Satellite-based estimation of total suspended solids and chlorophyll-a concentrations for the Gold Coast Broadwater, Australia

Satellite retrieval of total suspended solids (TSS) and chlorophyll-a (chl-a) was performed for the Gold Coast Broadwater, a micro-tidal estuarine lagoon draining a highly developed urban catchment area with complex and competing land uses. Due to the different water quality properties of the rivers and creeks draining into the Broadwater, sampling sites were grouped in clusters, with cluster-specific empirical/semi-empirical prediction models developed and validated with a leave-one-out cross validation approach for robustness. For unsampled locations, a weighted-average approach, based on their proximity to sampled sites, was developed. Confidence intervals were also generated, with a bootstrapping approach and visualised through maps. Models yielded varying accuracies (R2 = 0.40-0.75). Results show that, for the most significant poor water quality event in the dataset, caused by summer rainfall events, elevated TSS concentrations originated in the northern rivers, slowly spreading southward. Conversely, high chl-a concentrations were first recorded in the southernmost regions of the Broadwater.

Significant impact of time-of-day variation on metformin pharmacokinetics

AIMS/HYPOTHESIS

The objective was to investigate if metformin pharmacokinetics is modulated by time-of-day in humans using empirical and mechanistic pharmacokinetic modelling techniques on a large clinical dataset. This study also aimed to generate and test hypotheses on the underlying mechanisms, including evidence for chronotype-dependent interindividual differences in metformin plasma and efficacy-related tissue concentrations.

METHODS

A large clinical dataset consisting of individual metformin plasma and urine measurements was analysed using a newly developed empirical pharmacokinetic model. Causes of daily variation of metformin pharmacokinetics and interindividual variability were further investigated by a literature-informed mechanistic modelling analysis.

RESULTS

A significant effect of time-of-day on metformin pharmacokinetics was found. Daily rhythms of gastrointestinal, hepatic and renal processes are described in the literature, possibly affecting drug pharmacokinetics. Observed metformin plasma levels were best described by a combination of a rhythm in GFR, renal plasma flow (RPF) and organic cation transporter (OCT) 2 activity. Furthermore, the large interindividual differences in measured metformin concentrations were best explained by individual chronotypes affecting metformin clearance, with impact on plasma and tissue concentrations that may have implications for metformin efficacy.

CONCLUSIONS/INTERPRETATION

Metformin's pharmacology significantly depends on time-of-day in humans, determined with the help of empirical and mechanistic pharmacokinetic modelling, and rhythmic GFR, RPF and OCT2 were found to govern intraday variation. Interindividual variation was found to be partly dependent on individual chronotype, suggesting diurnal preference as an interesting, but so-far underappreciated, topic with regard to future personalised chronomodulated therapy in people with type 2 diabetes.

Response of glacier modelling parameters to time, space, and model complexity: Examples from eastern slopes of Canadian Rocky Mountains

Mountain glaciers are at risk of rapid retreat and require an accurate prediction of their melt and evolution. However, there is a great deal of hassle with mountain glacier melt modelling at a regional scale. Most advanced physical process-based models require an ample amount of high-resolution measurements, while widely-used empirical models suffer from parameter transferability. We developed a glacier melt, mass balance, and evolution modelling framework using three temperature index melt modelling approaches. We performed 24 model scenarios to examine the response of 19 empirical parameters to the effects of: (1) two time periods, for understanding how parameter response can vary with time period considered for the simulation; (2) two glaciers located at the eastern slopes of the Canadian Rocky Mountains, for understanding the effects of glaciers hydro-climate and geographic setting; and (3) two levels of complexity in the model structure including melt and mass balance models coupled with (complex) and without (simple) glacier evolution modules. The results showed that the best optimal melt parameter sets vary temporally and spatially for both simple and complex models, indicating that they are not transferable from one period to another and across glaciers. The variations of ice melt parameters are greater than the snowmelt parameters. The spatiotemporal variations of parameters are resulted from the geographical and local climatic settings and energy balance components, including albedo parameterization on the glacier surface, the altitudinal variations of the glaciers, and the slope and aspects to which glaciers are exposed. For all models, the most sensitive parameter is temperature Lapse rate (LR), but with increasing model complexity, the parameter responses vary depending on the melt model structure and input data. Our study provides important information for modelling glacier melt and evolution at a regional scale.

Solid State Kinetics of Nitrosation Using Native Sources of Nitrite

While many reactive species are known to cause N-nitrosation, trace nitrite (NO₂^-), which may be present in several excipients, is a source of nitrosating agents in pharmaceutical formulations. In this study we have found that the salt form of NO₂^- can influence the favored nitrosation conditions and final amount of nitrosamine being formed. Using native levels of NO₂^-, most likely present as ammonium nitrite (NH₄NO₂), in microcrystalline cellulose, we have determined the kinetics of nitrosamine formation in solid state with dimethylamine substrate present in metformin, used as model compound. It was found that the competing degradation of NH₄NO₂ into N₂ and H₂O limited the amount of nitrosamine formation to a great extent. Empirically modelling the kinetic data predicted reaching at maximum 1.6% conversion over a hypothetical 3-year shelf-life. These results also showed that using other sources of NO₂^- as spiking reagents, such as NaNO₂, may lead to unrealistic worst-case situations when the main form of NO₂^- in the drug product (DP) under evaluation may be NH₄NO₂. As well, measuring NO₂^- in freshly manufactured excipients containing NO₂^- potentially as NH₄NO₂ may lead to biased high NO₂^- content, which is not representative of the actual amounts present at the time of DP manufacture.

