Brain pretargeted nuclear imaging for the diagnosis of various neurodegenerative diseases is a quickly developing field. The tetrazine ligation is currently the most explored approach to achieve... Show moreBrain pretargeted nuclear imaging for the diagnosis of various neurodegenerative diseases is a quickly developing field. The tetrazine ligation is currently the most explored approach to achieve this goal due to its remarkable properties. In this work, we evaluated the performance of F-537-Tetrazine, previously developed by Biogen, and N-(3-[18F]fluoro-5-(1,2,4,5-tetrazin-3-yl)benzyl)propan-1-amine, previously developed in our group, thereby allowing for the direct comparison of these two imaging probes. The evaluation included synthesis, radiolabeling and a comparison of the physicochemical properties of the compounds. Furthermore, their performance was evaluated by in vitro and in vivo pretargeting models. This study indicated that N-(3-[18F] fluoro-5-(1,2,4,5-tetrazin-3-yl)benzyl)propan-1-amine might be more suited for brain pretargeted imaging. Show less
BackgroundThe 2022 consensus statement of the European Atherosclerosis Society (EAS) on lipoprotein(a) (Lp(a)) recognizes the role of Lp(a) as a relevant genetically determined risk factor and... Show moreBackgroundThe 2022 consensus statement of the European Atherosclerosis Society (EAS) on lipoprotein(a) (Lp(a)) recognizes the role of Lp(a) as a relevant genetically determined risk factor and recommends its measurement at least once in an individual's lifetime. It also strongly urges that Lp(a) test results are expressed as apolipoprotein (a) (apo(a)) amount of substance in molar units and no longer in confounded Lp(a) mass units (mg/dL or mg/L). Therefore, IVD manufacturers should transition to molar units. A prerequisite for this transition is the availability of an Lp(a) Reference Measurement Procedure (RMP) that allows unequivocal molecular detection and quantification of apo(a) in Lp(a). To that end an ISO 17511:2020 compliant LC-MS based and IFCC-endorsed RMP has been established that targets proteotypic peptides of apolipoprotein(a) (apo(a)) in Lp(a). The RMP is laborious and requires highly skilled operators. To guide IVD-manufacturers of immunoassay-based Lp(a) test kits in the transition from mass to molar units, a Designated Comparison Method (DCM) has been developed and evaluated.MethodsTo assess whether the DCM provides equivalent results compared to the RMP, the procedural designs were compared and the analytical performance of DCM and RMP were first evaluated in a head-to-head comparison. Subsequently, apo(a) was quantified in 153 human clinical serum samples. Both DCM and RMP were calibrated using external native calibrators that produce results traceable to SRM2B. Measurement uncertainty (MU) was checked against predefined allowable MU.ResultsThe major difference in the design of the DCM for apo(a) is the use of only one enzymatic digestion step. The analytical performance of the DCM and RMP for apo(a) is highly similar. In a direct method comparison, equivalent results were obtained with a median regression slope 0.997 of and a median bias of - 0.2 nmol/L (- 0.2%); the intermediate imprecision of the test results was within total allowable error (TEa) (CVa of 10.2% at 90 nmol/L).ConclusionsThe semi-automated, higher throughput, LC-MS-based method for Lp(a) meets the predefined analytical performance specifications and allowable MU and is hence applicable as a higher order Designated Comparison Method, which is ideally suited to guide IVD manufacturers in the transition from Lp(a) mass to molar units. Show less
Senjor, E.; Pirro, M.; Svajger, U.; Prunk, M.; Sabotic, J.; Jewett, A.; ... ; Kos, J. 2024
Cystatin F, a cysteine peptidase inhibitor, is a potent modulator of NK cytotoxicity. By inhibiting granule-mediated cytotoxicity pathway, cystatin F induces formation of non-functional NK cell... Show moreCystatin F, a cysteine peptidase inhibitor, is a potent modulator of NK cytotoxicity. By inhibiting granule-mediated cytotoxicity pathway, cystatin F induces formation of non-functional NK cell stage, called split-anergy. We show that N-glycosylation determines the localization and cellular function of cystatin F. Cystatin F mostly exhibited high-mannose glycosylation in U-937 cells, both high-mannose and complex glycosylation in NK-92 and primary NKs, and predominantly complex glycosylation in super-charged NKs. Manipulating N-glycosylation with kifunensine increased high-mannose glycosylation of cystatin F and lysosome localisation, which decreased cathepsin C activity and reduced NK cytotoxicity. Mannose-6-phosphate could significantly reduce the internalization of extracellular cystatin F. By comparing NK cells with different cytotoxic potentials, we found that high-mannose cystatin F was strongly associated with lysosomes and cathepsin C in NK-92 cell line. In contrast, in highly cytotoxic super-charged NKs, cystatin F with complex glycosylation was associated with the secretory pathway and less prone to inhibit cathepsin C. Modulating glycosylation to alter cystatin F localisation could increase the cytotoxicity of NK cells, thereby enhancing their therapeutic potential for treating cancer patients. Show less
