URWARE Wastewater Treatment Plant Models

In this document, a large number of mathematical models describing various physical, biological and chemical processes in a wastewater treatment plant are presented. In most cases, the models are fairly simple as they are inteded for steady-state simulations based on yearly averages of the influent wastewater charteristics. The combination of models forms a software tool namned URWARE (URban WAter REsearch model), which is a tool for substance flow analysis and energy calculations in wastewater treatment systems. All models are based on the MATLAB/Simulink platform. The different models can be combined in any fashion thereby creating various system structures that can be analysed and compared. The models keep track of numerous substances related to wastewater, such as organic substances, nutrients and to some extent heavy metals. Within all models the release of environmentally hazardous substances to water, soil and air are calculated. The results can be used as one (of many) information pathways for strategic decision making related to urban water systems. The individual models are described one by one and their behaviours are exemplified by simulation results. In many cases, comparisons with other available software models are given to validate (or at least make plausible) the results produced by the fairly simple URWARE models. Simulation results based on a combination of models into a complete wastewater treatment plant are also presented. However, details about the underlying theory and hypotheses on which the models are based cannot always be sufficiently described due to space limitations. Moreover, users should always be critical to any results predicted by models and not take them for granted simply because they have been calculated by a computer model. Knowledge about the real processes and comparisons with real data are imperative to evaluate whether the predicted results are reasonable or not. For the interested reader the complete source code to all models is included in an extensive appendix. A modelling task of this magnitude is never completed. The proposed models can always be further developed, improved and refined. Consequently, the models described in this document only represent the first version of the URWARE software. Many issues remain to be solved and further improvements to be done. However, it is the hope of the authors that the presented models are mature enough to be used, evaluated, modified and improved by other users outside the URWARE task group

Pioneering an effect-based early warning system for hazardous chemicals in the environment

Existing regulatory frameworks often prove inadequate in promptly identifying contaminants of emerging concern (CECs) and determining their impacts on biological systems at an early stage. The establishment of Early Warning Systems (EWSs) for CECs is becoming increasingly relevant for policy-making, aiming to proactively detect chemical hazards and implement effective mitigation measures. Effect-based methodologies, including bioassays and effect-directed analysis (EDA), offer valuable input to EWSs by pinpointing the relevant toxicity drivers and prioritizing the associated risks. This review evaluates the analytical techniques currently available to assess biological effects, and provides a structured plan for their systematic integration into an EWS for hazardous chemicals in the environment. Key scientific advancements in effect-based approaches and EDA are discussed, underscoring their potential for early detection and management of chemical hazards. Additionally, critical challenges such as data integration and regulatory alignment are addressed, emphasizing the need for continuous improvement of the EWS and the incorporation of analytical advancements to safeguard environmental and public health from emerging chemical threats.Pioneering an effect-based early warning system for hazardous chemicals in the environmentpublishedVersio

IL-13 and IL-4, but not IL-5 nor IL-17A, induce hyperresponsiveness in isolated human small airways

BACKGROUND:Specific inflammatory pathways are indicated to contribute to severe asthma, but their individual involvement in the development of airway hyperresponsiveness remains unexplored. OBJECTIVE:This experimental study in human small bronchi aimed to provide insight into which of the type 2 and type 17 cytokines cause hyperresponsiveness of airway smooth muscle. METHODS:Explanted small bronchi isolated from human lung tissue and human airway smooth muscle cells were treated for 2 and 1 day(s), respectively, with 100 ng/mL of IL-4, IL-5, IL-13, or IL-17A, and contractile responses, Ca2+ mobilization, and receptor expression were assessed. RESULTS:Treatment with IL-13 increased the potency of histamine, carbachol, and leukotriene D4 as contractile agonists. IL-4, but not IL-5 or IL-17A, also increased the potency of histamine. In human airway smooth muscle cells, IL-13 and IL-4, but not IL-5 and IL-17A, enhanced the histamine-induced Ca2+ mobilization that was accompanied with increased mRNA expression of histamine H1 and cysteinyl leukotriene CysLT1 receptors. RNA sequencing of isolated bronchi confirmed the IL-13-mediated upregulation of H1 and CysLT1 receptors, without showing an alteration of muscarinic M3 receptors. Dexamethasone had no effects on IL-13-induced hyperresponsiveness in human bronchi, the increased Ca2+ mobilization, or the enhanced receptor expression. In contrast, antagonism of the common receptor for IL-13 and IL-4 by the biologic dupilumab prevented the effects of both IL-13 and IL-4 in human bronchi and human airway smooth muscle cells. CONCLUSIONS:The glucocorticoid-insensitive hyperrresponsiveness in isolated human airways induced by IL-13 and IL-4 provides further evidence that the IL-4Rα pathway should be targeted as a new strategy for the treatment of airway hyperresponsiveness in asthma.FWN – Publicaties zonder aanstelling Universiteit Leide

Role of Ox-PAPCs in the Differentiation of Mesenchymal Stem Cells (MSCs) and Runx2 and PPARγ2 Expression in MSCs-Like of Osteoporotic Patients

BACKGROUND: Mesenchymal stem cells (MSCs) can differentiate into osteoblasts and adipocytes and conditions causing bone loss may induce a switch from the osteoblast to adipocyte lineage. In addition, the expression of Runx2 and the PPARγ2 transcription factor genes is essential for cellular commitment to an osteogenic and adipogenic differentiation, respectively. Modified lipoproteins derived from the oxidation of arachidonate-containing phospholipids (ox-PAPCs: POVPC, PGPC and PEIPC) are considered important factors in atherogenesis. METHODOLOGY: We investigated the effect of ox-PAPCs on osteogenesis and adipogenesis in human mesenchymal stem cells (hMSCs). In particular, we analyzed the transcription factor Runx2 and the PPARγ2 gene expression during osteogenic and adipogenic differentiation in absence and in presence of ox-PAPCs. We also analyzed gene expression level in a panel of osteoblastic and adipogenic differentiation markers. In addition, as circulating blood cells can be used as a "sentinel" that responds to changes in the macro- or micro-environment, we analyzed the Runx2 and the PPARγ2 gene expression in MSCs-like and ox-PAPC levels in serum of osteoporotic patients (OPs). Finally, we examined the effects of sera obtained from OPs in hMSCs comparing the results with age-matched normal donors (NDs). PRINCIPAL FINDINGS: Quantitative RT-PCR demonstrated that ox-PAPCs enhanced PPARγ2 and adipogenic gene expression and reduced Runx2 and osteoblast differentiation marker gene expression in differentiating hMSCs. In OPs, ox-PAPC levels and PPARγ2 expression were higher than in NDs, whereas Runx2 was lower than in ND circulant MSCs-like. CONCLUSIONS: Ox-PAPCs affect the osteogenic differentiation by promoting adipogenic differentiation and this effect may appear involved in bone loss in OPs