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Quaedackers, L.; Gilst, M.M. van; Brandt, I. van den; Vilanova, A.; Lammers, G.J.; Markopoulos, P.; Overeem, S. 2023

The burden of narcolepsy in adults: a population sampling study using personal media

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ABSTRACTObjectiveTo obtain insight in the spectrum of narcolepsy symptoms and associated burden in a large cohort of patients.MethodsWe used the Narcolepsy Monitor,...

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ABSTRACTObjectiveTo obtain insight in the spectrum of narcolepsy symptoms and associated burden in a large cohort of patients.MethodsWe used the Narcolepsy Monitor, a mobile app, to easily rate the presence and burden of 20 narcolepsy symptoms. Baseline measures were obtained and analyzed from 746 users aged between 18 and 75 years with a reported diagnosis of narcolepsy.ResultsMedian age was 33.0 years (IQR 25.0–43.0), median Ullanlinna Narcolepsy Scale 19 (IQR 14.0–26.0), 78% reported using narcolepsy pharmacotherapy. Excessive daytime sleepiness (97.2%) and lack of energy were most often present (95.0%) and most often caused a high burden (79.7% and 76.1% respectively). Cognitive symptoms (concentration 93.0%, memory 91.4%) and psychiatric symptoms (mood 76.8%, anxiety/panic 76.4%) were relatively often reported to be present and burdensome. Conversely, sleep paralysis and cataplexy were least often reported as highly bothersome. Females experienced a higher burden for anxiety/panic, memory, and lack of energy.ConclusionsThis study supports the notion of an elaborate narcolepsy symptom spectrum. Each symptom’s contribution to the experienced burden varied, but lesser-known symptoms did significantly add to this as well. This emphasizes the need to not only focus treatment on the classical core symptoms of narcolepsy.

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Jong, S.E. de; Unen, V. van; Manurung, M.D.; Stam, K.A.; Goeman, J.J.; Jochems, S.P.; ... ; Yazdanbakhsh, M. 2021

Systems analysis and controlled malaria infection in Europeans and Africans elucidate naturally acquired immunity

Article / Letter to editor

open access

Controlled human infections provide opportunities to study the interaction between the immune system and malaria parasites, which is essential for vaccine development. Here, we compared immune... Show moreControlled human infections provide opportunities to study the interaction between the immune system and malaria parasites, which is essential for vaccine development. Here, we compared immune signatures of malaria-naive Europeans and of Africans with lifelong malaria exposure using mass cytometry, RNA sequencing and data integration, before and 5 and 11 days after venous inoculation with Plasmodium falciparum sporozoites. We observed differences in immune cell populations, antigen-specific responses and gene expression profiles between Europeans and Africans and among Africans with differing degrees of immunity. Before inoculation, an activated/differentiated state of both innate and adaptive cells, including elevated CD161(+)CD4(+) T cells and interferon-gamma production, predicted Africans capable of controlling parasitemia. After inoculation, the rapidity of the transcriptional response and clusters of CD4(+) T cells, plasmacytoid dendritic cells and innate T cells were among the features distinguishing Africans capable of controlling parasitemia from susceptible individuals. These findings can guide the development of a vaccine effective in malaria-endemic regions.Malaria immunity can be acquired through natural infection, but the correlates of protection are still being determined. Yazdanbakhsh and colleagues combine experimental infection of volunteers with Plasmodium falciparum with systems analysis to throw light on the nature of protective immune responses. Show less

Pezzotti, N.; Thijssen, J.; Mordvintsev, A.; Hollt, T.; Lew, B. van; Lelieveldt, B.P.F.; ... ; Vilanova, A. 2020

GPGPU linear complexity t-SNE optimization

Article / Letter to editor

open access

In recent years the t-distributed Stochastic Neighbor Embedding (t-SNE) algorithm has become one of the most used and insightful techniques for exploratory data analysis of high-dimensional data.... Show moreIn recent years the t-distributed Stochastic Neighbor Embedding (t-SNE) algorithm has become one of the most used and insightful techniques for exploratory data analysis of high-dimensional data. It reveals clusters of high-dimensional data points at different scales while only requiring minimal tuning of its parameters. However, the computational complexity of the algorithm limits its application to relatively small datasets. To address this problem, several evolutions of t-SNE have been developed in recent years, mainly focusing on the scalability of the similarity computations between data points. However, these contributions are insufficient to achieve interactive rates when visualizing the evolution of the t-SNE embedding for large datasets. In this work, we present a novel approach to the minimization of the t-SNE objective function that heavily relies on graphics hardware and has linear computational complexity. Our technique decreases the computational cost of running t-SNE on datasets by orders of magnitude and retains or improves on the accuracy of past approximated techniques. We propose to approximate the repulsive forces between data points by splatting kernel textures for each data point. This approximation allows us to reformulate the t-SNE minimization problem as a series of tensor operations that can be efficiently executed on the graphics card. An efficient implementation of our technique is integrated and available for use in the widely used Google TensorFlow.js, and an open-source C++ library. Show less