Previous studies have demonstrated the common occurrence of constituency focus in parliamentary questions, which is most often attributed to electoral incentives. If an electoral system makes use... Show morePrevious studies have demonstrated the common occurrence of constituency focus in parliamentary questions, which is most often attributed to electoral incentives. If an electoral system makes use of a single nationwide district, however, these district-oriented electoral incentives do not apply. MPs may still substantively represent a geographical region, because they are motivated to stand up for a specific region for other reasons. This article explores the extent to which Dutch MPs pay attention in parliamentary questions and debates to specific regions. We find that those with stronger ties to a region, and especially MPs who reside in a region, are more likely to mention it in parliamentary questions and speeches. In addition, we find that this effect is stronger for provinces where regional attachment among residents is relatively stronger. Show less
Baca, M.; Popović, D.; Agadzhanyan, A.K.; Baca, K.; Conard, N.J.; Fewlass, H.; ... ; Nadachowski, A. 2024
The narrow-headed vole, collared lemming and common vole were the most abundant small mammal species across the Eurasian Late Pleistocene steppe-tundra environment. Previous ancient DNA studies of... Show moreThe narrow-headed vole, collared lemming and common vole were the most abundant small mammal species across the Eurasian Late Pleistocene steppe-tundra environment. Previous ancient DNA studies of the collared lemming and common vole have revealed dynamic population histories shaped by climatic fluctuations. To investigate the extent to which species with similar adaptations share common evolutionary histories, we generated a dataset comprised the mitochondrial genomes of 139 ancient and 6 modern narrow-headed voles from several sites across Europe and northwestern Asia covering approximately the last 100 thousand years (kyr). We inferred Bayesian time-aware phylogenies using 11 radiocarbon-dated samples to calibrate the molecular clock. Divergence of the main mtDNA lineages across the three species occurred during marine isotope stages (MIS) 7 and MIS 5, suggesting a common response of species adapted to open habitat during interglacials. We identified several time-structured mtDNA lineages in European narrow-headed vole, suggesting lineage turnover. The timing of some of these turnovers was synchronous across the three species, allowing us to identify the main drivers of the Late Pleistocene dynamics of steppe- and cold-adapted species. Show less
Oratie uitgesproken door Prof. Dr. Suzan Verberne bij de aanvaarding van het ambt van hoogleraar Natural Language Processing aan de Universiteit Leiden op maandag 3 juni 2024_______________________... Show moreOratie uitgesproken door Prof. Dr. Suzan Verberne bij de aanvaarding van het ambt van hoogleraar Natural Language Processing aan de Universiteit Leiden op maandag 3 juni 2024____________________________________________________________Text also in English : Is the search engine of the future a chatbot? Show less
Background: Measures against COVID-19 in nursing homes affected not only clients but also staff. However, staff perspectives on the importance of these measures remain underexplored. Objective: To... Show moreBackground: Measures against COVID-19 in nursing homes affected not only clients but also staff. However, staff perspectives on the importance of these measures remain underexplored. Objective: To investigate measures related to staff during the COVID-19 pandemic, staff perspectives of important measures and the involvement of staff in deciding on these measures. Design: A qualitative study. Setting(s): We analysed minutes of nursing home outbreak teams in the Netherlands and conducted group meetings with Dutch nursing home staff in different positions, prioritizing measures and discussing staff' involvement in deciding on the measures. Participants were recruited purposefully. Participants: The minutes of 41 nursing home organizations were collected during March-November, 2020. Four group meetings were organized in the same period, each with 5 to 7 participants, resulting in 23 participants. Methods: The meeting minutes were analysed using qualitative content analysis, whereas reflexive thematic analysis was used for the group meeting data. The group meetings were conducted online and structured by the Nominal Group Technique to discuss the importance of measures for staff. Results: Measures implemented for staff focused on prevention of COVID-19 transmission, (suspension of) educational activities, testing, additional tasks and staffing capacity, promoting wellbeing, and other means of support. The implemented measures overlapped with the measures considered important by staff. In addition, staff considered measures on decision-making support and communication to be important. Staff prioritized the measures in the group meetings because they affected their well-being, workforce scheduling, decision-making, or infection prevention. Furthermore, the group meetings revealed that decision-making shifted from mainly implementing national measures to more context-adjusted decision-making in the staff's or clients' situations. Conclusions: We showed that although nursing home staff were not always involved in decisionmaking during the first COVID-19 wave, there was overlap between the measures implemented by the organizations and measures considered important by staff. We suggest that organizations Show less
