Aim\nMethods\nResults\nDiscussion\nSystematic Review Registration\nTraditionally, early phase clinical trials in oncology have been performed in patients based on safety risk-benefit assessment.... Show moreAim\nMethods\nResults\nDiscussion\nSystematic Review Registration\nTraditionally, early phase clinical trials in oncology have been performed in patients based on safety risk-benefit assessment. Therapeutic transition to immuno-oncology may open new opportunities for studies in healthy volunteers, which are conducted faster and are less susceptible to confounders. Aim of this study was to investigate to what extent this approach is utilized and whether pharmacodynamic endpoints are evaluated in these early phase trials. We conducted a comprehensive review of clinical trials with healthy volunteers using immunotherapies potentially relevant for oncology.\nLiterature searches according to PRISMA guidelines and after registration in PROSPERO were conducted in PubMed, Embase, Web of Science and Cochrane databases with the cut-off date 20 October 2020, using search terms of relevant targets in immuno-oncology. Articles describing clinical trials with immunotherapeutics in healthy volunteers with a mechanism relevant for oncology were included. "Immunotherapeutic" was defined as compounds exhibiting effects through immunological targets. Data including study design and endpoints were extracted, with specific attention to pharmacodynamic endpoints and safety.\nIn total, we found 38 relevant immunotherapeutic compounds tested in HVs, with 86% of studies investigating safety, 82% investigating the pharmacokinetics (PK) and 57% including at least one pharmacodynamic (PD) endpoint. Most of the observed adverse events (AEs) were Grade 1 and 2, consisting mostly of gastrointestinal, cutaneous and flu-like symptoms. Severe AEs were leukopenia, asthenia, syncope, headache, flu-like reaction and liver enzymes increase. PD endpoints investigated comprised of cytokines, immune and inflammatory biomarkers, cell counts, phenotyping circulating immune cells and ex vivo challenge assays.\nHealthy volunteer studies with immuno-oncology compounds have been performed, although not to a large extent. The integration of healthy volunteers in well-designed proof-of-mechanism oriented drug development programs has advantages and could be pursued more in the future, since integrative clinical trial protocols may facilitate early dose selection and prevent cancer patients to be exposed to non-therapeutic dosing regimens.\nhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=210861, identifier CRD42020210861. Show less
We aimed at investigating host-virus co-metabolism during SARS-CoV-2 infection. Therefore, we extended comprehensive sex-specific, whole-body organ resolved models of human metabolism with the... Show moreWe aimed at investigating host-virus co-metabolism during SARS-CoV-2 infection. Therefore, we extended comprehensive sex-specific, whole-body organ resolved models of human metabolism with the necessary reactions to replicate SARS-CoV-2 in the lung as well as selected peripheral organs. Using this comprehensive host-virus model, we obtained the following key results: 1. The predicted maximal possible virus shedding rate was limited by isoleucine availability. 2. The supported initial viral load depended on the increase in CD4+ T-cells, consistent with the literature. 3. During viral infection, the whole-body metabolism changed including the blood metabolome, which agreed well with metabolomic studies from COVID-19 patients and healthy controls. 4. The virus shedding rate could be reduced by either inhibition of the guanylate kinase 1 or availability of amino acids, e.g., in the diet. 5. The virus variants differed in their maximal possible virus shedding rates, which could be inversely linked to isoleucine occurrences in the sequences. Taken together, this study presents the metabolic crosstalk between host and virus and emphasises the role of amino acid metabolism during SARS-CoV-2 infection, in particular of isoleucine. As such, it provides an example of how computational modelling can complement more canonical approaches to gain insight into host-virus crosstalk and to identify potential therapeutic strategies. Show less