Nitrate as a predictor of cyanobacteria biomass in eutrophic lakes in a climate change context

We aimed to predict cyanobacteria biomass and nitrate (NO₃^-) concentrations in Lake Võrtsjärv, a large, shallow, and eutrophic lake in Estonia. We used a model chain based on the succession of a mechanistic (INCA-N) model and an empirical, generalized linear model. INCA-N model calibration and validation was performed with long term climate and catchment parameters. We constructed twelve scenarios as combinations of climate forcing from the Intergovernmental Panel on Climate Change (IPCC, 3 scenarios), land conversion (forest to agriculture, 2 scenarios), and fertilizer use (2 scenarios). Models predicted 46% of the variance of cyanobacteria biomass and 65% of that of NO₃^- concentrations. The model chain simulated that scenarios comprising both forest conversion to agricultural lands and a greater use of fertilizer per surface area unit would cause increases in lacustrine NO₃^- (up to twice the historical mean) and cyanobacteria biomass (up to a four-fold increase compared to the historical mean). The changes in NO₃^- concentrations and cyanobacteria biomass were more pronounced in low and moderate warming scenarios than in high warming scenarios because of increased denitrification rates in a warmer climate. Our findings show the importance of reducing anthropogenic pressures on lake catchments in order to reduce harmful pollutant and microalgae proliferation, and highlight the counterintuitive effects of multiple stressor interactions on lake functioning.

Experimental investigation on CO2 absorption and physicochemical characteristics of different carbon-loaded aqueous solvents

The anthropogenic carbon dioxide (CO₂) denseness in the earth's atmosphere is increasing day-to-day by combusting fossil fuels for power generation. And, it is the most important greenhouse gas (GHG) responsible for 64% of global warming. Solvent-based carbon capture gained more attention towards researchers because of its easiness to integrate with the coal-fired power plant without significant modifications. During CO₂ absorption, the physical property of the solvent gets changed. A change in the solvent's physicochemical property affects further CO₂ absorption, thereby increasing the carbon-capture energy demand. The present experimental study encompasses CO₂ absorption studies using 30 wt% aqueous monoethanolamine (MEA), 2-amino-2-methyl-1-propanol (AMP) and piperazine (PZ) followed by the detailed analysis of physicochemical properties (pH, carbon loading (α), viscosity (μ), density (ρ) and surface tension (σ)) of various CO₂-loaded solutions. The results revealed that these properties are exhibiting interdependent eccentrics. Furthermore, an empirical model was developed to predict the carbon loading of the tested solvents. This model includes the tested physicochemical properties, reaction mixture temperature, diffusivity and change in the mass of solvent during carbon loading. In addition, an empirical model for viscosity as a function of temperature, carbon loading and molecular weight of solvents was developed. These models appear to predict the carbon loading and the viscosity well with greater accuracy. Graphical abstract.

Identifying multiple stressors that influence eutrophication in a Finnish agricultural river

In Finland, a recent ecological classification of surface waters showed that the rivers and coastal waters need attention to improve their ecological state. We combined eco-hydrological and empirical models to study chlorophyll-a concentration as an indicator of eutrophication in a small agricultural river. We used a modified story-and-simulation method to build three storylines for possible changes in future land use due to climate change and political change. The main objective in the first storyline is to stimulate economic activity but also to promote the sustainable and efficient use of resources. The second storyline is based on the high awareness but poor regulation of environmental protection, and the third is to survive as individual countries instead of being part of a unified Europe. We assumed trade of agricultural products to increase to countries outside Europe. We found that chlorophyll-a concentration in the river depended on total phosphorus concentration. In addition, there was a positive synergistic interaction between total phosphorus and water temperature. In future storylines, chlorophyll-a concentration increased due to land use and climate change. Climate change mainly had an indirect influence via increasing nutrient losses from intensified agriculture. We found that well-designed agri-environmental measures had the potential to decrease nutrient loading from fields, as long as the predicted increase in temperature remained under 2 °C. However, we were not able to achieve the nutrient reduction stated in current water protection targets. In addition, the ecological status of the river deteriorated. The influence of temperature on chlorophyll-a growth indicates that novel measures for shading rivers to decrease water temperature may be needed in the future.

