In this thesis, I focused on studying the above- and belowground interactions of J. vulgaris from a plant-soil feedback (hereafter, PSF) perspective. I investigated the temporal variation of... Show moreIn this thesis, I focused on studying the above- and belowground interactions of J. vulgaris from a plant-soil feedback (hereafter, PSF) perspective. I investigated the temporal variation of negative PSF and examined the effects of root-associated bacteria on plant performance and aboveground herbivores. Additionally, I tested the role of PSF in relation to plant population structure and the significance of soil legacy effects in natural conditions. The findings reveal that temporal dynamics in PSF are driven by changes in plant sensitivity and in the soil microbiome. Although bacteria isolated from J. vulgaris roots can negatively affect plant performance, they can also affect aboveground herbivores and other plant species. Consequently, these bacteria may not be suitable for biological control of J. vulgaris. Moreover, I discovered that soil nematodes can mediate plant-plant interactions, but often favoring J. vulgaris. In my field work, I detected soil legacy effects, but seedling recruitment spatial patterns of J. vulgaris were not soil-mediated. The insights gained from studying PSF and above- and belowground interactions have the potential to reshape traditional approaches employed in controlling invasive plants. This thesis emphasizes the importance of transitioning PSF experiments from indoor to outdoor settings considering various influencing factors simultaneously. Show less
Background/aims To investigate genotype-phenotype associations in patients with KCNV2 retinopathy.Methods Review of clinical notes, best-corrected visual acuity (BCVA), molecular variants,... Show moreBackground/aims To investigate genotype-phenotype associations in patients with KCNV2 retinopathy.Methods Review of clinical notes, best-corrected visual acuity (BCVA), molecular variants, electroretinography (ERG) and retinal imaging. Subjects were grouped according to the combination of KCNV2 variants-two loss-of-function (TLOF), two missense (TM) or one of each (MLOF)-and parameters were compared.Results Ninety-two patients were included. The mean age of onset (mean +/- SD) in TLOF (n=55), TM (n=23) and MLOF (n=14) groups was 3.51 +/- 0.58, 4.07 +/- 2.76 and 5.54 +/- 3.38 years, respectively. The mean LogMAR BCVA ( +/- SD) at baseline in TLOF, TM and MLOF groups was 0.89 +/- 0.25, 0.67 +/- 0.38 and 0.81 +/- 0.35 for right, and 0.88 +/- 0.26, 0.69 +/- 0.33 and 0.78 +/- 0.33 for left eyes, respectively. The difference in BCVA between groups at baseline was significant in right (p=0.03) and left eyes (p=0.035). Mean outer nuclear layer thickness ( +/- SD) at baseline in TLOF, MLOF and TM groups was 37.07 +/- 15.20 mu m, 40.67 +/- 12.53 and 40.38 +/- 18.67, respectively, which was not significantly different (p=0.85). The mean ellipsoid zone width (EZW) loss ( +/- SD) was 2051 mu m ( +/- 1318) for patients in the TLOF, and 1314 mu m ( +/- 965) for MLOF. Only one patient in the TM group had EZW loss at presentation. There was considerable overlap in ERG findings, although the largest DA 10 ERG b-waves were associated with TLOF and the smallest with TM variants.Conclusions Patients with missense alterations had better BCVA and greater structural integrity. This is important for patient prognostication and counselling, as well as stratification for future gene therapy trials. Show less
Rational drug design often starts from specific scaffolds to which side chains/substituents are added or modified due to the large drug-like chemical space available to search for novel drug-like... Show moreRational drug design often starts from specific scaffolds to which side chains/substituents are added or modified due to the large drug-like chemical space available to search for novel drug-like molecules. With the rapid growth of deep learning in drug discovery, a variety of effective approaches have been developed for de novo drug design. In previous work we proposed a method named DrugEx, which can be applied in polypharmacology based on multi-objective deep reinforcement learning. However, the previous version is trained under fixed objectives and does not allow users to input any prior information (i.e. a desired scaffold). In order to improve the general applicability, we updated DrugEx to design drug molecules based on scaffolds which consist of multiple fragments provided by users. Here, a Transformer model was employed to generate molecular structures. The Transformer is a multi-head self-attention deep learning model containing an encoder to receive scaffolds as input and a decoder to generate molecules as output. In order to deal with the graph representation of molecules a novel positional encoding for each atom and bond based on an adjacency matrix was proposed, extending the architecture of the Transformer. The graph Transformer model contains growing and connecting procedures for molecule generation starting from a given scaffold based on fragments. Moreover, the generator was trained under a reinforcement learning framework to increase the number of desired ligands. As a proof of concept, the method was applied to design ligands for the adenosine A2A receptor (A2AAR) and compared with SMILES-based methods. The results show that 100% of the generated molecules are valid and most of them had a high predicted affinity value towards A2AAR with given scaffolds. Show less