To reduce, replace, and refine in vivo testing, there is increasing emphasis on the development of more physiologically relevant in vitro test systems to improve the reliability of non-animal-based... Show moreTo reduce, replace, and refine in vivo testing, there is increasing emphasis on the development of more physiologically relevant in vitro test systems to improve the reliability of non-animal-based methods for hazard assessment. When developing new approach methodologies, it is important to standardize the protocols and demonstrate the methods can be reproduced by multiple laboratories. The aim of this study was to assess the transferability and reproducibility of two advanced in vitro liver models, the Primary Human multicellular microtissue liver model (PHH) and the 3D HepG2 Spheroid Model, for nanomaterial (NM) and chemical hazard assessment purposes. The PHH model inter-laboratory trial showed strong consistency across the testing sites. All laboratories evaluated cytokine release and cytotoxicity following exposure to titanium dioxide (TiO2) and zinc oxide (ZnO) nanoparticles. No significant difference was observed in cytotoxicity or IL-8 release for the test materials. The data were reproducible with all three laboratories with control readouts within a similar range. The PHH model ZnO induced the greatest cytotoxicity response at 50.0 μg/mL and a dose-dependent increase in IL-8 release. For the 3D HepG2 spheroid model, all test sites were able to construct the model and demonstrated good concordance in IL-8 cytokine release and genotoxicity data. This trial demonstrates the successful transfer of new approach methodologies across multiple laboratories, with good reproducibility for several hazard endpoints. Show less
Bakker, A.T.; Kotsogianni, A.I.; Mirenda, L.; Straub, V.M.; Avalos Garcia, M.; Berg, R.J.B.H.N. van den; ... ; Stelt, M. van der 2022
Wind and solar photovoltaic (PV) power form vital parts of the energy transition toward renewable energy systems. The rapid development of these two renewables represents an enormous infrastructure... Show moreWind and solar photovoltaic (PV) power form vital parts of the energy transition toward renewable energy systems. The rapid development of these two renewables represents an enormous infrastructure construction task including both power generation and its associated electrical grid systems, which will generate demand for metal resources. However, most research on material demands has focused on their power generation systems (wind turbines and PV panels), and few have studied the associated electrical grid systems. Here, we estimate the global metal demands for electrical grid systems associated with wind and utility-scale PV power by 2050, using dynamic material flow analysis based on International Energy Agency's energy scenarios and the typical engineering parameters of transmission grids. Results show that the associated electrical grids require large quantities of metals: 27-81 Mt of copper cumulatively, followed by 20-67 Mt of steel and 11-31 Mt of aluminum. Electrical grids built for solar PV have the largest metal demand, followed by offshore and onshore wind. Power cables are the most metal-consuming electrical components compared to substations and transformers. We also discuss the decommissioning issue of electrical grids and their recovery potential. This study would deepen the understanding of the nexus between renewable energy, grid infrastructure, and metal resources. Show less
Meulen, A.N. van der; Hartendorp, M.; Voorn, W.; Hermans, F.F.J. 2022
Programming education is strongly emerging in elementary and high school. Diversity and inclusion are important topics, however, insights on suited programming materials for younger learners with... Show moreProgramming education is strongly emerging in elementary and high school. Diversity and inclusion are important topics, however, insights on suited programming materials for younger learners with visual impairments are lacking. A wide range of programming materials for children exists, diverse in both what is being programmed (output) and how this is done (input), yet often relying on visual features. An understanding of the usability and accessibility aspects of these different materials is important to inform educational practice and to increase understanding of what makes programming materials suited for low vision and blind children. The aim of this study is to explore the usability and accessibility of programming materials currently used in education to low vision and blind children in the Netherlands. A focus group was conducted with six teachers or IT experts, all working with the target group in special education. The thematic analysis of the discussion of 25 materials (including unplugged lessons, robots and robotic kits, block-based and text- based languages) showed the potential of several materials, especially unplugged lessons, and the continuing search for suited materials and workforms specifically for the blind children. Furthermore, prioritizing “fun” and close connections to children’s daily life as well as careful explorations of usability at the cognitive level came forward as important factors for future research and development in programming materials for low vision and blind children. These insights can contribute to obtaining an inclusive approach to programming for young learners. Show less
Kortleve, A.J.; Mogollón, J.M.; Heimovaara, T.J.; Gebert, J. 2022