Beyrend, G.; Gracht, E. van der; Yilmaz, A.; Duikeren, S. van; Camps, M.; Hollt, T.; ... ; Ossendorp, F. 2019

PD-L1 blockade engages tumor-infiltrating lymphocytes to co-express targetable activating and inhibitory receptors

Article / Letter to editor

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Background The clinical benefit of immunotherapeutic approaches against cancer has been well established although complete responses are only observed in a minority of patients. Combination... Show moreBackground The clinical benefit of immunotherapeutic approaches against cancer has been well established although complete responses are only observed in a minority of patients. Combination immunotherapy offers an attractive avenue to develop more effective cancer therapies by improving the efficacy and duration of the tumor-specific T-cell response. Here, we aimed at deciphering the mechanisms governing the response to PD-1/PD-L1 checkpoint blockade to support the rational design of combination immunotherapy. Methods Mice bearing subcutaneous MC-38 tumors were treated with blocking PD-L1 antibodies. To establish high-dimensional immune signatures of immunotherapy-specific responses, the tumor microenvironment was analyzed by CyTOF mass cytometry using 38 cellular markers. Findings were further examined and validated by flow cytometry and by functional in vivo experiments. Immune profiling was extended to the tumor microenvironment of colorectal cancer patients. Results PD-L1 blockade induced selectively the expansion of tumor-infiltrating CD4(+) and CD8(+) T-cell subsets, co-expressing both activating (ICOS) and inhibitory (LAG-3, PD-1) molecules. By therapeutically co-targeting these molecules on the T-AI cell subsets in vivo by agonistic and antagonist antibodies, we were able to enhance PD-L1 blockade therapy as evidenced by an increased number of T-AI cells within the tumor micro-environment and improved tumor protection. Moreover, T-AI cells were also found in the tumor-microenvironment of colorectal cancer patients. Conclusions This study shows the presence of T cell subsets in the tumor micro-environment expressing both activating and inhibitory receptors. These T-AI cells can be targeted by combined immunotherapy leading to improved survival. Show less

Beyrend, G.; Gracht, E. van der; Yilmaz, A.; Duikeren, S. van; Camps, M.; Hollt, T.; ... ; Ossendorp, F. 2019

PD-L1 blockade engages tumor-infiltrating lymphocytes to co-express targetable activating and inhibitory receptors

Article / Letter to editor

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Hollt, T.; Vilanova, A.; Pezzotti, N.; Lelieveldt, B.P.F.; Hauser, H. 2019

Focus plus Context Exploration of Hierarchical Embeddings

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Hierarchical embeddings, such as HSNE, address critical visual and computational scalability issues of traditional techniques for dimensionality reduction. The improved scalability comes at the... Show moreHierarchical embeddings, such as HSNE, address critical visual and computational scalability issues of traditional techniques for dimensionality reduction. The improved scalability comes at the cost of the need for increased user interaction for exploration. In this paper, we provide a solution for the interactive visual Focus+Context exploration of such embeddings. We explain how to integrate embedding parts from different levels of detail, corresponding to focus and context groups, in a joint visualization. We devise an according interaction model that relates typical semantic operations on a Focus+Context visualization with the according changes in the level-of-detail-hierarchy of the embedding, including also a mode for comparative Focus+Context exploration and extend HSNE to incorporate the presented interaction model. In order to demonstrate the effectiveness of our approach, we present a use case based on the visual exploration of multi-dimensional images. Show less

Laban, S.; Suwandi, J.S.; Unen, V. van; Pool, J.; Wesselius, J.; Hollt, T.; ... ; Roep, B.O. 2018

Heterogeneity of circulating CD8 T-cells specific to islet, neo-antigen and virus in patients with type 1 diabetes mellitus