Molecular-level insight into interfacial water at a buried electrode interface is essential in electrochemistry, but spectroscopic probing of the interface remains challenging. Here, using surface... Show moreMolecular-level insight into interfacial water at a buried electrode interface is essential in electrochemistry, but spectroscopic probing of the interface remains challenging. Here, using surface-specific heterodyne-detected sum-frequency generation (HD-SFG) spectroscopy, we directly access the interfacial water in contact with the graphene electrode supported on calcium fluoride (CaF2). We find phase transition-like variations of the HD-SFG spectra vs. applied potentials, which arises not from the charging/discharging of graphene but from the charging/discharging of the CaF2 substrate through the pseudocapacitive process. The potential-dependent spectra are nearly identical to the pH-dependent spectra, evidencing that the pseudocapacitive behavior is associated with a substantial local pH change induced by water dissociation between the CaF2 and graphene. Our work evidences the local molecular-level effects of pseudocapacitive charging at an electrode/aqueous electrolyte interface. Show less
Gao, C.; Bezemer, T. M.; Bodegom, P. M. van; Cornelissen, H.C.; Logtestijn, R. van; Liu, X.; ... ; Soudzilovskaia, N. A. 2023
Insights into how to control the activity and selectivity of the electrochemical CO2 reduction reaction are still limited because of insufficient knowledge of the reaction mechanism and kinetics,... Show moreInsights into how to control the activity and selectivity of the electrochemical CO2 reduction reaction are still limited because of insufficient knowledge of the reaction mechanism and kinetics, which is partially due to the lack of information on the interfacial pH, an important parameter for proton-coupled reactions like CO2 reduction. Here, we used a reliable and sensitive pH sensor combined with the rotating ring-disk electrode technique, in which a functionalized Au ring electrode works as a real-time detector of the OH- generated during the CO2 reduction reaction at a gold disk electrode. Variations of the interfacial pH due to both electrochemical and homogeneous reactions are mapped and the correlation of the interfacial pH with these reactions is inferred. The interfacial pH near the disk electrode increases from 7 to 12 with increasing current density, with a sharp increase at around -0.5 V vs. RHE, which indicates a change of the dominant buffering species. Through scan rate-dependent voltammetry and chronopotentiometry experiments, the homogenous reactions are shown to reach equilibrium within the time scale of the pH measurements, so that the interfacial concentrations of different carbonaceous species can be calculated using equilibrium constants. Furthermore, pH measurements were also performed under different conditions to disentangle the relationship between the interfacial pH and other electrolyte effects. The buffer effect of alkali metal cations is confirmed, showing that weakly hydrated cations lead to less pronounced pH gradients. Finally, we probe to which extent increasing mass transport and the electrolyte buffer capacity can aid in suppressing the increase of the interfacial pH, showing that the buffer capacity is the dominant factor in suppressing interfacial pH variations. Show less
All tissue development and replenishment relies upon the breaking of symmetries leading to the morphological and operational differentiation of progenitor cells into more specialized cells. One of... Show moreAll tissue development and replenishment relies upon the breaking of symmetries leading to the morphological and operational differentiation of progenitor cells into more specialized cells. One of the main engines driving this process is the Notch signal transduction pathway, a ubiquitous signalling system found in the vast majority of metazoan cell types characterized to date. Broadly speaking, Notch receptor activity is governed by a balance between two processes: 1) intercellular Notch transactivation triggered via interactions between receptors and ligands expressed in neighbouring cells; 2) intracellular cis inhibition caused by ligands binding to receptors within the same cell. Additionally, recent reports have also unveiled evidence of cis activation. Whilst context-dependent Notch receptor clustering has been hypothesized, to date, Notch signalling has been assumed to involve an interplay between receptor and ligand monomers. In this study, we demonstrate biochemically, through a mutational analysis of DLL4, both in vitro and in tissue culture cells, that Notch ligands can efficiently self-associate. We found that the membrane proximal EGF-like repeat of DLL4 was necessary and sufficient to promote oligomerization/dimerization. Mechanistically, our