Predicting the development of rheumatoid arthritis (RA) in an early stage through magnetic resonance imaging (MRI) can initiate timely treatment and improve long-term patient outcomes. Although... Show morePredicting the development of rheumatoid arthritis (RA) in an early stage through magnetic resonance imaging (MRI) can initiate timely treatment and improve long-term patient outcomes. Although manual prediction is time-consuming and requires expert knowledge, automatic RA prediction has not been fully investigated. While standard models fail to achieve acceptable performance, we present a consistency-based deep learning framework to classify and predict RA automatically and precisely, including an output-standardized model, customized self-supervised pretraining and a loss function that is based on label consistency between original and augmented inputs. For training and evaluation, we used a database, containing 5945 MRI scans of carpal, metacarpophalangeal (MCP), and metatarsophalangeal (MTP) joints, from 2151 subjects obtained over a period of ten years. Four (three classification- and one prediction-) tasks were defined to distinguish two patient groups (with recent-onset arthritis and clinically suspect arthralgia) from healthy controls and RA from other arthritis patients within the recent-onset arthritis group, and predict RA development in a period of two years within the clinically suspect arthralgia group. The proposed method was evaluated with the area under the receiver operating curve (AUROC) on a separate test set, achieving mean AUROCs of 83.6%, 83.3%, and 69.7% in the three classification tasks, and 67.8% in the prediction task. This proves the existence of early signs of RA in MRI and the potential of a consistency-based deep learning model to detect these early signs and predict RA Show less
Rede uitgesproken door Prof. dr. Anton Jan van Zonneveld ter gelegenheid van zijn afscheid als hoogleraarNierziekten, in het bijzonder de experimentele vasculaire geneeskunde aan de Universiteit... Show moreRede uitgesproken door Prof. dr. Anton Jan van Zonneveld ter gelegenheid van zijn afscheid als hoogleraarNierziekten, in het bijzonder de experimentele vasculaire geneeskunde aan de Universiteit Leiden op vrijdag 31 mei 2024 Show less
Time-series forecasting through modelling sequences of temporally dependent observations has many industrial and scientific applications. While machine learning models have been widely used to... Show moreTime-series forecasting through modelling sequences of temporally dependent observations has many industrial and scientific applications. While machine learning models have been widely used to create time-series forecasting models, creating efficient and performant time-series forecasting models is a complex task for domain users. Automated Machine Learning (AutoML) is a growing field that aims to make the process of creating machine-learning models accessible for non-machine learning experts. This is achieved by optimising machine learning pipelines automatically. Time-series machine-learning pipelines include various specialised pre-processing steps that are not currently supported by existing AutoML systems. This dissertation investigates how AutoML can be extended to time-series data analysis problems such as time-series forecasting. Several challenges arise when developing specialised AutoML systems for time-series forecasting. For instance, advanced machine-learning pipelines that can extract time-series features and select well-suited machine-learning models need to be developed. Also, extra hyperparameters such as the window size, which shows how many historical data points are helpful, need to be optimised by the AutoML system. This dissertation addresses these issues. We provide a comprehensive overview of the AutoML research field, including hyperparameter optimisation techniques, neural architecture search, and existing AutoML systems. Next, we investigate the use of AutoML for short-term forecasting, single-step ahead time-series forecasting, and multi-step time-series forecasting with time-series features. Show less
This thesis contains several investigations into the contribution of complement proteins, especially C1q, in several human diseases. Additionally, human autoantibodies against C1q (anti-C1q) are... Show moreThis thesis contains several investigations into the contribution of complement proteins, especially C1q, in several human diseases. Additionally, human autoantibodies against C1q (anti-C1q) are studied, cloned and characterized in order to further the understanding of their role in autoimmune disease. Show less
The decision for immediate breast reconstruction after mastectomy is a preference-sensitive decision. For preference-sensitive decisions, shared decision making is propagated, but not yet properly... Show moreThe decision for immediate breast reconstruction after mastectomy is a preference-sensitive decision. For preference-sensitive decisions, shared decision making is propagated, but not yet properly implemented. Furthermore, prior studies identified unmet decision support needs in women considering breast reconstruction. With this thesis we aimed to optimally support women in making an informed decision about breast reconstruction. For this purpose, we developed an online patient decision aid (pDA) for breast cancer patients considering immediate breast reconstruction after mastectomy. This thesis describes the development and evaluation of this pDA. In our multicenter randomized controlled trial including 250 participants, we found that women who used the pDA felt better prepared for decision making, than women who received usual care. Other outcomes did not differ between both groups. Show less
