Jan is interested in the molecular complexity of cells and how molecular circuits are involved in cell and tissue function. With a background in mouse and Drosophila genetics, he entered the field of biomedical engineering in 2002 and has since focused on understanding and implementing molecular biology in the field of tissue engineering and regenerative medicine. His research is characterized by a holistic approach to both discovery and application, aiming at combining high throughput technologies, computational modeling and experimental cell biology to streamline the wealth of biological knowledge to real clinical applications. His research is defined by strong interdisciplinary collaborations through his big network. He is the former chair of the Netherlands Society for Biomaterials and Tissue Engineering and founder and former chair of the MosaCell platform for patient-derived stem cell research. He brought transcriptomics and computational sciences into his research established a data repository cBIT and his current team comprises both experimental and computational scientists. Jan is a full professor at Biomedical Engineering Department, Eindhoven University of Technology (TU/e), chair of BiS, Biointerface Science in Regenerative Medicine since 2018. He was a founding member of the Merln Institute for Technology-Inspired Regenerative Medicine, Maastricht University and chair of cBITE, Cell Biology Inspired Tissue Engineering Lab between 2014-2018 and worked as an associate professor at the MIRA Institute for Biomedical Technology, University of Twente between 2004-2014.
Sultan is a researcher at Biointerface Science lab since October, 2018. Previosly, she was working as an assistant prof at Ege University, Department of Bioengineering, Cell-Tissue Engineering Lab. With an extensive background on the enhancement of DNA vaccine induced immune responses via antigen engineering, molecular adjuvants and biomaterials, her main research interest is moved towards the overall physiology of dendritic cells to mount a potent immune response while moving towards lymph nodes and priming T cells.orcid.org/0000-0002-9275-6272
Aliaksei keens on the application of data science solutions for biomaterials discovery. Inspired by successes in other areas, he is excited about opportunities that data science can help in novel biomaterials discovery. In his current role, he embarked on a challenge to streamline biomaterials data management to make it ready for knowledge discovery via machine learning. "I discovered my passion for data-science during my bachelor training as a biomedical researcher. To pursue my craving, I explored the application of image analysis and cell screening assays for personalized patient treatment during my Master's thesis and shortly afterward. I obtained a Ph.D. degree in Maastricht University under supervision of the Prof. Jan De Boer. During my training, I extensively applied machine learning approach to understand how biomaterial design affects cell fate."orcid.org/0000-0001-6696-9728
Engineering the tendon fibroblast micro-environment by surface topographies
With a background in Alzheimer genetics, Steven started a PhD in the field of biomedical engineering in 2016 and has since focused on understanding and implementing molecular biology in the field of regenerative medicine. His main focus is to elucidate the mechanobiology of tendon fibroblasts. These cells provide the structural building blocks of tendons and are also involved in tissue regeneration when damage occurs. Tendon repair is however often characterized by scar formation and results in permanently weakened tendon tissue. The incomplete understanding of the underlying biological mechanisms hinders clinicians to provide full medical support. By combining molecular biology techniques and different surface topographies he aims to elucidate the complex interplay between mechanical forces, intracellular pathways and the biochemical responses these provoke. These new insights will allow a better understanding of mesenchymal stem cell differentiation towards this lineage and the subsequent phenotypical maintenance useful in the field of tendon regenerative medicine.
Controlling the tendon fibroblast phenotype by understanding tendon physiology
Ayşegül joined cBITE in February, 2017. In her PhD, she is going to focus on the generation of optimal decellularized 3D scaffolds and application of the mechanical loadings such as stretching to the created scaffolds for mesenchymal stem cells differentiation towards the tendogenic lineage. Further she’s going to investigate the interplay between most optimal surface stiffness, topography, decellularized tendon matrices and mechanical loading that elicit mesenchymal stem cell differentiation towards the tenogenic lineage, and ultimately obtain the ideal tendon transplants. Ideal decellularized 3D scaffolds can eliminate the immune reactions of host tissues to the transplanted tissue which generally happens as a result of native tissue transplants. Moreover, they can be used as ideal transplants since they can reduce the risk or disease transmission from donor to host.
Binary coded, digital biointerfaces – a next generation biomaterials approach with spatially complex subcellular patterns of discrete surface and near-surface properties
In 2009 Urnaa started her bachelor studies in Chemical Engineering at Gazi University (Turkey). During her studies she became interested in material science and started working in the surface chemistry lab. After finishing her bachelor’s degree in 2013, she started her master’s degree in Material Science and Nanotechnology at Bilkent University. During her master she worked on organically modified silica nanostructure based functional surfaces. In 2016 she started a PhD project in Maastricht where she will be developing binary coded digital bio-interfaces with subcellular discrete patterned surfaces using micro- and nanofabrication tools to investigate cell-material interactions.
Image-based computational modelling of cell-topography induced cell behavior
With a background in veterinary medicine, Kerbaï obtained a masters in bioinformatics in 2017 from the University of Leuven, Belgium. His research focus was on using several sigmoidal curve modelling approaches for the improvement qPCR within a DNA methylation screening protocol. He also holds a masters in epidemiology from the Institute of Tropical Medicine in Antwerp, Belgium. There, as he puts it, “his passion for the quantitative aspects life sciences” was ignited. His research aimed at using multiple correspondence analysis for food safety.
He joined cBITE in September 2017 and his research mainly focuses on investigating the spatio-temporal aspects of mechanotransduction pathways via combined life-cell imaging and computational modelling. Computational model validation via several perturbation tests in which specific pharmacological inhibitors are investigated both in-silico and in-vitro, constitutes an important component of his research. It is expected that fundamental insights into the mechanotransduction pathways could lead to controlled interactions at biomaterial-cell interface. Moreover, via optimal topographical design of biomaterial surfaces this could unlock novel opportunities for improved implant surfaces.
I come from southern part of India where I did my bachelors in Biotechnology in 2011. I got interested in the inter disciplinary scope of the field while working at a CRO where I was a part of the project to test active drug efficacy from different phytochemical plant extracts for anti cancerous activity. In 2013, I started my masters in university of Tuebingen (Germany) in biomedical technologies where I took implantology as one of my specialization with focus on biomaterials which really fascinated me. As a part of my thesis I did a project titled “In-vitro evaluation of small molecules for anti microbial activity in Gram negative bacteria” which focuses on the characterisation of active hits from High throughput screening. As a part of my Ph.d, I will be focussing my research in doing High throughput screening of biomaterials in ophthalmology used in treatment of Glaucoma to reduce the intra ocular pressure. The objective of the project is to develop surface topographies with anti-fouling surface properties that can avoid implant failure and fibrous formation.