Transport and retention of artificial and real wastewater particles inside a bed of settled aerobic granular sludge assessed applying magnetic resonance imaging

The removal or degradation of particulate organic matter is a crucial part in biological wastewater treatment. This is even more valid with respect to aerobic granular sludge and the impact of particulate organic matter on the formation and stability of the entire granulation process. Before the organic part of the particulate matter can be hydrolyzed and finally degraded by the microorganism, the particles have to be transported towards and retained within the granulated biomass. The understanding of these processes is currently very limited. Thus, the present study aimed at visualizing the transport of particulate organic matter into and through an aerobic granular sludge bed. Magnetic Resonance Imaging (MRI) was successfully applied to resolve the different fractions of a granular sludge bed over time and space. Quantification and merging of 3D data sets allowed for a clear determination of the particle distribution within the granular sludge bed. Dextran coated super paramagnetic iron oxide nanoparticles (SPIONs

Imaging with non-FDG PET tracers: outlook for current clinical applications

Apart from the historical and clinical relevance of positron emission tomography (PET) with 18F-fluorodeoxyglucose (18F-FDG), various other new tracers are gaining a remarkable place in functional imaging. Their contribution to clinical decision-making is irreplaceable in several disciplines. In this brief review we aimed to describe the main non-FDG PET tracers based on their clinical relevance and application for patient care

EPIdemiology of Surgery-Associated Acute Kidney Injury (EPIS-AKI) : Study protocol for a multicentre, observational trial

More than 300 million surgical procedures are performed each year. Acute kidney injury (AKI) is a common complication after major surgery and is associated with adverse short-term and long-term outcomes. However, there is a large variation in the incidence of reported AKI rates. The establishment of an accurate epidemiology of surgery-associated AKI is important for healthcare policy, quality initiatives, clinical trials, as well as for improving guidelines. The objective of the Epidemiology of Surgery-associated Acute Kidney Injury (EPIS-AKI) trial is to prospectively evaluate the epidemiology of AKI after major surgery using the latest Kidney Disease: Improving Global Outcomes (KDIGO) consensus definition of AKI. EPIS-AKI is an international prospective, observational, multicentre cohort study including 10 000 patients undergoing major surgery who are subsequently admitted to the ICU or a similar high dependency unit. The primary endpoint is the incidence of AKI within 72 hours after surgery according to the KDIGO criteria. Secondary endpoints include use of renal replacement therapy (RRT), mortality during ICU and hospital stay, length of ICU and hospital stay and major adverse kidney events (combined endpoint consisting of persistent renal dysfunction, RRT and mortality) at day 90. Further, we will evaluate preoperative and intraoperative risk factors affecting the incidence of postoperative AKI. In an add-on analysis, we will assess urinary biomarkers for early detection of AKI. EPIS-AKI has been approved by the leading Ethics Committee of the Medical Council North Rhine-Westphalia, of the Westphalian Wilhelms-University Münster and the corresponding Ethics Committee at each participating site. Results will be disseminated widely and published in peer-reviewed journals, presented at conferences and used to design further AKI-related trials. Trial registration number NCT04165369

Pore-Scale Hydrodynamics in a Progressively Bioclogged Three-Dimensional Porous Medium: 3-D Particle Tracking Experiments and Stochastic Transport Modeling

Biofilms are ubiquitous bacterial communities that grow in various porous media including soils, trickling, and sand filters. In these environments, they play a central role in services ranging from degradation of pollutants to water purification. Biofilms dynamically change the pore structure of the medium through selective clogging of pores, a process known as bioclogging. This affects how solutes are transported and spread through the porous matrix, but the temporal changes to transport behavior during bioclogging are not well understood. To address this uncertainty, we experimentally study the hydrodynamic changes of a transparent 3-D porous medium as it experiences progressive bioclogging. Statistical analyses of the system's hydrodynamics at four time points of bioclogging (0, 24, 36, and 48 h in the exponential growth phase) reveal exponential increases in both average and variance of the flow velocity, as well as its correlation length. Measurements for spreading, as mean-squared displacements, are found to be non-Fickian and more intensely superdiffusive with progressive bioclogging, indicating the formation of preferential flow pathways and stagnation zones. A gamma distribution describes well the Lagrangian velocity distributions and provides parameters that quantify changes to the flow, which evolves from a parallel pore arrangement under unclogged conditions, toward a more serial arrangement with increasing clogging. Exponentially evolving hydrodynamic metrics agree with an exponential bacterial growth phase and are used to parameterize a correlated continuous time random walk model with a stochastic velocity relaxation. The model accurately reproduces transport observations and can be used to resolve transport behavior at intermediate time points within the exponential growth phase considered