Environmental or occupational exposure of humans to trichloroethylene (TCE) has been associated with different extrahepatic toxic effects, including nephrotoxicity and neurotoxicity. Bioactivation... Show moreEnvironmental or occupational exposure of humans to trichloroethylene (TCE) has been associated with different extrahepatic toxic effects, including nephrotoxicity and neurotoxicity. Bioactivation of TCE via the glutathione (GSH) conjugation pathway has been proposed as underlying mechanism, although only few mechanistic studies have used cell models of human origin. In this study, six human derived cell models were evaluated as in vitro models representing potential target tissues of TCE-conjugates: RPTEC/TERT1 (kidney), HepaRG (liver), HUVEC/TERT2 (vascular endothelial), LUHMES (neuronal, dopaminergic), human induced pluripotent stem cells (hiPSC) derived peripheral neurons (UKN5) and hiPSC-derived differentiated brain cortical cultures containing all subtypes of neurons and astrocytes (BCC42). A high throughput transcriptomic screening, utilizing mRNA templated oligo-sequencing (TempO-Seq), was used to study transcriptomic effects after exposure to TCE-conjugates. Cells were exposed to a wide range of concentrations of S-(1,2-trans-dichlorovinyl)glutathione (1,2-DCVG), S-(1,2-trans-dichlorovinyl)-L-cysteine (1,2-DCVC), S-(2,2-dichlorovinyl)glutathione (2,2-DCVG), and S-(2,2-dichlorovinyl)-L-cysteine (2,2-DCVC). 1,2-DCVC caused stress responses belonging to the Nrf2 pathway and Unfolded protein response in all the tested models but to different extents. The renal model was the most sensitive model to both 1,2-DCVC and 1,2-DCVG, with an early Nrf2-response at 3 µM and hundreds of differentially expressed genes at higher concentrations. Exposure to 2,2-DCVG and 2,2-DCVC also resulted in the upregulation of Nrf2 pathway genes in RPTEC/TERT1 although at higher concentrations. Of the three neuronal models, both the LUHMES and BCC42 showed significant Nrf2-responses and at higher concentration UPR-responses, supporting recent hypotheses that 1,2-DCVC may be involved in neurotoxic effects of TCE. The cell models with the highest expression of γ-glutamyltransferase (GGT) enzymes, showed cellular responses to both 1,2-DCVG and 1,2-DCVC. Little to no effects were found in the neuronal models from 1,2-DCVG exposure due to their low GGT-expression. This study expands our knowledge on tissue specificity of TCE S-conjugates and emphasizes the value of human cell models together with transcriptomics for such mechanistic studies. Show less
The European Union (EU) has set a 37.5% GHG reduction target in 2030 for the mobility sector, relative to 1990 levels. This requires increasing the share of zero-emission passenger vehicles, mainly... Show moreThe European Union (EU) has set a 37.5% GHG reduction target in 2030 for the mobility sector, relative to 1990 levels. This requires increasing the share of zero-emission passenger vehicles, mainly in the form of electric vehicles (EVs). This study calculates future GHG emissions related to passenger vehicle manufacturing and use based on stated policy goals of EU Member States for EV promotion. Under these policies, by 2040 the stock of EVs would be about 73 times larger than those of 2020, contributing to a cumulative in-use emission reduction of 2.0 gigatons CO2- eq. Nevertheless, this stated EV adoption will not be sufficiently fast to reach the EU's GHG reduction targets, and some of the GHG environmental burdens may be shifted to the EV battery manufacturing countries. To achieve the 2030 reduction targets, the EU as a whole needs to accelerate the phase-out of internal combustion engine vehicles and transit to e-mobility at the pace of the most ambitious Member States, such that EVs can comprise at least 55% of the EU passenger vehicle fleet in 2030. An accelerated decarbonization of the electricity system will become the most critical prerequisite for minimizing GHG emissions from both EV manufacturing and in-use stages. Show less
Pollen classification is considered an important task in palynology. In the Netherlands, two genera of the Urticaceae family, named Parietaria and Urtica, have high morphological similarities but... Show morePollen classification is considered an important task in palynology. In the Netherlands, two genera of the Urticaceae family, named Parietaria and Urtica, have high morphological similarities but induce allergy at a very different level. Therefore, distinction between these two genera is very important. Within this group, the pollen of Urtica membranacea is the only species that can be recognized easily under the micro-scope. For the research presented in this study, we built a dataset from 6472 pollen images and our aim was to find the best possible classifier on this dataset by analysing different classification methods, both machine learning and deep learning-based methods. For machine learning-based methods, we measured both