experimental evidence supports the view that DLL4 ligand dimerization is specifically required for cis-inhibition of Notch receptor activity. To further substantiate these findings, we have adapted and extended existing ordinary differential equation-based models of Notch signalling to take account of the ligand dimerization-dependent cis-inhibition reported here. Our new model faithfully recapitulates our experimental data and improves predictions based upon published data. Collectively, our work favours a model in which net output following Notch receptor/ligand binding results from ligand monomer-driven Notch receptor transactivation (and cis activation) counterposed by ligand dimer-mediated cis-inhibition.Author summary The growth and maintenance of tissues is a fundamental characteristic of metazoan life, controlled by a highly conserved core of cell signal transduction networks. One such pathway, the Notch signalling system, plays a unique role in these phenomena by orchestrating the generation of the phenotypic and genetic asymmetries which underlie tissue development and remodeling. At the molecular level, it achieves this via two specific types of receptor/ligand interaction: intercellular binding of receptors and ligands expressed in neighbouring cells, which triggers receptor activation (transactivation); intracellular receptor/ligand binding within the same cell which blocks receptor activation (cis inhibition). Together, these counterposed mechanisms determine the strength, the direction and the specificity of Notch signalling output. Whilst, the basic mechanisms of receptor transactivation have been delineated in some detail, the precise nature of cis inhibition has remained enigmatic. Through a combination of experimental approaches and computational modelling, in this study, we present a new model of Notch signalling in which ligand monomers promote Notch receptor transactivation, whereas cis inhibition is induced optimally via ligand dimers. This is the first model to include a concrete molecular distinction, in terms of ligand configuration, between the main branches of Notch signalling. Our model faithfully recapitulates both our presented experimental results as well as the recently published work of others, and provides a novel perspective for understanding Notch-regulated biological processes such as embryo development and angiogenesis.Competing Interest StatementThe authors have declared no competing interest. Show less
The present study explores international teachers' identity in an intercultural context as manifested through their interpersonal behaviors. In this study with fourteen native speaker Chinese... Show moreThe present study explores international teachers' identity in an intercultural context as manifested through their interpersonal behaviors. In this study with fourteen native speaker Chinese language teachers and one hundred and ninety-two students, survey and interview methods were used as primary sources of data, and classroom observations were stimuli for interviews. The findings reveal that overseas teaching experiences strengthen teachers' professional identity, although they also bring teachers tensions. The study demonstrates that the teacher-student relationship is a useful lens to explore and interpret teacher identity in an intercultural context. The findings not only highlight how pre-existing beliefs and working context influence teachers’ identity development but also illuminate the distinctions of identity among teachers with different interpersonal profiles. Show less
Human populations have been shaped by catastrophes that may have left long-lasting signatures in their genomes. One notable example is the second plague pandemic that entered Europe in ca. 1,347 CE... Show moreHuman populations have been shaped by catastrophes that may have left long-lasting signatures in their genomes. One notable example is the second plague pandemic that entered Europe in ca. 1,347 CE and repeatedly returned for over 300 years, with typical village and town mortality estimated at 10%-40%.1 It is assumed that this high mortality affected the gene pools of these populations. First, local population crashes reduced genetic diversity. Second, a change in frequency is expected for sequence variants that may have affected survival or susceptibility to the etiologic agent (Yersinia pestis).2 Third, mass mortality might alter the local gene pools through its impact on subsequent migration patterns. We explored these factors using the Norwegian city of Trondheim as a model, by sequencing 54 genomes spanning three time periods: (1) prior to the plague striking Trondheim in 1,349 CE, (2) the 17th-19th century, and (3) the present. We find that the pandemic period shaped the gene pool by reducing long distance immigration, in particular from the British Isles, and inducing a bottleneck that reduced genetic diversity. Although we also observe an excess of large FST values at multiple loci in the genome, these are shaped by reference biases introduced by mapping our relatively low genome coverage degraded DNA to the reference genome. This implies that attempts to detect selection using ancient DNA (aDNA) datasets that vary by read length and depth of sequencing coverage may be particularly challenging until methods have been developed to account for the impact of differential reference bias on test statistics. Show less