Modelling biofilm development: the importance of considering the link between EPS distribution, detachment mechanisms and physical properties

International audienceIn industry treatments against biofilms need to be optimized and in the wastewater treatment field, biofilm composition needs to be controlled. Therefore, describing the biochemical and physical structures of biofilms is now required to better understand the influence of operating parameters and treatment on biofilms. The present study aims to investigate how growth conditions influence EPS composition, biofilm physical properties and volume detachment using a 1D biofilm model. Two types of EPS are considered in the present model, proteins and polysaccharides. The main hypotheses are that: (i) the production of polysaccharides occurs mainly under strong nutrient limitation(s) occurs while the production of proteins is coupled to both the substrate uptake rate and the lysis process; (ii) the local biofilm porosity depends on the local biofilm composition. Both volume and surface detachment occur in biofilms and volume detachment extent depends on the biofilm local cohesion and thus on the local composition of biofilms for a given shear stress.The model is based on experimental trends and aims to represent these observations on the basis of biochemical and physical processes. Four case studies covering a wide range of contrasting growth conditions such as different COD/N ratios, applied SOLR and shear stresses are investigated. The model predicts how the biochemical and physical biofilm structures change as a result of contrasting growth conditions. More precisely simulation results are in good agreement with the main experimental observations reported in the literature, such as: (i) a strong nitrogen limitation of growth induces an important accumulation of polysaccharides leading to a more porous and homogenous biofilm, (ii) a high applied surface organic loading load allows to obtain a high biofilm thickness, (iii) a strong shear stress applied during the biofilm growth leads to a reduction of the biofilm thickness and to a consolidation of the biofilm structure. Overall, this model represents a relevant decision tool for the selection of appropriate enzymatic treatments in the context of negative biofilm control. From our results, it appears that protease based treatments should be more appropriate for biofilms developed under low COD/N ratios (about 20 gCOD/gN) whereas both glucosidases and proteases based treatments should be more appropriate for biofilms developed under high COD/N ratio (about 70 gCOD/gN). In addition, the model could be useful for other applications such as resource recovery in biofilms or granules, and help to better understand biological membrane fouling

Pore-Scale Hydrodynamics in a Progressively Bioclogged Three-Dimensional Porous Medium: 3-D Particle Tracking Experiments and Stochastic Transport Modeling.

Biofilms are ubiquitous bacterial communities that grow in various porous media including soils, trickling, and sand filters. In these environments, they play a central role in services ranging from degradation of pollutants to water purification. Biofilms dynamically change the pore structure of the medium through selective clogging of pores, a process known as bioclogging. This affects how solutes are transported and spread through the porous matrix, but the temporal changes to transport behavior during bioclogging are not well understood. To address this uncertainty, we experimentally study the hydrodynamic changes of a transparent 3-D porous medium as it experiences progressive bioclogging. Statistical analyses of the system's hydrodynamics at four time points of bioclogging (0, 24, 36, and 48 h in the exponential growth phase) reveal exponential increases in both average and variance of the flow velocity, as well as its correlation length. Measurements for spreading, as mean-squared displacements, are found to be non-Fickian and more intensely superdiffusive with progressive bioclogging, indicating the formation of preferential flow pathways and stagnation zones. A gamma distribution describes well the Lagrangian velocity distributions and provides parameters that quantify changes to the flow, which evolves from a parallel pore arrangement under unclogged conditions, toward a more serial arrangement with increasing clogging. Exponentially evolving hydrodynamic metrics agree with an exponential bacterial growth phase and are used to parameterize a correlated continuous time random walk model with a stochastic velocity relaxation. The model accurately reproduces transport observations and can be used to resolve transport behavior at intermediate time points within the exponential growth phase considered