texture and moment features based on images from the pollen grains. Varied feature selection tech-niques, classifiers as well as a hierarchical strategy were implemented for pollen classification. For deep learning-based methods, we compared the performance of six popular Convolutional Neural Networks: AlexNet, VGG16, VGG19, MobileNet V1, MobileNet V2 and ResNet50. Results show that compared with flat classification models, a hierarchical strategy yielded the highest accuracy with 94.5% among machine learning-based methods. Among deep learning-based methods, ResNet50 achieved an accuracy of 99.4%, slightly outperforming the other neural networks investigated. In addition, we investigated the influence on performance by changing the size of image datasets to 1000 and 500 images, respectively. Results demonstrated that on smaller datasets, ResNet50 still achieved the best classification performance. An ablation study was implemented to help understanding why the deep learning-based methods outper-formed the other models investigated. Using Urticaceae pollen as an example, our research provides a strategy of selecting a classification model for pollen datasets with highly similar pollen grains to support palynologists and could potentially be applied to other image classification tasks.(c) 2022 Leiden Institute of Advanced Computer Science, Leiden University. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Show less
Hollander, L.S. den; Béquignon, O.J.M.; Wang, X.; Wezel, K. van; Broekhuis, J.; Gorostiola González, M.; ... ; Heitman, L.H. 2022
CC chemokine receptor 2 (CCR2), a G protein-coupled receptor, plays a role in many cancer-related processes such as metastasis formation and immunosuppression. Since ∼ 20 % of human cancers contain... Show moreCC chemokine receptor 2 (CCR2), a G protein-coupled receptor, plays a role in many cancer-related processes such as metastasis formation and immunosuppression. Since ∼ 20 % of human cancers contain mutations in G protein-coupled receptors, ten cancer-associated CCR2 mutants obtained from the Genome Data Commons were investigated for their effect on receptor functionality and antagonist binding. Mutations were selected based on either their vicinity to CCR2's orthosteric or allosteric binding sites or their presence in conserved amino acid motifs. One of the mutant receptors, namely S101P2.63 with a mutation near the orthosteric binding site, did not express on the cell surface. All other studied mutants showed a decrease in or a lack of G protein activation in response to the main endogenous CCR2 ligand CCL2, but no change in potency was observed. Furthermore, INCB3344 and LUF7482 were chosen as representative orthosteric and allosteric antagonists, respectively. No change in potency was observed in a functional assay, but mutations located at F1163.28 impacted orthosteric antagonist binding significantly, while allosteric antagonist binding was abolished for L134Q3.46 and D137N3.49 mutants. As CC chemokine receptor 2 is an attractive drug target in cancer, the negative effect of these mutations on receptor functionality and drugability should be considered in the drug discovery process. Show less
Battery energy storage systems (BESS) are expected to fulfill a crucial role in the renewable energy systems of the future. Within current regulatory frameworks, assessing the sustainability as... Show moreBattery energy storage systems (BESS) are expected to fulfill a crucial role in the renewable energy systems of the future. Within current regulatory frameworks, assessing the sustainability as well as the social risks for BESS should be considered. In this research we conducted a social life cycle assessment (S-LCA) of two BESS: the vanadium redox flow battery (VRFB) and the lithium-ion battery (LIB). The S-LCA was conducted based on the guidelines set by UNEP/SETAC and using the PSILCA v.3 database. It was found that most social risks related to the life cycle of the batteries are associated with the raw material extraction stage, while sectors related to chemicals also entail considerable risks. Workers are the stakeholder group affected most. These results apply to supply chains located in both China and Germany, but risks were lower for similar supply chains in Germany. An LIB with a nickel manganese cobalt oxide cathode is associated with considerably larger risks compared to a LIB with lithium manganese oxide cathode. For a VRFB life cycle with an increased vanadium price, the social risks were higher than those of the VRFB supply chain with a regular vanadium price. Our paper shows that S-LCA through the PSILCA database can provide interesting insights into the potential social risks associated with a certain product's life cycle. Generalizations of the results are not recommended, and one should be careful with assessments for technologies that have not yet matured due to the cost sensitivity of the methodology. Show less