Article / Letter to editor

open access

Pezzotti, N.; Fekete, J.D.; Hollt, T.; Lelieveldt, B.P.F.; Eisemann, E.; Vilanova, A. 2018

Multiscale Visualization and Exploration of Large Bipartite Graphs

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Pezzotti, N.; Fekete, J.D.; Hollt, T.; Lelieveldt, B.P.F.; Eisemann, E.; Vilanova, A. 2018

Multiscale Visualization and Exploration of Large Bipartite Graphs

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A bipartite graph is a powerful abstraction for modeling relationships between two collections. Visualizations of bipartite graphs allow users to understand the mutual relationships between the... Show moreA bipartite graph is a powerful abstraction for modeling relationships between two collections. Visualizations of bipartite graphs allow users to understand the mutual relationships between the elements in the two collections, e.g., by identifying clusters of similarly connected elements. However, commonly-used visual representations do not scale for the analysis of large bipartite graphs containing tens of millions of vertices, often resorting to an a-priori clustering of the sets. To address this issue, we present the Who's-Active-On-What-Visualization (WAOW-Vis) that allows for multiscale exploration of a bipartite social-network without imposing an a-priori clustering. To this end, we propose to treat a bipartite graph as a high-dimensional space and we create the WAOW-Vis adapting the multiscale dimensionality-reduction technique HSNE. The application of HSNE for bipartite graph requires several modifications that form the contributions of this work. Given the nature of the problem, a set-based similarity is proposed. For efficient and scalable computations, we use compressed bitmaps to represent sets and we present a novel space partitioning tree to efficiently compute similarities; the Sets Intersection Tree. Finally, we validate WAOW-Vis on several datasets connecting Twitter-users and -streams in different domains: news, computer science and politics. We show how WAOW-Vis is particularly effective in identifying hierarchies of communities among social-media users. Show less

Li, N.; Unen, V. van; Hollt, T.; Thompson, A.; Bergen, J. van; Pezzotti, N.; ... ; Koning, F. 2018

Mass cytometry reveals innate lymphoid cell differentiation pathways in the human fetal intestine

Article / Letter to editor

open access

Abdelmoula, W.M.; Pezzotti, N.; Holt, T.; Dijkstra, J.; Vilanova, A.; McDonnell, L.A.; Lelieveldt, B.P.F. 2018

Interactive Visual Exploration of 3D Mass Spectrometry Imaging Data Using Hierarchical Stochastic Neighbor Embedding Reveals Spatiomolecular Structures at Full Data Resolution

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Abdelmoula, W.M.; Pezzotti, N.; Holt, T.; Dijkstra, J.; Vilanova, A.; McDonnell, L.A.; Lelieveldt, B.P.F. 2018

Interactive Visual Exploration of 3D Mass Spectrometry Imaging Data Using Hierarchical Stochastic Neighbor Embedding Reveals Spatiomolecular Structures at Full Data Resolution

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Pezzotti, N.; Hollt, T.; Gemert, J. van; Lelieveldt, B.P.F.; Eisemann, E.; Vilanova, A. 2018

DeepEyes: Progressive Visual Analytics for Designing Deep Neural Networks

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Hollt, T.; Pezzotti, N.; Unen, V. van; Koning, F.; Lelieveldt, B.P.F.; Vilanova, A. 2018

CyteGuide: Visual Guidance for Hierarchical Single-Cell Analysis

Article / Letter to editor

open access

Pezzotti, N.; Hollt, T.; Gemert, J. van; Lelieveldt, B.P.F.; Eisemann, E.; Vilanova, A. 2018

DeepEyes: Progressive Visual Analytics for Designing Deep Neural Networks

Article in monograph or in proceedings

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Deep neural networks are now rivaling human accuracy in several pattern recognition problems. Compared to traditional classifiers, where features are handcrafted, neural networks learn increasingly... Show moreDeep neural networks are now rivaling human accuracy in several pattern recognition problems. Compared to traditional classifiers, where features are handcrafted, neural networks learn increasingly complex features directly from the data. Instead of handcrafting the features, it is now the network architecture that is manually engineered. The network architecture parameters such as the number of layers or the number of filters per layer and their interconnections are essential for good performance. Even though basic design guidelines exist, designing a neural network is an iterative trial-and-error process that takes days or even weeks to perform due to the large datasets used for training. In this paper. we present DeepEyes, a Progressive Visual Analytics system that supports the design of neural networks during training. We present novel visualizations, supporting the identification of layers that learned a stable set of patterns and, therefore, are of interest for a detailed analysis. The system facilitates the identification of problems, such as superfluous filters or layers, and information that is not being captured by the network. We demonstrate the effectiveness of our system through multiple use cases, showing how a trained network can be compressed, reshaped and adapted to different problems. Show less

