Implant associated infections can result in inflammatory conditions such as periimplantitis, that can ultimately lead to implant loss. This is caused by a large community of bacterial species. These bacteria form a multispecies biofilm on the tooth surface. Its composition can shift as it matures over time, the so-called pathogenic shift occurs once pathogens adhere to the biofilm.
We developed a measurement protocol and analysis pipeline based on ATR-FTIR spectroscopy that is able to distinguish between different oral bacteria by detecting slight changes in protein expression. This can easily be done for single species samples with supervised learning algorithms like the k-nearest neighbour algorithm, with which we achieved a prediction accuracy of 99.8 %. Chemometric and deep learning approaches can streamline the process in distinguishing multispecies samples. This would be a step towards early detection of the pathogenic shift in oral biofilms and help avoiding diseases.
Microfluidic systems facilitate the realization of compact and miniaturized lab-on-a-chip systems which can be used for various applications. The conventional method to fabricate such devices entails the use of complex etching processes in clean rooms and soft lithography methods which require substantial expertise. Since the design of such microfluidic devices is often customized depending on the application of the user, it would be ideal to have a fabrication technique that would allow for fast and reliable production with the possibility to generate high resolution three-dimensional structures using different materials. 3D printing technique has been recently demonstrated as a means to fabricate microfluidic devices. It enables rapid prototyping of robust and complex structures. Nowadays, 3D printers can create small structures down to several tens of microns. 3D-printed devices can also provide lab-on-a-chip systems which are compatible with optical techniques and microscopy. In this work, we demonstrate the integration of optical manipulation in 3D-printed microfluidic systems with particular focus on optimized design and fabrication protocol. 3D printing was performed using a Multijet printer (MJP2500 Plus). A microfluidic chip was designed for the purpose of dual beam optical trapping and optical stretching of mammalian cells. Three inlets with channel dimensions of 500 µm were used to flow buffer, particles or cells into the device. Two single mode fibers were inserted into fiber guide channels with dimensions of 500 µm, separated with a distance of 300 µm, in order to deliver counterpropagating beams into the trapping region. Hydrodynamic focusing was performed showing that laminar flow can be achieved in the device. In order to evaluate the compatibility of 3D-printed microfluidic chips for optical manipulation, the mean square displacement of the optically trapped 10 µm polystyrene particle was measured for different laser powers. In addition, we demonstrate optical stretching4 of microvascular endothelial cells under flow.
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