Low-molecular-weight hydrogels are attractive scaffolds for drug delivery applications because of their modular and facile preparation starting from inexpensive molecular components. The molecular... Show moreLow-molecular-weight hydrogels are attractive scaffolds for drug delivery applications because of their modular and facile preparation starting from inexpensive molecular components. The molecular design of the hydrogelator results in a commitment to a particular release strategy, where either noncovalent or covalent bonding of the drug molecule dictates its rate and mechanism. Herein, we demonstrate an alternative approach using a reaction-coupled gelator to tune drug release in a facile and user-defined manner by altering the reaction pathway of the low-molecular-weight gelator (LMWG) and drug components through an acylhydrazone-bond-forming reaction. We show that an off-the-shelf drug with a reactive handle, doxorubicin, can be covalently bound to the gelator through its ketone moiety when the addition of the aldehyde component is delayed from 0 to 24 h, or noncovalently bound with its addition at 0 h. We also examine the use of an L-histidine methyl ester catalyst to prepare the drugloaded hydrogels under physiological conditions. Fitting of the drug release profiles with the Korsmeyer-Peppas model corroborates a switch in the mode of release consistent with the reaction pathway taken: increased covalent ligation drives a transition from a Fickian to a semi-Fickian mode in the second stage of release with a decreased rate. Sustained release of doxorubicin from the reaction-coupled hydrogel is further confirmed in an MTT toxicity assay with MCF-7 breast cancer cells. We demonstrate the modularity and ease of the reaction-coupled approach to prepare drug-loaded self-assembled hydrogels in situ with tunable mechanics and drug release profiles that may find eventual applications in macroscale drug delivery. Show less
Helder, R.W.J.; Rousel, J.; Boiten, W.A.; Gooris, G.S.; Nadaban, A.; Ghalbzouri, A. el; Bouwstra, J.A. 2022
Human skin equivalents (HSEs) are 3D-cultured human skin models that mimic many aspects of native human skin (NHS). Although HSEs resemble NHS very closely, the barrier located in the stratum... Show moreHuman skin equivalents (HSEs) are 3D-cultured human skin models that mimic many aspects of native human skin (NHS). Although HSEs resemble NHS very closely, the barrier located in the stratum corneum (SC) is impaired. This is caused by an altered lipid composition in the SC of HSEs compared with NHS. One of the most pronounced changes in this lipid composition is a high level of monounsaturation. One key enzyme in this change is stearoyl-CoA desaturase-1 (SCD1), which catalyses the monounsaturation of lipids. In order to normalize the lipid composition, we aimed to target a group of nuclear receptors that are important regulators in the lipid synthesis. This group of receptors are known as the peroxisome proliferating activating receptors (PPARs). By (de)activating each isoform (PPAR-alpha, PPAR-delta and PPAR-gamma), the PPAR isoforms may have normalizing effects on the lipid composition. In addition, another PPAR-alpha agonist Wy14643 was included as this supplement demonstrated normalizing effects in the lipid composition in a more recent study. After PPAR (ant)agonists supplementation, the mRNA of downstream targets, lipid synthesis genes and lipid composition were investigated. The PPAR downstream targets were activated, indicating that the supplements reached the keratinocytes to trigger their effect. However, minimal impact was observed on the lipid composition after PPAR isoform (de) activation. Only the highest concentration Wy14643 resulted in strong, but negative effects on CER composition. Although the novel tested modifications did not result in an improvement, more insight is gained on the nuclear receptors PPARs and their effects on the lipid barrier in full-thickness skin models. Show less
The origin and evolution of galaxies are closely linked to many different physical phenomena. Among them, the most important one is the environment they reside in. Isolated and cluster member... Show moreThe origin and evolution of galaxies are closely linked to many different physical phenomena. Among them, the most important one is the environment they reside in. Isolated and cluster member galaxies indeed are affected by different forces which affect their evolution. The main concern of this thesis is to understand such forces and how they are related to galaxy evolution. Therefore, this thesis covers various topics including black hole mass calculations, the black hole mass-stellar velocity dispersion relation, the nature of AGN emission in galaxy clusters and field galaxies, a detailed investigation of X-ray and optical galaxy overdensity phenomenon, and the dynamical processes in pre-merging galaxy clusters. Show less