Laban, S.; Suwandi, J.S.; Unen, V. van; Pool, J.; Wesselius, J.; Hollt, T.; ... ; Roep, B.O. 2018

Heterogeneity of circulating CD8 T-cells specific to islet, neo-antigen and virus in patients with type 1 diabetes mellitus

Article / Letter to editor

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Auto-reactive CD8 T-cells play an important role in the destruction of pancreatic β-cells resulting in type 1 diabetes (T1D). However, the phenotype of these auto-reactive cytolytic CD8 T-cells... Show moreAuto-reactive CD8 T-cells play an important role in the destruction of pancreatic β-cells resulting in type 1 diabetes (T1D). However, the phenotype of these auto-reactive cytolytic CD8 T-cells has not yet been extensively described. We used high-dimensional mass cytometry to phenotype autoantigen- (pre-proinsulin), neoantigen- (insulin-DRIP) and virus- (cytomegalovirus) reactive CD8 T-cells in peripheral blood mononuclear cells (PBMCs) of T1D patients. A panel of 33 monoclonal antibodies was designed to further characterise these cells at the single-cell level. HLA-A2 class I tetramers were used for the detection of antigen-specific CD8 T-cells. Using a novel Hierarchical Stochastic Neighbor Embedding (HSNE) tool (implemented in Cytosplore), we identified 42 clusters within the CD8 T-cell compartment of three T1D patients and revealed profound heterogeneity between individuals, as each patient displayed a distinct cluster distribution. Single-cell analysis of pre-proinsulin, insulin-DRIP and cytomegalovirus-specific CD8 T-cells showed that the detected specificities were heterogeneous between and within patients. These findings emphasize the challenge to define the obscure nature of auto-reactive CD8 T-cells. Show less

Li, N.; Unen, V. van; Hollt, T.; Thompson, A.; Bergen, J. van; Pezzotti, N.; ... ; Koning, F. 2018

Mass cytometry reveals innate lymphoid cell differentiation pathways in the human fetal intestine

Article / Letter to editor

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Innate lymphoid cells (ILCs) are abundant in mucosal tissues and involved in tissue homeostasis and barrier function. Although several ILC subsets have been identified, it is unknown if additional... Show moreInnate lymphoid cells (ILCs) are abundant in mucosal tissues and involved in tissue homeostasis and barrier function. Although several ILC subsets have been identified, it is unknown if additional heterogeneity exists, and their differentiation pathways remain largely unclear. We applied mass cytometry to analyze ILCs in the human fetal intestine and distinguished 34 distinct clusters through a t-SNE-based analysis. A lineage (Lin)-CD7+CD127-CD45RO+CD56+ population clustered between the CD127+ ILC and natural killer (NK) cell subsets, and expressed diverse levels of Eomes, T-bet, GATA3, and RORγt. By visualizing the dynamics of the t-SNE computation, we identified smooth phenotypic transitions from cells within the Lin-CD7+CD127-CD45RO+CD56+ cluster to both the NK cells and CD127+ ILCs, revealing potential differentiation trajectories. In functional differentiation assays, the Lin-CD7+CD127-CD45RO+CD56+CD8a- cells could develop into CD45RA+NK cells and CD127+RORγt+ ILC3-like cells. Thus, we identified a previously unknown intermediate innate subset that can differentiate into ILC3 and NK cells. Show less

Unen, V. van; Hollt, T.; Pezzotti, N.; Li, N.; Reinders, M.J.T.; Eisemann, E.; ... ; Lelieveldt, B.P.F. 2017

Visual analysis of mass cytometry data by hierarchical stochastic neighbour embedding reveals rare cell types

Article / Letter to editor

open access

Pezzotti, N.; Lelieveldt, B.P.F.; Maaten, L. van der; Hollt, T.; Eisemann, E.; Vilanova, A. 2017

Approximated and User Steerable tSNE for Progressive Visual Analytics

Article / Letter to editor

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Zhang, C.; Caan, M.W.A.; Hollt, T.; Eisemann, E.; Vilanova, A. 2017

Overview plus Detail Visualization for Ensembles of Diffusion Tensors

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