knowledge and data is imperative. By the end of 2003, a numerical national water resources model was constructed for Denmark, which has been applied in several national assessments. At the regional level there has, however, been some reluctance to use the model, primarily because the model did not contain the most recent data and understanding obtained from detailed local studies. The model has therefore been subject to a comprehensive update focussing on utilising the system understanding from the local studies. This process was largely stakeholder driven by involvement of predominantly the technical staff at the regional water authorities. Local knowledge is continuously improved urging the model update to be an on-going process. Based on experience from the update of the Danish national water resources model, three levels of model updating have been identified: 1) Basic data update – keeping the model up-to-date with respect to input data, 2) improving the model description by including new or more detailed data, and 3) reconstructing the model concept. The three levels vary with respect to technical tasks, challenges and stakeholder involvement. Two utility programs developed to optimise the updating process and support the uptake of data and knowledge from local users are furthermore presented. Finally, some of the challenges in operating a national model with multiple users belonging to different institutions with varying demands are discussed. [Copyright &y& Elsevier]

The IEC standards describe how to measure the power performance of an isolated wake-free wind turbine. However, most wind turbines operate under waked conditions for a substantial amount of time, calling for the need of a new methodology for power performance evaluation. We define multivariate power curves in the form of multivariate polynomial regressions, whose input variables are several wind speed and turbulence measurements retrieved with nacelle lidars. We use a dataset of synthetic power performance tests including both waked and wake-free conditions. The dataset is generated through aeroelastic simulations combined with both virtual nacelle lidars and the dynamic wake meandering model. A feature-selection algorithm is used to select the input variables among the available measurements, showing that the optimal model includes four input variables: three correspondent to wind speed and one to turbulence measures. Additionally, we give insights on the optimal nacelle-lidar scanning geometry needed to implement the multivariate power curve. Results show that the multivariate power curves predict the power output with accuracy of the same order under both waked and wake-free operation. For the in-wake cases, the accuracy is much higher than that of the IEC standard power curve, with an error reduction of up to 88%. • Aeroelastic simulations combined with a wake model and virtual nacelle lidars. • Modelling wind turbine power curves as multivariable polynomial regressions. • Several nacelle lidar configurations are tested. • The multivariate power curves are more accurate than the IEC standard power curve. • The multivariate power curves are as accurate in wake as in wake-free conditions. [ABSTRACT FROM AUTHOR]

In human autoimmune diseases, low plasma levels of complement factors C3 and C4 are commonly used as a proxy for complement activation. The measurements of C3 and C4 concentrations (the result of synthesis and consumption) however, show low sensitivity in patient follow-up. We find that the estimation of the C3dg fragment released during complement activation is a better parameter for complement activation. Available techniques for measuring the activation fragment C3dg, e.g. immune-electrophoresis or involving PEG-precipitation, are time-consuming and difficult to standardize. Here we examine the specificity and use of an antibody with mono-specificity for a neoepitope at the N-terminus of C3dg, which is only exposed after cleavage of C3. We present a stable, reproducible, and easy-to-use, time-resolved immunoassay with specificity for C3dg that can be used to directly evaluate ongoing complement activation. We demonstrate that the assay can be applied to clinical samples with a high specificity (95%) and a positive likelihood ratio of 10. It can also differentiate the complement related disease Systemic Lupus Erythematosus from controls and other immune-mediatedimmune mediated diseases like Rheumatoid Arthritis (86% specificity) and Spondyloarthritis (91% specificity). Further, we establish how the assay may also be used for experimental research in in vivo mouse models. [ABSTRACT FROM AUTHOR]

• Novel method to project groundwater contamination. • Pit-latrine contamination risk under 5 population scenarios. • Business as usual model predicts a 3x increase in microbial borehole contamination. • Current nitrogen in pit-latrines comparable to national fertiliser in Malawi. Pit-latrines are central to achieving UN Sustainable Development Goal 6 (SDG 6) of ensuring "clean water and sanitation for all". Unless safely managed, pit-latrines result in groundwater contamination, which increases morbidity and mortality. Despite this, there have been no long-term spatial projections of future pit-latrine contamination risks. National survey data of over 100,000 water-points and 260,000 pit-latrines in Malawi was used to generate a novel, high-resolution model of pit-latrines from 2020 to 2070 under five population scenarios. The results here are presented as a 'business as usual' scenario of population growth and pit-latrine usage, predicting a three-fold increase in the number of current water-points at risk of short-distance microbial pit-latrine contamination between 2020 and 2070, with a seven-fold increase in number at the highest risk of contamination. Current nitrogen loading into pit-latrines is comparable to national fertiliser application. The model predicts 8.2 mega-tonnes of faecal nitrogen will be disposed of into subsequently abandoned pit-latrines between 2020 and 2070. Change is necessary to prevent SDG6's push for sanitation undermining its goal of clean water. [Display omitted] [ABSTRACT FROM AUTHOR]