Electrochemical CO2 reduction (CO2R) is an attractive option for storing renewable electricity and for the sustainable production of valuable chemicals and fuels. In this roadmap, we review recent... Show moreElectrochemical CO2 reduction (CO2R) is an attractive option for storing renewable electricity and for the sustainable production of valuable chemicals and fuels. In this roadmap, we review recent progress in fundamental understanding, catalyst development, and in engineering and scale-up. We discuss the outstanding challenges towards commercialization of electrochemical CO2R technology: energy efficiencies, selectivities, low current densities, and stability. We highlight the opportunities in establishing rigorous standards for benchmarking performance, advances in in operando characterization, the discovery of new materials towards high value products, the investigation of phenomena across multiple-length scales and the application of data science towards doing so. We hope that this collective perspective sparks new research activities that ultimately bring us a step closer towards establishing a low- or zero-emission carbon cycle. Show less
Ham, A. van der; Liu, X.; Calvani, D.; Melcrová, A.; Kozdra, M.; Buda, F.; ... ; Schneider, G.F. 2022
Molecularly thin, nanoporous thin films are of paramount importance in material sciences. Their use in a wide range of applications requires control over their chemical functionalities, which is... Show moreMolecularly thin, nanoporous thin films are of paramount importance in material sciences. Their use in a wide range of applications requires control over their chemical functionalities, which is difficult to achieve using current production methods. Here, the small polycyclic aromatic hydrocarbon decacyclene is used to form molecular thin films, without requiring covalent crosslinking of any kind. The 2.5 nm thin films are mechanically stable, able to be free-standing over micrometer distances, held together solely by supramolecular interactions. Using a combination of computational chemistry and microscopic imaging techniques, thin films are studied on both a molecular and microscopic scale. Their mechanical strength is quantified using AFM nanoindentation, showing their capability of withstanding a point load of 26 ± 9 nN, when freely spanning over a 1 μm aperture, with a corresponding Young's modulus of 6 ± 4 GPa. Our thin films constitute free-standing, non-covalent thin films based on a small PAH. Show less
The synthesis, characterization, crystal structure and detailed magnetic properties of a pyrazine (pyz) and azido (N3) bridged cobalt(II) compound of formula [Co(N3)2(pyz)] (1) are reported.... Show moreThe synthesis, characterization, crystal structure and detailed magnetic properties of a pyrazine (pyz) and azido (N3) bridged cobalt(II) compound of formula [Co(N3)2(pyz)] (1) are reported. Compound 1 shows a layered structure formed by Co(II) chains with double μ-N3(κN1,N1) bridges that are further connected by μ-(pyrazine-κN1,N4) bridges. The layers present weak van der Waals interactions between azido terminal groups. The magnetic properties show the presence of a metamagnetic behaviour in 1 with two critical fields of 200 and 400 mT at low temperatures. AC magnetic measurements show the presence of a long-range 2D ferromagnetic order at Tc ≈ 8.0-7.0 K for dc fields above 200 mT and a long-range 3D ferromagnetic order at Tc ≈ 4.5 K for dc fields above 400 mT. Show less
Over several decades, a variety of computational methods for drug discovery have been proposed and applied in practice. With the accumulation of data and the development of machine learning methods... Show moreOver several decades, a variety of computational methods for drug discovery have been proposed and applied in practice. With the accumulation of data and the development of machine learning methods, computational drug design methods have gradually shifted to a new paradigm, i.e. deep learning methods have attracted particular interest in drug design. In this study, a new deep learning-based method (DrugEx) was proposed to design de novo drug-like molecules. It was proven that candidate molecules designed by DrugEx had a larger chemical diversity, and better covered the chemical space of known ligands. In order to address the issue of polypharmacology, the DrugEx algorithm was updated with multi-objective optimization towards multiple targets. The results of its application demonstrated the generation of compounds with a diverse predicted selectivity profile toward multiple targets, offering the potential of high efficacy and lower toxicity. In order to improve its generality, DrugEx was further updated to have the capability of designing molecules based on given scaffolds. We extended the architecture of Transformer to deal with each molecule as a graph. As a proof, its effectiveness in that 100% valid molecules are generated and most of them had predicted high affinity towards A2AAR with given scaffolds. Moreover, GenUI was developed as a visualizion software platform that makes it possible to integrate molecular generators within a feature-rich graphical user interface to facilitate collaboration in the disparate communities interested in computer-aided drug discovery.These studies highlight the overwhelming power of AI methods in drug discovery. Show less
