Five 20k grants for cross-campus bioengineering research projects
Since 2020, Delft Bioengineering Institute (BEI) organizes a cross-campus call for interdisciplinary research projects in the field of bioengineering. This year, nine teams of BEI PIs sent in a proposal. A peer review by the submitting PIs themselves resulted in the following five excellent projects, that will each be granted with €20.000 by Delft Bioengineering Institute.
>> Shark-skin inspired lattice structure for drag reduction
Shark skin is covered in thousands of tooth-like denticles or scales, which help the fish move efficiently through the water, and it may be useful to cover boats with a shark-skin inspired layer. But despite numerous studies on the functional significance of shark denticles, a couple of questions remain unanswered. Therefore, Aimée Sakes (3mE/Biomechanical Engineering), Sepideh Ghodrat (IO/Sustainable Design Engineering) and Jovana Jovanova (3mE/Maritime and Transport Technology) will join forces to further the understanding the effect of shark denticle morphology, stacking, and anchoring on the drag reducing and lift increasing properties of the shark skin.
Project title: Shark-Skin Inspired Lattice Structure for Drag Reduction
BEI PIs: Aimée Sakes (3mE/Biomechanical Engineering), Sepideh Ghodrat (IO/Sustainable Design Engineering), Jovana Jovanova (3mE/Maritime and Transport Technology)
>> Observing DNA-binding kinetics at base-pair resolution
Knowledge on human diseases is strongly based on knowledge of the kinetics of individual DNA-binding proteins and associated metabolism, like replication, repair, and transcription. Unfortunately, these dynamic and fluctuating processes are challenging to effectively study. Many existing technologies are either difficult to implement, require clean-room facilities, or have complex protocols to manipulate DNA strands in a serial manner. In this project, Nynke Dekker (TNW/Bionanoscience) and Carlas Smith (3mE/Delft Center for Systems and Control) will team up to design a simple device that can be used to quickly observe multiple DNA-binding processes over a large sample, using a micro-structured surface and SIMFLUX-TIRF microscopy.
Project title: Micro-structured substrate with SIM-TIRF microscopy for highly selective, high throughput observation of DNA-binding kinetics at base-pair resolution
BEI PIs: Nynke Dekker (TNW/Bionanoscience), Carlas Smith (3mE/Delft Center for Systems and Control)
>> Physics-informed neural networks for biochemical engineering
With the retreat of fossil resources, bio-based materials are increasingly important. However, industrial bioprocesses to make these materials still suffer problems, such as reliable scale-up and maximization of resource efficiency. More and more, computational fluid dynamics (CFD) is used to support scale-up and reduce uncertainty, but current models are incapable of capturing part of the physics relevant for bioprocesses. In their previously granted BEI MSc project proposal, Cees Haringa (TNW/Biotechnology), Jochen Cremer (EWI/Electrical Sustainable Energy) and Artur Schweidtmann (TNW/Chemical Engineering) study the use of the new machine learning method - physics-informed neural networks (PINNs) – to improve the speed of bioprocess simulations. This preliminary study shows promise, with expected speed-gains in several order of magnitudes. Therefore, in the current proposed work, the PIs will focus on the physical relevance of the model, using a combination of experimental techniques to probe the hydrodynamics of complex bioreactor systems, and explore the use of PINNS to bridge the gap between model and experiment. They aim to improve the physical agreement of bioprocess simulations, and showcase the value of PINNs in the context of bioprocess engineering.
Project title: Physics-Informed Neural Networks for Biochemical Engineering
BEI PIs: Cees Haringa (TNW/Biotechnology), Jochen Cremer (EWI/Electrical Sustainable Energy), Artur Schweidtmann (TNW/Chemical Engineering)
>> Unravelling the biophysical mechanisms of cancer cell invasion
Over 90% of cancer-related deaths are caused by cancer metastasis, and cancer cell migration into the surrounding extracellular matrices and tumor-microenvironment is a critical step at its early stages. While much is known about the molecular basis of cancer cell invasion, the biophysical mechanisms behind cancer invasion remain elusive. To fill this gap, Pouyan Boukany (TNW/Chemical Engineering) and Lisanne Rens (EWI/Delft Institute of Applied Mathematics) will combine microfluidics modeling of metastasis and computational modeling in collective cell migration. A better understanding of the underlying biophysical mechanisms of cancer invasion will ultimately lead to better treatment of metastatic cancer.
Project title: Unravelling the biophysical mechanisms of cancer cell invasion through complex microenvironments by combining microfluidics and computational modelling
BEI PIs: Pouyan Boukany (TNW/Chemical Engineering), Lisanne Rens (EWI/Delft Institute of Applied Mathematics)
>> Improving artificial retinas to treat vision disorders
Electrical neuro-stimulation is a promising therapeutic for many diseases and disorders resulting from neural dysfunctions. In this project, Dante Muratore (EWI/Microelectronics) and Sérgio Pequito (3mE/Delft Center for Systems and Control) will focus on technology for a retinal prosthesis for treatment of vision disorders using a calibrated bidirectional interface. One of the challenges of bidirectional interfaces is that, by injecting charge through the large electrode-tissue interface impedance, a large artifact obscures the neural activity that they want to record for calibration. This problem, known as ‘stimulation artifact’, has been addressed by the PIs since the fall of 2020. Combining Dante’s experience in circuits for neural interfaces and artifact mitigation through preventive methods, and Sérgio’s expertise in back-end techniques due to his background in dynamical systems, the PIs have already validated the results of their efforts in-silico. With this project, they aim for an in-vitro validation to obtain preliminary data and validation of the proposed methodology.
Project title: Multi-channel Artifact Reduction on the Edge for a Bidirectional High-Resolution Artificial Retina
BEI PIs: Dante Muratore (EWI/Microelectronics), Sérgio Pequito (3mE/DCSC)