Completed projects

Degenerative diseases like osteoarthritis affect millions of people worldwide. Hybrid hydrogels show great promise in tissue engineering applications as scaffolds for supporting native cartilage that is damaged from arthritis. Such gels can be designed and synthesized to be biocompatible and have outstanding mechanical properties, approaching the remarkable behavior associated with native tissue. However, further improvement in function in the sense of promoting tissue regeneration is needed. Previous work has shown that (poly)peptide-polymer conjugates can be tailored to promote cellular interaction. Integrating peptides into hybrid hydrogels in a controlled manner remains a formidable challenge. This is particularly true in gels that exhibit stimuli-responsive behavior (e.g., triggered gelation) and are thus amenable to relevant processing such as injection and 3D bioprinting. All this must be achieved while also maintaining the necessary mechanical properties to support normal tissue function. This project addresses hydrogel design using an adaptable hybrid, dual network synthetic scaffold whereby the building blocks are functionalized for specific attachment to peptides. The mechanical properties will be tuned to match those of native cartilage and the processing and cellular interactions will be probed at the later stages of the Ph.D.

This project focusses on the use of the renewable, promising and abundant phenolic lignin biopolymer in the development of self-healing hydrogels with applications in the (bio)medical field. The pulping industry generates huge amounts of lignin as by-product, however, the majority is incinerated to recover bioenergy. Since lignin has a complex and yet not fully understood structure, it is not directly used as a high value reagent. This project will focus on the depolymerisation of lignin to obtain oligolignin which will undergo hydroxyalkylation followed by reversible boronate ester formation to finally obtain a self-healing oligomeric lignin-based hydrogel. 

Continuous flow technology enables the synthesis of various complex organic chemicals (e.g. pharmaceuticals) with greatly improved efficiency compared with conventional multi-step batch synthesis. Translation of continuous flow principles to emerging polymerization techniques is still in its infancy. This is particularly true for novel photomediated polymerization protocols, whose fundamental process–reactivity relationships have only recently begun to be explored. As momentum builds in the field of controlled photopolymerizations of (cyclic) olefins and (cyclic) esters, a systematic merging of these approaches will enable access to structurally unique macromolecules. The aim of this project is to develop a fundamental understanding of how the process of state-of-the-art reactor technology for continuous flow polymerization influences polymer composition, topology, and function. This scalable technology will be explored for the process intensification of novel controlled photo-mediated polymerizations employing several orthogonal mechanisms including reversible deactivation radical polymerization (RDRP), ring-opening transesterification polymerization (ROTEP) and ring-opening metathesis polymerization (ROMP). Photomediated chemistry related to these various mechanisms remains at the forefront of current trends. They are ripe for further development, with high impact throughout the polymer community.

Ovarian cancer (OC), of which the incidence increases with age, ranks fifth in cancer deaths among women. The common symptoms of OC are indistinct and similar to other benign observations. Most women are therefore diagnosed at an advanced stage III or IV of the disease, at which the 5-year relative survival rate is low (around 39% for stage III and only 17% for stage IV). Serum biomarkers may offer new possibilities to diagnose OC at an early stage. In this project, several nanobodies (Nbs) specifically targeting OC biomarkers are evaluated based on their expression level as well as their target binding affinity. The best candidates will be site-specifically alkynated at their C-terminus using the Expressed protein ligation (EPL) technique and will  subsequently coupled to  to sensor platforms at which all nanobodies are covalently be coupled to sensor surfaces with a unique and uniform orientation, allowing optimal target binding and resulting in improved sensitivity and selectivity.

Introduction: Precision medicine relies on validated biomarkers that can accurately classify patients by their probable disease risk, prognosis and/or response to treatment. Metabolomics is particularly promising for biomarker development because altered metabolism is considered a hallmark of cancer. The measurement of the metabolomic plasma profile is cheap (+-50 EUR) and fast (+-17 min), with a high information throughput on a per sample base.

Rationale: Complete resection is the mainstay of treatment for resectable non-small cell lung cancer (NSCLC). However, rates of recurrence of disease are high, with five-year survival rates ranging between 73% (stage IA) and 24% (stage IIIA). Therefore, a predictive biological marker that stratifies between NSCLC patients whom surgery cures, versus patients with early disease relapse after surgery, is eagerly awaited.

Study objective: The primary study hypothesis is that the metabolic plasma profile is a predictive marker of early disease progression after complete surgical resection in patients with pathological stages I to IIIA NSCLC. The secondary study hypothesis is that the level of dissimilarity between the metabolic profile before surgery and the metabolic profile after surgery, is a predictor for disease recurrence (in which the extreme case would be, that a normalisation of the metabolic profile to the profile of a healthy person, is indicative of a good prognosis).