AimsPlants can influence the level of herbivory experienced by neighboring plants. The importance of such belowground associational effects are poorly understood. In this study we examine whether... Show moreAimsPlants can influence the level of herbivory experienced by neighboring plants. The importance of such belowground associational effects are poorly understood. In this study we examine whether Jacobaea vulgaris provides associational resistance against nematodes to neighboring plants.MethodsThirteen species (6 forbs, 3 grasses and 4 legumes) were each grown in mixtures with J. vulgaris and in monocultures. A nematode community was introduced to half of the pots. After 12 weeks, plant dry mass was assessed for each individual plant in each pot, and the number of nematodes in the soil and roots were identified. We then examined for each plant species its performance in mixtures and in monocultures, in presence and absence of nematodes and analyzed the abundance and composition of nematodes.ResultsForbs produced more, grasses similar, and legumes less biomass in mixtures with J. vulgaris than in monocultures. Nematode addition did not influence biomass. There were fewer root-feeding nematodes in the soil in mixtures than in monocultures, but this was only true for plants that were good hosts for nematodes. The community composition of soil nematodes was different in monocultures and mixtures. Densities of migratory endoparasitic nematodes in the roots of neighboring plants were lower in mixtures than in monocultures. Moreover, the presence of nematodes changed the outcome of plant-plant interactions, often in favor of J. vulgaris.ConclusionsJacobaea vulgaris provides belowground associational resistance to other plants against migratory endoparasitic nematodes, and the presence of nematodes can change the outcome of plant-plant interactions. Show less
Liu, X.; Ye, K.; Vlijmen, H.W.T. van; Emmerich, M.T.M.; IJzerman, A.P.; Westen, G.J.P. van 2021
In polypharmacology drugs are required to bind to multiple specific targets, for example to enhance efficacy or to reduce resistance formation. Although deep learning has achieved a breakthrough in... Show moreIn polypharmacology drugs are required to bind to multiple specific targets, for example to enhance efficacy or to reduce resistance formation. Although deep learning has achieved a breakthrough in de novo design in drug discovery, most of its applications only focus on a single drug target to generate drug-like active molecules. However, in reality drug molecules often interact with more than one target which can have desired (polypharmacology) or undesired (toxicity) effects. In a previous study we proposed a new method named DrugEx that integrates an exploration strategy into RNN-based reinforcement learning to improve the diversity of the generated molecules. Here, we extended our DrugEx algorithm with multi-objective optimization to generate drug-like molecules towards multiple targets or one specific target while avoiding off-targets (the two adenosine receptors, A1AR and A2AAR, and the potassium ion channel hERG in this study). In our model, we applied an RNN as the agent and machine learning predictors as the environment. Both the agent and the environment were pre-trained in advance and then interplayed under a reinforcement learning framework. The concept of evolutionary algorithms was merged into our method such that crossover and mutation operations were implemented by the same deep learning model as the agent. During the training loop, the agent generates a batch of SMILES-based molecules. Subsequently scores for all objectives provided by the environment are used to construct Pareto ranks of the generated molecules. For this ranking a non-dominated sorting algorithm and a Tanimoto-based crowding distance algorithm using chemical fingerprints are applied. Here, we adopted GPU acceleration to speed up the process of Pareto optimization. The final reward of each molecule is calculated based on the Pareto ranking with the ranking selection algorithm. The agent is trained under the guidance of the reward to make sure it can generate desired molecules after convergence of the training process. All in all we demonstrate generation of compounds with a diverse predicted selectivity profile towards multiple targets, offering the potential of high efficacy and low toxicity. Show less
![A rare example of a double metamagnetic transition leading to 2D and 3D long-range order in the two-dimensional pyrazine- and azido-bridged cobalt(ii) compound [Co(pyz)(N3)2]](/sites/all/modules/custom/islandora_solr_search/images/defaultimg.png?solr_nav%5Bid%5D=6848e5b8291f4fb8cea0&solr_nav%5Bpage%5D=0&solr_nav%5Boffset%5D=16)
