Consensus-based recommendations for the management of uveitis associated with juvenile idiopathic arthritis:the SHARE initiative

BACKGROUND: In 2012, a European initiative called Single Hub and Access point for pediatric Rheumatology in Europe (SHARE) was launched to optimise and disseminate diagnostic and management regimens in Europe for children and young adults with rheumatic diseases. Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease in children and uveitis is possibly its most devastating extra-articular manifestation. Evidence-based guidelines are sparse and management is mostly based on physicians' experience. Consequently, treatment practices differ widely, within and between nations. OBJECTIVES: To provide recommendations for the diagnosis and treatment of JIA-associated uveitis. METHODS: Recommendations were developed by an evidence-informed consensus process using the European League Against Rheumatism standard operating procedures. A committee was constituted, consisting of nine experienced paediatric rheumatologists and three experts in ophthalmology from Europe. Recommendations derived from a validated systematic literature review were evaluated by an Expert Committee and subsequently discussed at two consensus meetings using nominal group techniques. Recommendations were accepted if >80% agreement was reached (including all three ophthalmologists). RESULTS: In total, 22 recommendations were accepted (with >80% agreement among experts): 3 on diagnosis, 5 on disease activity measurements, 12 on treatment and 2 on future recommendations. CONCLUSIONS: The SHARE initiative aims to identify best practices for treatment of patients suffering from JIA-associated uveitis. Within this remit, recommendations for the diagnosis and treatment of JIA-associated uveitis have been formulated by an evidence-informed consensus process to suggest a standard of care for JIA-associated uveitis patients throughout Europe

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Modelling ultrafiltration performance by integrating local (critical) fluxes along the membrane length

Despite the vast number of studies on the understanding and estimation of the permeate flux in ultrafiltration, most of them base their estimations on either one or another mechanism, without pointing out a clear ‘bridge’ between them. The aim of this paper is to assess these mechanisms on the determination of the permeate flux, using as feed a multicomponent mixture of BSA, NaCl and H 2 O. Maxwell-Stefan Equations expressed as function of the components' volume fractions were used for an easier consideration of the non-idealities of the system. These non-idealities (hydration, adsorption, electrical interactions and volume exclusion) were critical in the local fluxes calculation, for which an increase in the thickness of the boundary layer along the filtration channel was considered. The developed model proved to be suitable for the estimation of fluxes lower than the limiting flux. Since the non-idealities of the system can be calculated along the concentration polarization layer, no extra information on the protein diffusivity was needed. Additionally, the fact that the model includes all the components from the solution offers the possibility of including the rejection of the accompanying ions in the calculations. </p

Fine ultrafiltration of concentrated oligosaccharide solutions – Hydration and pore size distribution effects

The effects of high concentration in the fine ultrafiltration of a solution of oligosaccharides were investigated both experimentally and using a mass transfer model based on the Maxwell-Stefan equations. At high concentrations, negative retentions were found for the smaller sugars, which cannot be ascribed to effects of ionic interaction, membrane adsorption or fouling. Instead, the behaviour could be quantitatively described by incorporating the effects of the thermodynamic non-ideality of the solutions and the effects of the pore size distribution. Experiments were performed to validate the model using as feed an oligosaccharide mixture with a concentration up to a 35% w/w. The model predictions allows the identification of an optimum feed concentration at which the efficiency of the separation is maximized. The results show that the fine ultrafiltration of sugars can be well described and predicted when taking into account the relevant thermodynamic interactions, the membrane pore size distribution and pressure effects

Modelling of membrane cascades for the purification of oligosaccharides

The aim of this study was to evaluate the potential of NF membrane cascades for continuous oligosaccharide purification. Three different nanofiltration membranes were evaluated, and the best combination in terms of membrane type and process parameters was determined for two commercial oligosaccharide mixtures of fructooligosaccharides (FOS) and galactooligosaccharides (GOS). To represent the cascade mathematically, a dynamic model was built based on film theory and on measurements performed in single-stage conditions. The model predictability was demonstrated with experiments in a membrane cascade set-up. Considering an initial purity of 84% for FOS and 40.4% for GOS, the model predicted a maximum attainable purity of 94.9% and 46.7% for FOS and GOS respectively. A minimum yield of 90% was used as constraint during the optimisation process, in which the physical limitations of the set up were also taken into account. This paper demonstrates that the trade-off situation between purity and yield can be overcome by using cascade configuration, leading to an efficient separation that cannot be achieved by single-stage membrane systems.</p

Ultrafiltration of non-spherical molecules

Information about the sizes of the solute molecules and membrane pores is needed to estimate solute rejection in filtration processes. Molecules are normally regarded as spheres, and the Stokes radius is commonly used to represent their molecular size. However, many molecules used in food and pharma processes are oligomers or polymers which are strongly elongated; therefore, considering them spherical affects the accuracy of the model predictions. We here adapt the so-called Steric Pore Model to a more realistic representation of the transfer of rigid elongated molecules into and through ultrafiltration membrane pores. To do so, sugars with different degree of polymerization were used as model molecules. They were considered to be capsule-shaped to facilitate their size estimation. In order to represent the system as accurately as possible, the effect of hydration on the sugars size was included, and the membrane pore size distribution was estimated based on rejection data. It was demonstrated that considering these molecules to be capsule-shaped instead of spherical generates better predictions over the entire rejection spectrum using a unique pore size distribution. Additionally, this capsular geometry lets us simplify the calculations, making the estimation of the rejection straightforward