Utilising computational power to improve drug safety: predicting and understanding tissue selectivity

Increasing tissue selectivity of compounds may aid the development of safer drug treatments by decreasing side effect prevalence. To enable this, improved insight into the mechanisms underlying tissue selectivity is required. In this article the influence of receptor concentration, drug-target affinity and binding kinetics on tissue selectivity is described. Simulations were performed in a physiological model with drug-target binding, informed by in silico predicted physicochemical properties. Lower tissue selectivity was observed for high affinity ligands than for low affinity ligands. This observation moves against the current paradigm in which high affinity ligands are assumed to be better drug candidates

Identifying markers of cell identity from single-cell omics data

Einzelzell-Omics-Daten stehen derzeit im Fokus der Entwicklung computergestützter Methoden in der Molekularbiologie und Genetik. Einzelzellexperimenten lieferen dünnbesetzte, hochdimensionale Daten über zehntausende Gene oder hunderttausende regulatorische Regionen in zehntausenden Zellen. Diese Daten bieten den Forschenden die Möglichkeit, Gene und regulatorische Regionen zu identifizieren, welche die Bestimmung und Aufrechterhaltung der Zellidentität koordinieren. Die gängigste Strategie zur Identifizierung von Zellidentitätsmarkern besteht darin, die Zellen zu clustern und dann Merkmale zu finden, welche die Cluster unterscheiden, wobei davon ausgegangen wird, dass die Zellen innerhalb eines Clusters die gleiche Identität haben. Diese Annahme ist jedoch nicht immer zutreffend, insbesondere nicht für Entwicklungsdaten bei denen sich die Zellen in einem Kontinuum befinden und die Definition von Clustergrenzen biologisch gesehen potenziell willkürlich ist. Daher befasst sich diese Dissertation mit Clustering-unabhängigen Strategien zur Identifizierung von Markern aus Einzelzell-Omics-Daten. Der wichtigste Beitrag dieser Dissertation ist SEMITONES, eine auf linearer Regression basierende Methode zur Identifizierung von Markern. SEMITONES identifiziert (Gruppen von) Markern aus verschiedenen Arten von Einzelzell-Omics-Daten, identifiziert neue Marker und übertrifft bestehende Marker-Identifizierungsansätze. Außerdem ermöglicht die Identifizierung von regulatorischen Markerregionen durch SEMITONES neue Hypothesen über die Regulierung der Genexpression während dem Erwerb der Zellidentität. Schließlich beschreibt die Dissertation einen Ansatz zur Identifizierung neuer Markergene für sehr ähnliche, dennoch underschiedliche neurale Vorlauferzellen im zentralen Nervensystem von Drosphila melanogaster. Ingesamt zeigt die Dissertation, wie Cluster-unabhängige Ansätze zur Aufklärung bisher uncharakterisierter biologischer Phänome aus Einzelzell-Omics-Daten beitragen.Single-cell omics approaches are the current frontier of computational method development in molecular biology and genetics. A single single-cell experiment provides sparse, high-dimensional data on tens of thousands of genes or hundreds of thousands of regulatory regions (i.e. features) in tens of thousands of cells (i.e. samples). This data provides researchers with an unprecedented opportunity to identify those genes and regulatory regions that determine and coordinate cell identity acquisition and maintenance. The most common strategy for identifying cell identity markers consists of clustering the cells and then identifying differential features between these clusters, assuming that cells within a cluster share the same identity. This assumption is, however, not guaranteed to hold, particularly for developmental data where cells lie along a continuum and inferring cluster boundaries becomes non-trivial and potentially biologically arbitrary. In response, this thesis presents clustering-independent strategies for marker feature identification from single-cell omics data. The primary contribution of this thesis is a linear regression-based method for marker feature identification from single-cell omics data called SEMITONES. SEMITONES can identify markers or marker sets from diverse single-cell omics data types, identifies novel markers, outperforms existing marker identification approaches. The thesis also describes how the identification of marker regulatory regions by SEMITONES enables the generation of novel hypotheses regarding gene regulation during cell identity acquisition. Lastly, the thesis describes the clustering-independent identification of novel marker genes for highly similar yet distinct neural progenitor cells in the Drosophila melanogaster central nervous system. Altogether, the thesis demonstrates how clustering-independent approaches aid the elucidation of yet uncharacterised biological patterns from single cell-omics data

Clinical aspects of coagulation monitoring during complex cardiovascular surgery

Complex cardiovascular surgery with extracorporeal circulation fundamentally alters the coagulation process, which has intra- and postoperative implications for the blood management of patients undergoing surgery. In recent years, much research has contributed to a deeper understanding of these changes; at the same time, indications for surgery, surgical techniques, and the spectrum of coagulation monitoring are also evolving. In this context, this thesis describes and investigates the specific aspects of coagulation in this group of high-risk patients with the aim of further optimizing perioperative coagulation management

Staged Parameter Optimisation for a Robotic Bird Model

This paper proposes a method to estimate a nonlinear mathematical model describing the dynamic behaviour of a robotic bird. Established knowledge on aircraft modelling and aerodynamics is used to derive an appropriate model structure. A new parameter optimisation method is developed, which consists of experiment design and staged parameter optimisation using datasets from test flights. The modelling method delivers promising results for predicting pitch and yaw of a model aeroplane and can be applied to the Robird when flight data become available

Access denied : A closer look at anti-phage defense mechanisms

Microorganisms are under constant threat by their viruses, bacteriophages (phages). In response to this pressure, they have developed multiple strategies to protect from phage infection. Mechanisms that protect microorganisms from phage infection include restriction-modification, BREX, DISARM, and CRISPR-Cas systems. However, phages have developed several mechanisms by which they can evade anti-phage defense systems. One common way to evade these systems by phages is by modifying their nucleic acids (DNA). This thesis encompasses the characterization of several CRISPR-Cas and DISARM proteins and studying the effect of phage DNA modifications on the activity of these proteins.</p

Health problems and risks encountered among healthy and vulnerable Dutch travelers

The results described in this thesis expand and deepen the knowledge of the disease burden that several groups of Dutch travelers can face while traveling abroad and after returning home, varying from young medical students to the older traveler⁠. One can think of communicable diseases (e⁠.g⁠. enteric- and respiratory infections), non-communicable diseases (e⁠.g⁠. exacerbation of cardiovascular diseases or mental disorders) and (road-traffic-related) injuries⁠. In addition, travelers can also face non-medical challenges such as culture shock and violence⁠. Travelers can also become colonized with resistant bacteria (e⁠.g⁠. ESBL-E) while staying abroad⁠. Active surveillance and contact isolation precautions may then be recommended when a traveler returns from a destination in Asia, and is admitted to the hospital in the home country⁠. The different studies provide more insights and practical advices regarding pre-travel information, which attributes both to practical tailored travel advice for Dutch travelers and will also be of interest for future research in the evolving world of travel medicine⁠.The printing of this thesis was partly financially supported by ChipSoft B.V.LUMC / Geneeskund

Optimizing Working Space in Laparoscopy: Studies in a porcine model

__Abstract__ Adequate working space is essential for safe and effective laparoscopic surgery. However, the factors that determine working space have not been sufficiently studied. Working space can be very limited, especially in children. A literature review was undertaken to search for factors that can be influenced to increase working space in laparoscopy