A key component in risk assessment of contaminated sites is in the formulation of a conceptual site model (CSM). A CSM is a simplified representation of reality and forms the basis for the mathematical modeling of contaminant fate and transport at the site. The CSM should therefore identify the most important site-specific features and processes that may affect the contaminant transport behavior at the site. However, the development of a CSM will always be associated with uncertainties due to limited data and lack of understanding of the site conditions. CSM uncertainty is often found to be a major source of model error and it should therefore be accounted for when evaluating uncertainties in risk assessments. We present a Bayesian belief network (BBN) approach for constructing CSMs and assessing their uncertainty at contaminated sites. BBNs are graphical probabilistic models that are effective for integrating quantitative and qualitative information, and thus can strengthen decisions when empirical data are lacking. The proposed BBN approach facilitates a systematic construction of multiple CSMs, and then determines the belief in each CSM using a variety of data types and/or expert opinion at different knowledge levels. The developed BBNs combine data from desktop studies and initial site investigations with expert opinion to assess which of the CSMs are more likely to reflect the actual site conditions. The method is demonstrated on a Danish field site, contaminated with chlorinated ethenes. Four different CSMs are developed by combining two contaminant source zone interpretations (presence or absence of a separate phase contamination) and two geological interpretations (fractured or unfractured clay till). The beliefs in each of the CSMs are assessed sequentially based on data from three investigation stages (a screening investigation, a more detailed investigation, and an expert consultation) to demonstrate that the belief can be updated as more information becomes available. [ABSTRACT FROM AUTHOR]

Abstract: The geologically related uncertainty in groundwater modeling originates from two main sources: geological structures and hydraulic parameter values within these structures. Within a geological structural element the parameter values will always exhibit local scale heterogeneity, which can be accounted for, but is often neglected, in assessments of prediction uncertainties. Strategies for assessing prediction uncertainty due to geologically related uncertainty may be divided into three main categories, accounting for uncertainty due to: (a) the geological structure; (b) effective model parameters; and (c) model parameters including local scale heterogeneity. The most common methodologies for uncertainty assessments within each of these categories, such as multiple modeling, Monte Carlo analysis, regression analysis and moment equation approach, are briefly described with emphasis on their key characteristics. Based on reviews of previous studies, assessments are made on the relative importance of the three uncertainty categories for different types of model predictions. Furthermore, the strengths, limitations and interactions of these methodologies are discussed and conclusions are made with respect to identifying key subjects for which further research is needed. When all sources of uncertainty are analyzed by exploring model parameter and local scale heterogeneity uncertainty for several plausible geological model structures the joint uncertainties can be assessed by use of model averaging techniques, such as Bayesian Model Averaging (BMA). General challenge in model averaging with respect to choosing mutually exclusive and collectively exhaustive choice models, as well as to assign weights when models are used beyond their calibration base, are discussed. [Copyright &y& Elsevier]

Abstract: 36Cl produced by thermonuclear bomb testing has been proposed as an additional tool to date or at least to identify recent groundwater components. In order to investigate the behaviour of 36Cl in shallow groundwater a multi-tracer approach (3H/3He, SF6, CFC-12 and 85Kr) was used to characterise and date the groundwater of a quaternary sands aquifer which is located on the Island of Funen near the city of Odense, Denmark. Recharge to the semi-confined shallow aquifer occurs through permeable sand windows and fractured tills at the surface. Locally, however, mixing with older pre-bomb water from the underlying limestone aquifer may occur. The integrated analyses of the available tracer data allowed a well constrained age structure determination of the investigated water system. The 36Cl/Cl ratios measured in groundwater were used to reconstruct the fallout rates for radioactive 36Cl at Odense. The calculated fallout values exceeded the fallout estimated based on data from the Dye-3 ice core in Greenland. Recycling of the bomb peak fallout seems to be the most probable reason of the high values measured. The local extent of this process is difficult to quantify, which impedes the use of 36Cl for dating. [Copyright &y& Elsevier]

• Novel method to assess the impacts of groundwater abstraction on adverse water quantity and quality relations. • Estimating environmental groundwater requirements from impacts on the aquifer. • Securing sustainable groundwater quality by constraining drawdown. • Obtaining spatially differentiated environmental groundwater requirements. • Assisting in the planning of abstracting water in relative water-abundant areas. Planning for sustainable groundwater abstraction requires realistic and reliable assessments of groundwater drawdown in aquifers as well as impacted groundwater-dependent terrestrial and aquatic ecosystems. Present-day impact assessments allocate water for the environment and ecosystems in the form of environmental groundwater requirements (EGWR s). However, securing sustainable groundwater abstraction also requires stable groundwater quality for consumers and receptors (e.g. streams and groundwater-dependent ecosystems). We suggest dividing EGWR into two parts, namely EGWR flow , related to impacts on surface water, and EGWR wq , related to impacts on groundwater quality. We then propose a method for modelling maximum safe groundwater abstraction rates based on a relationship between water quality and piezometric heads. The method provides estimations of sustainable abstraction rates that secure stable water quality and maintain water security. Using hydrological modelling, we estimated spatially differentiated EGWR wq , for Zealand, Denmark, based on three different conditioned drawdowns of 3, 6 and 9 m. We found that depending on the boundaries and the different conditioned drawdowns EGWR wq poses a 2.5–83% share of the groundwater recharge. We found that a redistribution of water abstraction would make 27 million m3 available compared with actual abstraction, dependent on scale, while keeping within a conditioned drawdown of 3 m. Our results demonstrate how conditioned drawdown can be implemented with the objectives of evaluating actual abstraction and securing stable water quality, hence comprising a step towards more reliable and relevant groundwater impact assessments. [ABSTRACT FROM AUTHOR]