Streptomyces bacteria are a valuable source of natural products, many of which are used in the clinic or in biotechnology. In our search for novel antibiotics we discovered lugdunomycin, a natural... Show moreStreptomyces bacteria are a valuable source of natural products, many of which are used in the clinic or in biotechnology. In our search for novel antibiotics we discovered lugdunomycin, a natural product with a highly complex chemical architecture that is produced by Streptomyces sp. QL37. It is derived from the angucyclines, a well-known class of molecules known for their antibacterial and anticancer activities. Though angucyclines are produced in high quantities under most conditions, lugdunomycin is produced in minimal amounts. This thesis describes novel insights into the transcriptional control of the lugdunomycin biosynthetic gene cluster and into the lugdunomycin biosynthesis pathway. These insights may be applied to improve the yield of lugdunomycin and expand the chemical diversity of angucyclines. Using molecular biology, bioinformatic approaches and omics studies, such as metabolomics and transcriptomics, we have characterized the lugdunomycin biosynthetic gene cluster, the regulatory genes (lugRI–lugRV) required for transcriptional activation of the cluster, and the oxygenase genes (lugOI–lugOV) that play a key role in the different chemical rearrangements of the angucyclines. Furthermore, this thesis contains a detailed review of the regulatory network that controls antibiotic production in Actinobacteria. Show less
The transition to electric vehicles (EVs) reduces vehicle emissions to combat climate change. EVs raise concerns regarding the production of lithium-ion batteries and related emissions; while... Show moreThe transition to electric vehicles (EVs) reduces vehicle emissions to combat climate change. EVs raise concerns regarding the production of lithium-ion batteries and related emissions; while batteries can also provide energy storage services for the electricity system. Here we use the material flow analysis method to quantify the future material demand for lithium-ion batteries and the prospective life cycle assessment method to quantify future emissions of battery production. Further combined with battery technology modelling, future energy storage potential of EV batteries is evaluated. Results show the demand for battery raw materials will increase by a factor of over 15 in the next three decades, which requires a drastic expansion of battery supply chains. The increasing utilization of renewable energy and improved mining technology of raw materials for battery production will result in a 50% decrease in emissions per lithium-ion battery production between 2020-2050. Renewable energy transition contributes largely to this emission reduction, but EV battery storage can provide short-term grid services for complementing variable renewable generation. EV batteries alone could satisfy short-term grid storage demand by as early as 2030. This research reveals environmental challenges and opportunities for EV batteries as well as options to improve EV battery sustainability. Show less
Parkinson's disease is the second most common neurodegenerative disease in the world. One of its symptoms is the loss of dopaminergic neurons in the substantia nigra pars compacta. A number of... Show moreParkinson's disease is the second most common neurodegenerative disease in the world. One of its symptoms is the loss of dopaminergic neurons in the substantia nigra pars compacta. A number of phenotypes, including the aggregation of misfolded proteins, mitochondrial dysfunction, and neuroinflammatory chemicals released by microglia and activated astrocytes, may all play a role in its pathogenesis.Due to the multisystemic nature of Parkinson's disease, novel tools for developing mechanistic models that simulate its pathogenic processes have been proposed. Furthermore, as the amount of information in biological databases grows and the cost of omics experiments decreases, methods for integrating different types of biological data have become essential for increasing the level of detail in mechanistic models of biological systems.Constraint-based modelling is a valuable tool in bioengineering and biomedicine. It is used to estimate the reaction flux in a metabolic network. The constraints represent essential characteristics of a biological system, including connectivity between metabolites and reactions, thermodynamics, maximum and minimum flux rates, and the steady-state.This thesis presents studies and tools for integrating various types of specific information to genome-scale models used in constraint-based modelling. In addition, is presented the iDopaNeuro default models, genome-scale models of a culture of dopaminergic neurons derived from induced pluripotent stem cells. Show less