Quantifying suspended solids in small rivers using satellite data

The management of suspended solids and associated contaminants in rivers requires knowledge of sediment sources. In-situ sampling can only describe the integrated impact of the upstream sources. Empirical models that use surface reflectance from satellite images to estimate total suspended solid (TSS) concentrations can be used to supplement measurements and provide spatially continuous maps. However, there are few examples, especially in narrow, shallow and hydrologically dynamic rivers found in mountainous areas. A case study of the Didipio catchment in Philippines was used to address these issues. Four 5-m resolution RapidEye images, from between the years 2014 and 2016, and near-simultaneous ground measurements of TSS concentrations were used to develop a power law model that approximates the relationship between TSS and reflectance for each of four spectral bands. A second dataset using two 2-m resolution Pleiades-1A and a third using a 6-m resolution SPOT-6 image along with ground-based measurements, were consistent with the model when using the red band data. Using that model, encompassing data from all three datasets, gave an R² value of 65% and a root mean square error of 519mgL^-1. A linear relationship between reflectance and TSS exists from 1mgL^-1 to approximately 500mgL^-1. In contrast, for TSS measurements between 500mgL^-1 and 3580mgL^-1 reflectance increases at a generally lower and more variable rate. The results were not sensitive to changing the pixel location within the vicinity of the ground sampling location. The model was used to generate a continuous map of TSS concentration within the catchment. Further ground-based measurements including TSS concentrations that are higher than 3580mgL^-1 would allow the model to be developed and applied more confidently over the full relevant range of TSS.

Response of a multi-stressed Mediterranean river to future climate and socio-economic scenarios

Streams and rivers are among the most threatened ecosystems in Europe due to the combined effects of multiple pressures related to anthropogenic activities. Particularly in the Mediterranean region, changes in hydromorphology along with increased nutrient loadings are known to affect the ecological functions and ecosystem services of streams and rivers with the anticipated climate change being likely to further impair their functionality and structure. In this study, we investigated the combined effects of agricultural driven stressors on the ecology and delivered services of the Pinios river basin in Greece under three future world scenarios developed within the EU funded MARS project. Scenarios are based on combinations of Representative Concentration Pathways and Shared Socioeconomic Pathways and refer to early century (2030) and mid-century (2060) representing future climate worlds with particular socioeconomic characteristics. To assess the responses of ecological and ecosystem service indicators to the scenarios we first simulated hydrology and water quality in Pinios with a process-based model. Simulated abiotic stressor parameters (predictors) were linked to two biotic indicators, the macroinvertebrate indicators ASPT and EPT, with empirical modelling based on boosted regression trees and general linear models. Our results showed that the techno world scenario driven by fast economic growth and intensive exploitation of energy resources had the largest impact on both the abiotic status (nutrient loads and concentrations in water) and the biotic indicators. In contrast, the predicted changes under the other two future worlds, consensus and fragmented, were more diverse and were mostly dictated by the projected climate. This work showed that the future scenarios, especially the mid-century ones, had significant impact on both abiotic status and biotic responses underpinning the need for implementing catchment management practices able to mitigate the ecological threat on waters in the long-term.

Combining microCT-based characterization with empirical modelling as a robust screening approach for the design of optimized CaP-containing scaffolds for progenitor cell-mediated bone formation

Biomaterials are a key ingredient to the success of bone tissue engineering (TE), which focuses on the healing of bone defects by combining scaffolds with cells and/or growth factors. Due to the widely variable material characteristics and patient-specificities, however, current bone TE strategies still suffer from low repeatability and lack of robustness, which hamper clinical translation. Hence, optimal TE construct (i.e. cells and scaffold) characteristics are still under debate. This study aimed to reduce the material-specific variability for cell-based construct design, avoiding trial-and-error, by combining microCT characterization and empirical modelling as an innovative and robust screening approach. Via microCT characterization we have built a quantitative construct library of morphological and compositional properties of six CE approved CaP-based scaffolds (CopiOs®, BioOss™, Integra Mozaik™, chronOS Vivify, MBCP™ and ReproBone™), and of their bone forming capacity and in vivo scaffold degradation when combined with human periosteal derived cells (hPDCs). The empirical model, based on the construct library, allowed identification of the construct characteristics driving optimized bone formation, i.e. (a) the percentage of β-TCP and dibasic calcium phosphate, (b) the concavity of the CaP structure, (c) the average CaP structure thickness and (d) the seeded cell amount (taking into account the seeding efficiency). Additionally, the model allowed to quantitatively predict the bone forming response of different hPDC-CaP scaffold combinations, thus providing input for a more robust design of optimized constructs and avoiding trial-and error. This could improve and facilitate clinical translation.

STATEMENT OF SIGNIFICANCE

Biomaterials that support regenerative processes are a key ingredient for successful bone tissue engineering (TE). However, the optimal scaffold structure is still under debate. In this study, we have provided a useful innovative approach for robust screening of potential biomaterials or constructs (i.e. scaffolds seeded with cells and/or growth factors) by combining microCT characterization with empirical modelling. This novel approach leads to a better insight in the scaffold parameters influencing progenitor cell-mediated bone formation. Additionally, it serves as input for more controlled and robust design of optimized CaP-containing bone TE scaffolds. Hence, this novel approach could improve and facilitate clinical translation.